The version for , part of the 麻豆原创 Services and Support portfolio, is the helping organizations adopt, activate, and scale the 麻豆原创 Customer Experience and AI innovations announced at 麻豆原创 Sapphire.

The proactive, expert-led engagement model is built to de-risk transformation, accelerate time to value, and sustain measurable outcomes across customer experience initiatives. It combines guided adoption, prescriptive functional and technical assistance, AI-powered best practices, and continuous value realization aligned to the realities of modern customer experience (CX): AI at the core, unified data, omnichannel at scale, retention over acquisition, service-led growth, and persistent skills gaps in a rapidly evolving digital landscape.

At its heart, the Advanced Success Plan for 麻豆原创 Customer Experience brings together the right expertise at the right time, program governance, solution experts, value advisors, and adoption specialists. This helps teams execute faster and smarter with 麻豆原创 Customer Experience.

What sets the Advanced Success Plan apart

• Outcome-based: Business outcomes and key value indicators are co-defined with teams, with milestones and workstreams aligned to deliver measurable Autonomous CX results.
• Proactive by design: AI Assistants, adoption checks, and innovation accelerators are embedded throughout, reducing risk and compressing time to value as agentic capabilities evolve.
• Continuous enablement: Role-based best practices and coaching are tied directly to the Autonomous CX road map, closing skills gaps at pace as new AI and platform capabilities become available.
• Cross-solution orchestration: Unified processes and shared business context across marketing, commerce, sales, and service break silos and enable enterprise-scale execution.

This is the first of a planned series to deep dive on the topics below. Here, we start with introducing how the Advanced Success Plan for 麻豆原创 Customer Experience helps operationalize seven macro trends shaping modern customer experience.

1. AI鈥憄owered customer experiences

AI now underpins everything from next best engagement to intelligent service resolution. The Advanced Success Plan embeds AI adoption patterns directly into the delivery approach, identifying high value use cases, calibrating data prerequisites, and guiding model governance.

The results are prioritization of high鈥慽mpact starting points, a plan to scale with guardrails, accelerating time from pilot to production and grounding every decision in 麻豆原创鈥檚 CX AI capabilities and product road map.

2. Hyper鈥�personalization at scale

Personalization demands more than algorithms; it requires clean, consent鈥慳ware data, robust decisioning, and experimentation discipline. The Advanced Success Plan delivers:

• Data readiness assessments and integration patterns to enrich customer profiles and segments
• Governance and testing playbooks to validate personalization hypotheses at scale
• Prescriptive journeys to operationalize next best action across every customer channel

The result: hyper personalization moves from proof of concept to standard operating model.

3. Unified customer data and breaking down silos

Siloed data undermines CX. We help establish a unified data foundation and harmonized identities, aligning business, data, and integration teams. With technical guidance and adoption accelerators, users can move faster toward a single view of the customer to fuel analytics, personalization, and service excellence.

The results are unified profile use cases, data quality baselines, and source鈥憃f鈥憈ruth decisions to reduce duplication and latency.

4. Omnichannel commerce and B2B digital transformation

Modern buyers expect seamless journeys across web, mobile, marketplace, and partner portals, especially in B2B. The plan accelerates omnichannel capability build鈥憃ut by uniting commerce, order sourcing, pricing, and fulfilment patterns, supported by outcome鈥慴ased governance.

The result: Channel consistency, catalogue and contract complexity, and the alignment of service and sales motions are all addressed, driving measurable improvement in conversion rates and repeat purchase.

5. Customer retention over acquisition

Acquisition costs are rising and retention is the new growth engine. The Advanced Success Plan helps operationalize retention strategies, churn prediction, intelligent engagement, loyalty, and proactive service across the CX stack.

The result: We align metrics such as retention rate, customer lifetime value, and service鈥憈o鈥憆evenue contribution, and ensure the data foundation supports them.

6. Service as a revenue driver

Service is no longer a cost center; it鈥檚 a growth channel. We guide users to productize services, monetize value鈥慳dded offerings, and embed outcome鈥慴ased contracts. The plan includes:

• Playbooks for cross鈥憇ell/upsell from service interactions
• Knowledge and field service patterns to improve first鈥憈ime fix and attach rates, KPI frameworks for service鈥憀ed growth

The result: With prescriptive governance and AI鈥慸riven intelligence, service organizations move from reactive cost management to consistent, measurable contribution to top鈥憀ine revenue and customer retention.

7. Navigating digital transformation complexity and skills gaps

Large transformation programs falter on orchestration and capability enablement. The Advanced Success Plan addresses both by:

• Establishing a cadence of value sprints and decision forums
• Providing role鈥慴ased enablement covering functional and technical assistance, data, product ownership, end-user adoption, and change management
• AI-guided best practices embedded throughout delivery to eliminate rework and accelerate quality outcomes across Industry AI scenarios

Organizations execute with confidence, even amid shifting requirements, resource constraints, and rapidly evolving agentic AI capabilities.

Measurable outcomes

• Accelerated time to first value through prioritized, AI-ready use cases aligned to capabilities
• Higher adoption and sustained performance via continuous enablement
• Reduced program risk through proactive governance, telemetry, and structured decision forums
• Measurable gains in conversion rates, customer retention, and service-led revenue contribution across the full CX stack

Getting started

• Define Autonomous CX priorities: Identify two to three priority outcomes for the next two quarters facilitated by the 麻豆原创 Value Management service.
• Assess readiness: Evaluate data, integration, governance, and enablement gaps to define a 12 to 18 month engagement plan.
• Engage the Advanced Success Plan: Align workstreams, milestones, and metrics with our expert team.聽
• Industrialize and scale: Convert proven delivery patterns into reusable accelerators, deployable across regions and lines of business.

This series will examine each of the seven trends in depth, demonstrating how the Advanced Success Plan for 麻豆原创 Customer Experience translates CX strategy into repeatable execution and measurable business outcomes.

Tara Tracey is a global product owner at 麻豆原创.

AI is what brings that ambition within reach. It helps companies act faster, personalize at scale, and engage in new ways. But it is also raising expectations. Every interaction now reflects how well the business runs.

When a customer places an order or asks for help, the experience depends on what happens behind the scenes. If pricing is inaccurate, inventory is uncertain, or fulfillment falls short, the experience breaks.

That is why customer experience is now defined by execution. Customers do not experience systems or intent. They experience outcomes.

Agentic AI can increase speed, intelligence, and personalization. But speed alone does not improve customer experience. It amplifies what is already there. When execution is aligned with process, data and governance, AI drives better outcomes. When it is not, AI exposes the disconnect.

Aligning experience and execution

Autonomous CX brings agentic AI directly into the processes that run the business instead of layering it on top of disconnected systems. It connects AI assistants across marketing, commerce, sales, and service onto a shared business context across 麻豆原创 CX, 麻豆原创 Cloud ERP, supply chain, and connected systems. Orders, inventory, pricing, and financials are defined once and used consistently, so decisions are based on live operational reality.

At the center of this shift are AI assistants and autonomous agents. Assistants coordinate multiple agents across end-to-end customer workflows, from discovery to fulfillment, engagement to service, and issue to resolution.

At 麻豆原创 Sapphire, we highlighted assistants that make this real across the portfolio:

• In marketing, Content Assistant and Campaign Assistant orchestrate intent understanding, content creation, segmentation, optimization, and campaign execution within governance controls.
• In commerce, Merchandising Assistant, Shopping Assistant, and Order Management Assistant connect discovery, conversion, and fulfillment to operational reality.
• In sales, Sales Assistant, Deal Qualification Assistant, and Deal Closing Assistant move sellers from signal to execution.
• In service, Case Management Assistant and Service Management Assistant improve resolution and service quality, with additional assistants purpose-built for self-service, HR service, and accounts receivable workflows.

AI-driven discovery and engagement grounded in business reality

麻豆原创鈥檚 collaboration with Google follows the same principle: connect AI-driven discovery and engagement to business execution.

Together, 麻豆原创 and Google are focused on three priorities: first, applying the latest AI models, including Gemini, to deliver high-quality customer experiences; second, supporting industry standards and open protocols to enable interoperability across ecosystems; third, enabling seamless, personalized journeys across channels and Google surfaces such as Shopping and Gemini.

By combining 麻豆原创鈥檚 governed business data with Google鈥檚 AI capabilities, assistants and agents can connect customer intent from storefronts, search, and AI-driven channels to 麻豆原创 commerce and order processes. This ensures that what customers see reflects what the business can fulfill.

This is also why 麻豆原创 is adopting and expanding how 麻豆原创 product data can power AI-driven experiences wherever customer intent originates. This keeps experiences aligned with pricing, inventory, and fulfillment in real time.

麻豆原创 Commerce Cloud innovations

麻豆原创 continues to be recognized in analyst evaluations, including the Gartner庐 Magic Quadrant™ for Digital Commerce, where 麻豆原创 has been positioned as a Leader for 11 consecutive times.

, trusted by the largest enterprises, now extends to mid-market and growing companies on 麻豆原创 Cloud ERP. The new 麻豆原创 Commerce Cloud, cloud ERP edition delivers a standardized, end-to-end approach, reducing complexity, leveraging AI natively, and accelerating time to value. It connects discovery through fulfillment via tight integration with 麻豆原创 Cloud ERP.

For digitally mature organizations, 麻豆原创 is expanding composable commerce with new and modular cart and checkout services. These services integrate with core processes such as pricing, promotions, loyalty, tax, payments, inventory, sourcing, and order management across 麻豆原创 and non-麻豆原创 touchpoints. This helps organizations modernize their architecture while maintaining end-to-end execution.

麻豆原创 is also expanding its ecosystem with Vercel to accelerate storefront development and deployment with optimized performance, scalability, and composable front-end experiences.

In payments, 麻豆原创 Unified Payment, powered by Adyen, embeds global processing directly into the commerce flow to simplify integration and improve conversion. 麻豆原创 also continues to enhance its open payment framework with pre-integrated providers, such as Checkout.com and PayPal, giving customers flexible provider choices that are easy to configure and use.

Together, these capabilities reduce total cost of ownership, speed deployment, and make it easier to deliver better experiences at scale.

Sales execution turns insight into action

Customer experience extends into sales execution, where teams need clear next steps and confidence those actions can be fulfilled.

We introduced new innovations, including field sales capabilities for retail execution processes in consumer goods companies and other field-selling environments. These capabilities provide rich mobile experiences that work offline, making it easier to plan store visits, capture in-store activity, and manage execution in real time.

Sales leaders gain connected insights tied directly to pricing, inventory, and order processes, leading to more consistent execution and better outcomes.

Scaling trusted autonomous service

Autonomous CX is strengthened through partnerships that extend execution while preserving trust and governance.

Our combines its agentic AI-driven voice and digital self鈥憇ervice with service, order, and entitlement data from 麻豆原创 Service Cloud. AI-driven automation can handle routine interactions with full context, escalating seamlessly and with continuity to service teams when human expertise is needed. This approach helps organizations scale service without breaking trust and ensures customer interactions remain connected to real business processes.

麻豆原创 is also expanding its partnership with Amazon to scale AI-driven service across voice and digital channels, enabling faster, more consistent resolution while keeping service execution grounded in real-time business data.

Industry AI in action

We are also showcasing Industry AI scenarios that demonstrate how assistants and autonomous capabilities operate in real business environments.

Autonomous Revenue Growth Management supports trade planning teams and key account managers in consumer products companies that sell through retailers, with applicability to agribusiness and wholesale distribution. Industry鈥憇pecific Joule Assistants provide AI鈥慸riven insights across trade planning and execution, helping teams identify growth opportunities, optimize commercial terms and respond more quickly to performance signals. The result is more predictable growth with fewer downstream exceptions.

Unified commerce supports merchandising and operations teams across retail, wholesale, and direct-to-consumer models. Unified commerce connects demand, inventory, and customer data across channels, with Joule Assistants guiding decisions on assortment, pricing, and placement. The result is more consistent execution and faster decisions.

The next phase of customer engagement

Across these innovations and Industry AI scenarios, the pattern is clear. AI delivers value only when it acts on shared, trusted context. When experience and execution stay aligned, speed becomes a source of trust instead of risk.

This is how 麻豆原创 is approaching the future of customer experience: as a coordinated system where every decision is visible, and every promise can be kept.

Balaji Balasubramanian is president and chief product officer of 麻豆原创 Customer Experience.

The CX innovations and Industry AI scenarios highlighted here are planned for general availability in Q3 2026.
The capabilities announced as part of 麻豆原创鈥檚 Autonomous Enterprise run across 麻豆原创 Cloud ERP, including 麻豆原创 Cloud ERP Private.
Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner鈥檚 business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.
Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.

In his kickoff keynote at 麻豆原创 Sapphire Orlando, Florida, Klein and other 麻豆原创 Board members detailed how 麻豆原创 plans to bring agentic AI to the world’s most critical business workflows so that humans and AI can meet the accelerating demands of global business profitably, strategically, and safely.

鈥淭oday I鈥檓 super proud to launch our new 麻豆原创 Business AI Platform, which forms the basis for our vision of the future of business: the Autonomous Enterprise, where agents run the business and you can focus on what truly matters,鈥� Klein said.

Enterprise AI is at an inflection point, Klein told his 30,000-strong in-person and virtual keynote audience, and 麻豆原创 is in a unique position to deliver what customers need to turn their businesses into autonomous enterprises.

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The business AI imperative

Across industries, organizations are investing heavily in artificial intelligence, yet many still struggle to translate that investment into meaningful business value. At 麻豆原创 Sapphire, the message was clear: This isn鈥檛 a technology problem; it鈥檚 a context and execution problem.

While 80% accuracy may be sufficient for consumer AI applications, Klein said, 鈥淓ighty percent is just not good enough when you run the world鈥檚 most business-critical businesses. They [LLMs] should not guess; they should deliver accurate, compliant, and secure outcomes.鈥� 

Klein acknowledged that while adoption of AI has become near-universal, tangible business value remains elusive. Citing a recent Stanford AI survey, he noted that almost every company is now using AI, but seeing only limited return.

The reason, he argued, lies in a structural gap. Above the waterline of enterprise AI, LLMs continue to improve at tasks trained on publicly available data, while below it lies what enterprises truly need: AI that understands mission-critical business data, end-to-end processes, and operates within security, compliance, and governance frameworks.

ERP as the foundation for business AI

麻豆原创鈥檚 answer to this challenge begins with what Klein described as 鈥渢he brain of every company: its ERP system.鈥� For over 50 years, 麻豆原创 has had solutions with incredibly deep process and data domain know-how alongside the governance requirements, compliance controls, and company-specific configurations that define how businesses actually run.

Now, as part of the company鈥檚 new vision, 麻豆原创 plans to infuse this institutional knowledge into AI agents, enabling them to navigate thousands of business processes, select from more than 7 million data fields, and verify identity and access authorizations before returning any output.

鈥淲e鈥檙e bringing together LLMs with 50 years of business know-how stored in our ERP. But to do this, we had to do nothing less than completely reinvent our company,鈥� he told the audience. 鈥淭oday we are very excited to show you the new 麻豆原创 and our vision for the Autonomous Enterprise.鈥�

麻豆原创 Business AI Platform

To bring this vision to life, 麻豆原创 executives on stage announced a series of important innovations, beginning with the launch of the new 麻豆原创 Business AI Platform, a unified architecture bringing together 麻豆原创 Business Technology Platform, 麻豆原创 Business Data Cloud, and AI Foundation under a single roof.

鈥淭he heart of this new platform is the rich context layer,鈥� said Klein. 鈥淗ere, we infuse the deep ERP business domain know-how into the AI agents. Through our knowledge graphs, our AI agents have now a compass, a map, to find the right process and data in your ERP universe. And to provide the agents even more context, we are also introducing our new 麻豆原创 Domain Models. They have been trained on 麻豆原创’s code to even better understand the business logic of your company.鈥�

But, he said, 麻豆原创 is going further: 鈥淏ecause you run your business not only with 麻豆原创 solutions, our AI agents have to also understand non-麻豆原创 data. That’s why we included our 麻豆原创 Business Data Cloud in the context layer to build a single semantical data layer across 麻豆原创 and non-麻豆原创. No more silos, no spaghetti data sprawl鈥攂ecause no AI agent can compensate for a broken data model.鈥�

Echoing Klein, 麻豆原创 CTO Philipp Herzig, who presented the platform in detail, said it has been designed to close the agent adoption gap in the enterprise by delivering outcome, speed, enterprise-readiness, and context. 鈥淚t’s the place where you build, contextualize, reason, and govern AI,鈥� he said.

Herzig explained that the platform is structured around three layers: the context layer which Klein referenced, the build layer, and the governance layer. 鈥淎gents are only as powerful as the context they operate on,鈥� he said. 鈥淟acking context is the number one reason why enterprise AI projects fail to deliver value.鈥�

Within the build layer of the new platform, the new Joule Studio is designed to understand a company鈥檚 business challenges and enables the building of new AI agents quickly and easily.

The third tier is the governance layer, anchored by the new 麻豆原创 AI Agent Hub built on 麻豆原创 LeanIX. This provides a single command center to discover, manage, and govern all AI agents鈥斅槎乖� and non-麻豆原创. It will be generally available in Q3 and included in 麻豆原创 Business AI Platform at no additional charge.

Underscoring the changing AI marketplace, Herzig was joined on stage by KPMG Global Head of Advisory Rob Fisher, who told the audience: 鈥淲hat I鈥檓 hearing from clients is a clear shift; they鈥檙e moving from AI pilots to embedding integrated AI and agents into how work gets done. Where we see leaders really separating from the pack is in the execution and the organizational adaptability.鈥�

麻豆原创 Autonomous Suite

Building on the platform, 麻豆原创 Executive Board Member Muhammad Alam, 麻豆原创 Product & Engineering, announced the transformation of 麻豆原创鈥檚 SaaS application portfolio into the 麻豆原创 Autonomous Suite, described as the most significant evolution of 麻豆原创鈥檚 applications business in the company鈥檚 history.

The suite spans five domains: Autonomous Finance, Autonomous Spend, Autonomous Supply Chain Management, Autonomous HCM, and Autonomous CX, with more than 200 agents and over 50 assistants available in the coming months. Each assistant is mapped to core business roles and carries defined KPIs tracked through 麻豆原创 AI Agent Hub.

鈥溌槎乖� Autonomous Suite brings together the depth of our process expertise, semantically rich data, and built-in governance and compliance,鈥� said Alam. 鈥淭hese agents are designed with outcomes as a core objective. Each assistant has a defined set of ROI KPIs that you can expect it to deliver.鈥� 

鈥淯nderpinning the autonomous suite are out-of-the-box agents鈥攈undreds of agents cutting across all core business processes,鈥� he shared. 鈥淭hese agents come together into what we call assistants, or Joule Assistants. We’ve mapped these assistants to roles across the core processes of an organization, because we know that the first step 
in realizing value from AI is to empower your people to do more, do it better, or do things that just weren’t possible to be done before.鈥�

Turning to Joule itself, Muhammad said 麻豆原创 is fundamentally reimagining how users will interact with 麻豆原创 applications in the future.

鈥淲e call this Joule spaces and along with the familiar Joule conversations experience and Joule Studio 2.0, it is now part of what we call Joule Work,鈥� he explained.

鈥淛oule Work represents a massive step forward in super-charging the capabilities of Joule as we know it today,鈥� Alam said. 鈥淲ith Joule Work, we’re bringing a claw-based agentic harness to Joule along with computer and file access, better support for open standards such as MCP and A2A, access to a more complete knowledge base, and, of course, amazing visualizations on the fly.鈥�

Industry AI: H&M and Sector-Specific Transformation

During the keynote, 麻豆原创 Chief Operating Officer Sebastian Steinhaeuser introduced the Industry AI initiative, delivering AI-powered solutions built on decades of sector-specific expertise across 26 industries. In life sciences, he highlighted how 麻豆原创 customer Takeda is achieving up to 10% productivity gains, up to 25% reduction in revenue loss from stock-outs, and up to five percent reduction in safety stock through Autonomous Regulated Manufacturing.

He was also joined on stage by H&M Group CDIO Ellen Svanstr枚m, who discussed how the fashion retailer is embedding AI across its value chain. Built on RISE with 麻豆原创, 麻豆原创 Business Data Cloud, 麻豆原创 Commerce Cloud, and 麻豆原创 SuccessFactors solutions, H&M has developed a Store Intelligence Agent that processes real-time signals to generate actionable recommendations for store managers. Svanstrom also demonstrated the AI-powered InStore Concierge, a customer-facing agent that bridges digital and physical retail through personalized outfit recommendations and real-time availability.

RISE with 麻豆原创 and 麻豆原创 GROW: Path to the Autonomous Enterprise

Returning to the keynote stage, Klein emphasized that technology adoption alone does not create business value. Simply plugging AI agents into your system landscape will drive zero value, he said. 鈥淢oving to the Autonomous Enterprise requires serious change management. Adoption of AI goes hand-in-hand with business process change and end user enablement.鈥�

To support customers on this journey, 麻豆原创 announced a comprehensive reset of its RISE with 麻豆原创 and 麻豆原创 GROW offerings. RISE with 麻豆原创 customers will receive contractual commitment to activate three Joule Assistants within the first year, with the Max Success Plan extending adoption across the full enterprise.  

麻豆原创 GROW customers will receive more than 20 AI assistants from day one, with an AI-enabled toolchain designed to support go-live in weeks. New partnerships with Palantir and Accenture will support the most complex migration scenarios.

Closing: The Autonomous Enterprise

Klein closed the keynote by asking Joule to summarize the key takeaways and noting that 麻豆原创 is evolving from being a software company to becoming a business AI company.

鈥淲e showed how to turn the promise of business AI into reality with 麻豆原创 Business AI Platform, which provides the data processes and governance AI need to deliver accurate and secure outcomes at scale; we introduced the 麻豆原创 Autonomous Suite, where applications reason, decide, and act for you; and we showed how to manage change management with RISE with 麻豆原创. Together with customers and partners, we showed how 麻豆原创 is helping companies realize the vision of the Autonomous Enterprise.鈥�

鈥淲e鈥檝e been reinventing how businesses run for over 50 years, and now by infusing 麻豆原创鈥檚 ERP brain into the new 麻豆原创 Business AI Platform, we鈥檙e solving one of the biggest challenges businesses are facing today: how to turn AI into business value,鈥� he said. 鈥淚t鈥檚 the end of long negotiations, supply chain disruptions, financial blind spots, and the beginning of better: Welcome to the Autonomous Enterprise.鈥�

The company introduces a unified 麻豆原创 Business AI Platform, deepening partnerships with Anthropic, Amazon Web Services, Google Cloud, Microsoft, NVIDIA and Palantir

ORLANDO聽鈥� At 麻豆原创 Sapphire in 2026, (NYSE: 麻豆原创) introduced the to help enhance the world’s most critical business workflows, so that humans and AI work together to meet the accelerating demands of global business profitably, strategically and safely.

鈥淔or the mission-critical processes of our customers, ‘almost right’ just isn鈥檛 good enough,鈥� said Christian Klein, CEO of 麻豆原创 SE. 鈥淏y uniting 麻豆原创 Business AI Platform with 麻豆原创 Autonomous Suite, we anchor AI agents in the business processes, data and governance so they can deliver accurate, compliant and secure outcomes, unlocking new sources of revenue and meaningful cost savings.鈥�

The Autonomous Enterprise includes a unified AI platform for building, contextualizing and governing agents, an autonomous suite that executes core business operations and a new user experience that redefines how people work with enterprise software.

Introducing 麻豆原创 Business AI Platform

麻豆原创 Business AI Platform is a new foundation for building and deploying enterprise AI grounded in real business context. 麻豆原创 Business AI Platform now unifies 麻豆原创 Business Technology Platform, 麻豆原创 Business Data Cloud and 麻豆原创 Business AI into a single, governed environment.

At its core is the 麻豆原创 Knowledge Graph solution, which gives AI agents a structured map of business entities, processes and relationships across a customer’s 麻豆原创 landscape. Joule Studio is 麻豆原创’s AI-first solution for building enterprise agents, applications and agentic workflows. Developers can build using the no-code, pro-code and AI frameworks of their choice on 麻豆原创-managed infrastructure that is secure, scalable and optimized for enterprise AI.

Deploying 麻豆原创 Autonomous Suite Across Every Business Function and Industry

Building on this foundation, 麻豆原创 also introduced 麻豆原创 Autonomous Suite, which enables 麻豆原创’s existing business applications with AI agents capable of running processes from start-to-finish.

The suite will deploy more than 50 domain-specific Joule Assistants across finance, supply chain, procurement, human capital management and customer experience. These assistants will automate end-to-end processes by orchestrating a subset of over 200 specialized agents to execute precise tasks. For example, the new Autonomous Close Assistant can compress the financial close process from weeks to days by automating journal entries, reconciliation and error resolution across the entire process.

麻豆原创 also launched Industry AI, expanding its deep industry portfolio through seven autonomous solutions that will enable start-to-finish industry processes and embed sector-specific process logic, data models and regulatory requirements. At 麻豆原创 Sapphire, 麻豆原创 showcased its work with European energy giant RWE to leverage Industry AI, helping reduce unplanned downtime across its offshore wind turbines. With 麻豆原创’s Autonomous Asset Management scenario, AI agents are designed to analyze data from thousands of past incidents, identify the likely root cause and generate pre-filled work orders with the right tools and proven fixes from other sites.

Designing the Autonomous User Experience

The company also revealed Joule Work, redefining how users engage with 麻豆原创 software. Instead of navigating individual applications and entering data across several screens, users will now interact primarily with Joule. By describing a desired business outcome, Joule will orchestrate the right combination of workflows, data and agents to get it done.

Joule Work goes beyond conversation, proactively surfacing relevant insights and automating routine tasks behind the scenes so work moves forward even when humans aren’t actively steering it. It will be available on desktop, mobile and voice across 麻豆原创 and non-麻豆原创 systems.

Accelerating the Customer Journey Toward Autonomy with 鈧�100 Million Infusion

麻豆原创 evolved its customer and partner programs to help accelerate the organization’s journey to the Autonomous Enterprise. To catalyze adoption, the company has launched a 鈧�100 million fund for 麻豆原创 partners to help customers deploy 麻豆原创-built AI assistants and agents. The fund is also available to partners that extend or build new partner agents on the new 麻豆原创 Business AI Platform using Joule Studio.

麻豆原创 has enhanced its RISE with 麻豆原创 and 麻豆原创 GROW offerings to accelerate AI adoption. Both include access to the Joule Assistants portfolio; RISE with 麻豆原创 customers will have three assistants activated within their first year, while 麻豆原创 GROW customers receive full portfolio access at onboarding. 麻豆原创 S/4HANA on-premises and 麻豆原创 ERP Central Component (麻豆原创 ECC) customers are not excluded: those that commit to transitioning the majority of their current landscape to 麻豆原创 Cloud ERP gain access to select AI scenarios, bridging the gap between their current landscape and their cloud destination

麻豆原创 also introduced new agent-led transformation tooling that can reduce ERP migration efforts by more than 35 percent, driving faster and more predictable projects by automating system analysis, code remediation, configuration and testing at scale.

Lastly, 麻豆原创 announced a full slate of strategic partnerships across each category:

• Platform and suite partnerships include Anthropic, with Claude among the foundation models 麻豆原创鈥檚 AI platform will leverage to power Joule agents across HR, procurement and supply chain; Amazon Web Services, bringing zero-copy data integration between 麻豆原创 Business Data Cloud and Amazon Athena; Google Cloud and Microsoft, enabling bidirectional agent-to-agent interoperability between Joule and external agent frameworks; Mistral AI and Cohere, delivering sovereign model options on 麻豆原创’s cloud infrastructure; , providing visual AI workflow orchestration inside Joule Studio; NVIDIA, whose OpenShell provides the trusted secure runtime for Joule Studio; and , bringing AI agents into 麻豆原创 Service Cloud to handle customer interactions with full access to business data and service processes.
• Implementation partnerships include Palantir and Accenture, partnering on complex data migration scenarios, and for AI-powered cloud ERP migrations.

.

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About 麻豆原创

As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE: 麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

Note to editors:
To preview and download broadcast-standard stock footage and press photos digitally, please visit . On this platform, you can find high resolution material for your media channels.

For customers interested in learning more about 麻豆原创 products:
Global Customer Center: +49 180 534-34-24
United States Only: 1 (800) 872-1麻豆原创 (1-800-872-1727)

For more information, press only:
Aim茅e Leabon, +1 646-799-3277, aimee.leabon@sap.com, EST
Marcus Winkler, +49 622 776-74-97, marcus.winkler@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2025 Annual Report on Form 20-F.
漏 2026 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see  for additional trademark information and notices.
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Customers can deploy Joule Agents in 麻豆原创 CX Solutions to build, launch, and optimize marketing campaigns

Gemini Enterprise acts as a central hub for agents to take action across 麻豆原创 and Google Cloud platforms

LAS VEGAS 鈥� (NYSE: 麻豆原创) and Google Cloud today announced a new partnership that will help marketers put AI agents to work at scale.

Through new integrations between the 麻豆原创 Engagement Cloud, 麻豆原创 Customer Experience (麻豆原创 CX) and Joule solutions and Gemini Enterprise, joint customers can now deploy agents that securely access unified data stored across both ecosystems to execute complex marketing strategies based on high-level goals defined by the user.

Together, 麻豆原创 and Google Cloud provide a unified foundation for data and AI agents to operate across both ecosystems. Gemini Enterprise will act as a central hub for data integrations and multi-agent coordination, allowing agents to take action across a customers鈥� 麻豆原创 and Google Cloud solutions. These integrations will be supported by the 麻豆原创 Business Data Cloud Connect solution for Google and BigQuery, which enable bidirectional, zero-copy data access between the two platforms, with enterprise-grade security and governance. Capabilities across both Gemini Enterprise and agent gateway APIs from 麻豆原创 will allow customers鈥� agents to more securely exchange context, trigger actions and optimize outcomes across platforms, enabling true multi-agent orchestration.

The integration allows marketers to prompt an agent within 麻豆原创 Engagement Cloud with a clear objective like, 鈥淚ncrease repeat purchases from the last 30 days,鈥� or 鈥淢aximize customer lifetime value while reducing campaign operational costs.鈥� An agent, like a Joule Agent, will handle the end-to-end process鈥攆rom content personalization to visualization to conversational engagement.

鈥淭his is more than a data integration; it鈥檚 a leap forward for AI agents that can collaborate naturally and execute seamlessly,” said Balaji Balasubramanian, President and Chief Product Officer, 麻豆原创 Customer Experience and Consumer Industries. 鈥淏y combining 麻豆原创 Business Data Cloud Connect for Google with interoperable AI agents across 麻豆原创 and Google Cloud, we鈥檙e giving organizations a path from AI experimentation to AI-enabled customer experience at scale. Marketers can spend less time on manual tasks and more time shaping the customer journey.

鈥淭o realize the full potential of agentic AI, businesses need their systems to speak the same language,鈥� said Kevin Ichhpurani, President, Global Partner Ecosystem at Google Cloud. 鈥淏y uniting 麻豆原创鈥檚 enterprise data and customer engagement platform with Google Cloud鈥檚 AI, we鈥檙e enabling marketers to move beyond simple automation to multi-agent orchestration, driving dynamic campaigns that reason and adapt to market shifts in real time.鈥�

According to from 麻豆原创 Engagement Cloud, more than half of marketers say fragmented, outdated data prevents them from acting in the moment. 麻豆原创 and Google Cloud are helping remove that roadblock by unifying data and letting AI agents turn insights into action. Using Joule with 麻豆原创 Engagement Cloud, campaigns can move from planning to activation automatically without manual stitching across tools.

Customers will benefit from autonomous campaign generation, optimization and continuous improved performance. Businesses will achieve faster speed-to-market, lower operational overhead and always-on optimization that drives higher ROI, while giving teams more time to focus on strategy and end-to-end campaign execution.

While marketing is the first example, and will be available to customers in H2 2026, this multi-agent orchestration model is designed to support high-value use cases across the 麻豆原创 CX portfolio, laying the foundation for AI-driven customer experience, powered by trusted, unified real-time data and interoperable agents.

For more information about 麻豆原创 Customer Experience solutions, visit .

For more information about Gemini Enterprise, visit .

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About Google Cloud

Google Cloud offers a powerful, optimized AI stack 鈥� including AI infrastructure, leading models like Gemini, data management capabilities, multicloud security solutions, developer tools and platform, as well as agents and applications 鈥� that enables organizations to transform their business for the Agentic Era. Customers in more than 200 countries and territories turn to Google Cloud as their trusted technology partner.

About 麻豆原创

As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE:麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

Note to editors:
To preview and download broadcast-standard stock footage and press photos digitally, please visit . On this platform, you can find high resolution material for your media channels.

For customers interested in learning more about 麻豆原创 products:
Global Customer Center: +49 180 534-34-24
United States Only: 1 (800) 872-1麻豆原创 (1-800-872-1727)

For more information, press only:
Mallory Kuno, +1 (425) 239-9362, mallory.kuno@sap.com, ET
麻豆原创 麻豆原创 Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2025 Annual Report on Form 20-F.
漏 2026 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see  for additional trademark information and notices.
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Instead, they immediately encounter friction. They鈥檙e asked to repeat information they鈥檝e already shared across multiple channels and departments. Then they see an offer for the item they just purchased, rather than something similar or new. And when they encounter an issue down the line, customer support doesn鈥檛 recognize their history.

Micro moments like these do not feel minor to customers anymore. They feel inexcusable. Customer expectations have changed faster than most brands can keep up. Customers now assume brands know who they are, what they need, and what鈥檚 happening right now. And they expect brands to act on that knowledge instantly.

At the same time, businesses are embracing a new era of AI. Dubbed “agentic AI,” it represents a paradigm shift where AI doesn鈥檛 just analyze or recommend products, but increasingly plans, decides, and acts through a network of agents. This creates a massive opportunity for customer experience (CX) leaders today, in particular marketers, who, according to McKinsey, are leading in AI adoption amongst business functions. But it also raises the stakes.

Because when AI moves faster than your data, systems, and processes, it exposes everything that鈥檚 broken. That tension鈥攂etween rising expectations and disconnected reality鈥攊s exactly what 麻豆原创 and Google Cloud are addressing together.

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The marketer鈥檚 reality: ambition outpacing execution

According to recent , more than half of marketers say fragmented or outdated data prevents them from acting in the moment. Insights arrive too late. Activation requires manual stitching across tools. And even the best strategies stall before they ever reach customers.

It is clear that most organizations genuinely want to deliver great customer experiences. But fragmentation is what stands in the way of delivering connected, meaningful engagements.

On one side: Customers expect effortless, relevant, and real-time experiences. On the other hand, organizations still operate with fragmented data, siloed teams, and delayed insights.

Our latest reveals that customers are increasingly frustrated: 45% say brands can鈥檛 keep up with changing expectations, and 44% say interactions feel less personal than before.鈥�

AI accelerating the engagement divide 

The disconnect between what customers feel and what businesses believe is the “.” Customer signals live across disconnected systems. Data arrives late or without context. Execution happens separately from insight. And while customers feel this friction immediately, many companies do not realize how disconnected their experiences truly are in their customers’ eyes. Now, AI is accelerating this divide.

Agents can generate content, launch campaigns, and optimize engagement at unprecedented speed. But when those agents act on incomplete, outdated, or fragmented data, they only exacerbate inconsistency and poor customer experiences.

When talking to our customers, it鈥檚 clear that there is no shortage of ambition when it comes to AI. In our research, 78% of brands say AI will be integral to their customer retention efforts this year. But only 46% of brands can connect their data in a way that is accessible to power AI sustainably.

The real challenge for CX leaders today is ensuring that AI has the right foundation: trusted data, unified context, and direct connection to execution.

New model for engagement built on trusted enterprise data

麻豆原创 and Google Cloud are expanding their partnership to enable a fundamentally different approach to marketing execution, one grounded in trusted enterprise data and real-time signals, accelerated with multi-agent coordination, and delivered at scale through 麻豆原创 and Google鈥檚 customer engagement solutions.

麻豆原创 provides both operational truth for elements such as inventory, orders, and fulfillment status, and deep customer knowledge across customer experience interactions. Google Cloud brings additional real-time signals and analytics, along with advanced AI. Combined, they create a shared, real-time understanding of the customer, grounded in business and situational context.

At the heart of this partnership:

• 麻豆原创 Business Data Cloud (麻豆原创 BDC) connects semantically rich data across the enterprise with AI to enable real-time insights and drive personalized interactions grounded in business context. This includes 麻豆原创 Business Data Cloud Connect for Google BigQuery.
• Google BigQuery unlocks real-time signals across the Google ecosystem, such as geolocation, weather, and rich analytics, through bidirectional, zero-copy data access with 麻豆原创 BDC, while ensuring enterprise-grade governance and security.
• 麻豆原创 Customer Experience applications provide the real-time behavioral context 鈥� customer profiles, transactions, orders, service interactions, and consented engagement data.
• 麻豆原创 Engagement Cloud activates enterprise data and AI insights and predictions to securely orchestrate real-time, personalized interactions across the entire customer life cycle.

With these innovations, marketers can finally move from insight to execution automatically.

To realize the full potential of agentic AI, businesses need their systems to speak the same language. By uniting 麻豆原创’s enterprise data and customer engagement platform with Google Cloud’s AI, we鈥檙e enabling marketers to move beyond simple automation to multi-agent orchestration, driving dynamic campaigns that reason and adapt to market shifts in real time.

Kevin Ichhpurani, President, Global Partner Ecosystem at Google Cloud

From prompt to performance: how agents work together for marketing

Another critical element of this new execution model is agent interoperability. Gemini Enterprise acts as a central hub for multi-agent coordination, enabling  customers鈥� agents to securely exchange context and take action across platforms. Meanwhile, Joule acts as the engagement layer within 麻豆原创 applications, executing tasks, orchestrating campaign and content workflows, and optimizing marketing outcomes. Working together, 麻豆原创 and Google are enabling true multi-agent orchestration connected to trusted enterprise data.

Within this broader CX transformation, 麻豆原创 Engagement Cloud is where agentic intelligence becomes operational for marketing teams. It is the environment where enterprise signals, generative media, and AI agents translate into real customer interactions and automated lifecycle journeys.

Advanced generative capabilities powered by Google Gemini models, for example, Nano Banana 2, introduce new agentic skills that help CX teams dynamically generate messaging, imagery, and campaign variations. Through assistants and agents in Joule, these capabilities become embedded directly into marketing workflows, allowing brands to adjust tone, localize content, and respond instantly to changing conditions.

It is not just content generation and personalization that are being rewired. With unified data context and interoperable agents, mobile messaging can turn into immersive conversational experiences with Google Rich Communication Services (RCS) and advertising audiences, and creative, which can continuously evolve based on real-time performance and business signals, transforming campaigns into intelligent, self-optimizing systems.

And through this multi-agent network, marketers will not need to build every step of a campaign manually. Instead, they define the goal, gain more time to focus on strategy and creativity, and let agents handle the rest.

For example, a marketer can prompt:

• 鈥淚ncrease repeat purchases from customers in the last 30 days.鈥�
• 鈥淢aximize customer lifetime value while reducing campaign operational costs.鈥�

And from there:

• Joule Agents coordinate content production, grounded in customer and enterprise data, understand business context, customer history, and constraints
• Google鈥檚 Gemini Models and agents generate creative variations, messaging, and channel-specific content
• Agents collaborate across 麻豆原创 and Google Cloud to personalize, activate, and continuously optimize campaigns in real time across engagement channels and media networks

This is more than a data integration. It鈥檚 a leap forward for AI agents that can collaborate naturally and execute seamlessly. By combining 麻豆原创 Business Data Cloud Connect for Google with interoperable AI agents across 麻豆原创 and Google, we鈥檙e giving organizations a path from AI experimentation to AI-empowered customer experience at scale. Marketers can spend less time on manual tasks and more time shaping the customer journey.

Balaji Balasubramanian, President and Chief Product Officer, 麻豆原创 Customer Experience and Consumer Industries

Clear business outcomes for marketing teams

By enabling a network of interoperable AI agents and grounding them in enterprise data and shared context across 麻豆原创 and Google, organizations can achieve measurable outcomes, including:

• Faster speed-to-market through autonomous campaign and content generation
• Lower operational overhead by eliminating manual execution steps
• Always鈥憃n optimization that continuously improves performance
• Higher ROI through relevant, timely, and consistent engagement at scale

Marketers can spend less time managing workflows and more time shaping strategy, creative direction, and customer value.

Beyond campaigns: continuous engagement at enterprise scale

While marketing is a natural starting point, this is just the beginning. Customer engagement does not live in one system or team. Engagement spans commerce, service, sales, supply chain, and operations. A brand promise made in a message must be fulfilled by inventory. A personalized offer depends on pricing, availability, and delivery. And a single customer service interaction can shape the future of customer loyalty and lifetime value.

This multi-agent model is designed to support high-value use cases across the 麻豆原创 Customer Experience portfolio, laying the foundation for an AI-driven customer experience powered by trusted, unified, real-timedata.

In an AI-driven world, customer experience goes beyond any single interaction鈥攊t’s defined by every touchpoint a customer has with your company.

The problem is not the promise of AI. It鈥檚 the gap between intelligence in the system and connection in the moment. Customers are increasingly disengaging because intelligence is not being applied where it matters most.

Technology, particularly AI, has fundamentally changed what customers expect. They assume brands can recognize them across channels, understand context in real time, and anticipate their needs. When that doesn鈥檛 happen, the miss feels less like oversight and more like indifference. Timing is off. Service lacks continuity, and personalization stops at the surface, despite all the data behind it.

While many enterprises are trapped in siloed systems and disconnected data, consumer expectations are growing. Brands that don鈥檛 deliver the expected experiences are quickly abandoned.

In addition, global socioeconomic factors are increasing rapidly and unpredictably, challenging bottom lines and making customer loyalty more critical than ever鈥攁t a time when consumers are less loyal than ever.聽

When economies falter, companies usually take one of two approaches. Some hunker down, cut costs and staff, and hope to survive. Others zero-in on differentiators like to drive growth and boost profitability.

The importance of CX for key metrics like churn, retention, loyalty, new sales, and competitive differentiation is well-established, so not investing in customer experience could be considered akin to saying you are willing to let those mission-critical metrics falter.

The following 15 takeouts from 麻豆原创’s highlight some of the most common CX pitfalls and opportunities.

1. 82% of consumers say a brand has disappointed them

Modern customers do not go quietly into the bad experience night. A whopping 82% of consumers say a brand has disappointed them, even when the product itself meets their needs. The issue isn鈥檛 the product or service; it鈥檚 the experience of purchasing and post-purchase care.

This is the essence of the 鈥溾��: the distance between what customers expect in the moments that matter, and what brands are actually delivering.

2. 60% do not pay attention to brands anymore and 48% care more about experience

Consumer attention in a difficult economy has shifted from logos and taglines to experiences that feel useful, contextual, and personal. So, what鈥檚 a brand to do when 60% of consumers say they simply don鈥檛 pay attention to brands and 48% care more about the experience than the product?

This is where CX outcomes become clear: engagement is no longer about shouting louder; it鈥檚 about showing up better and building experiences powered by unified data and intelligent orchestration.

3. Left unread: only 16% of customers skim email headlines, while 29% read one or two sentences

Consumer behavior in the inbox shows just how fragile engagement is:

• Most consumers only read the subject line
• Others will read one to two sentences before deciding whether to delete or engage further

Combined with the fact that 58% of consumers think most marketing emails they receive aren鈥檛 relevant, brands are staring down a massive relevancy problem. Sending more emails into the engagement abyss doesn鈥檛 solve this problem, but gaining a holistic understanding of your customers as individuals does.

4. 37% do not think brands personalize to their needs

For well over a decade we鈥檝e been talking about the importance of personalization, but today 37% of consumers believe brands don鈥檛 personalize engagements to their needs. Surface-level personalization鈥攏ames in subject lines, basic segmentation鈥攊s no longer enough.

This aligns with our assessment that 79% of companies have low or moderate CEM scores, meaning teams can access portions of shared data and deliver basic personalization, but coordination across marketing, sales, service, commerce, and product teams remains limited. Experiences often feel disconnected, forcing brands to rely on short-term tactics rather than building deeper relationships.

Consumers expect real-time, behavior-driven personalization based on context, intent, and history, not just boiler-plate persona buckets. Customers can see and feel investments in personalization and it matters.

5. 46% say customer service feels too impersonal, while 41% believe brands do not understand them as a person

Considering how much data brands collect, it鈥檚 striking that nearly half of consumers (46%) say customer service feels too impersonal.

Customers are asking a simple, and valid, question: 鈥淚f you have all this information about me, why isn鈥檛 my experience better?鈥� When data doesn鈥檛 translate into empathy and action, it starts to feel like surveillance, not service.

With 46% of consumers saying service isn鈥檛 personal, it should be no surprise that a nearly equal amount (41%) believe that brands don鈥檛 understand them as a person. However, 34% agree that AI can help brands better understand them and what matters most to them.

This presents brands with a real-time opportunity: use AI and data to close the perception gap. Instead of just predicting purchases, enterprises should also be anticipating customer needs and reducing friction.

6. 78% of brands say they deliver seamless cross-channel engagement, consumers disagree

Seventy-eight percent of brands say their engagement strategies offer seamless multichannel experiences with glowing outcomes like increased CLV, retention, and advocacy, but consumers are simultaneously reporting little emotional connection and frequent disappointment. In fact, 44% say that brand interactions feel less personal and more generic than ever before.

The takeaway: internal dashboards can create a if not tied directly to real customer sentiment and behavioral signals across channels.

7. 54% of enterprises cannot access and use real-time data, and 66% still rely on third-party data

Fifty-four percent of enterprises can鈥檛 access and use real-time data. On top of that, 60% suffer from 鈥渄ark data,鈥� which is information that鈥檚 collected but not used throughout the customer journey.

Without real-time, connected data, brands are mostly flying blind. AI, personalization, and omnichannel orchestration don鈥檛 fail because the ideas or execution are wrong; they fail because the foundations are.

Although privacy regulations and legislation are increasing while third-party cookies decline, a majority (66%) of enterprises are still heavily reliant on third-party data. Simultaneously, 55% say their data is too unstructured to use effectively.

The lethal combination of overreliance on external data plus underutilized internal data keeps brands from building strong, first-party relationships rooted in trust and value.

8. 78% of brands say AI is essential for customer retention in 2026

AI is everywhere, and 78% of brands view AI as critical to retaining customers in 2026. However, 66% report they can鈥檛 use AI to optimize campaign performance in practice, while many also note they can鈥檛 utilize real鈥憈ime AI optimization in day鈥憈o鈥慸ay campaigns.

A quick translation of the above stats: an AI strategy is crucial, but execution is lagging because of fragmented systems, poor data quality, and integration issues.

9. Only 30% share engagement data with a CX or CRM platform

Despite the collective agreement that a comprehensive customer profile is important, only 30% of brands share their customer engagement data within a CX or CRM platform. This means that most brands are attempting to deliver personalized experiences without having a unified engagement core.

If engagement data lives in campaign tools, service systems, commerce platforms, and ERP, but never gets connected via CX or CRM, customers will feel every fracture along their journey.

10. 30% of consumers have used AI agents that act on their behalf

AI is not just an enterprise capability; it鈥檚 also a customer behavior. Thirty percent of consumers say they鈥檝e used AI agents to make decisions and act on their behalf when buying from brands.

This is a game-changer when it comes to engagement. Brands are now engaging not only with humans, but also with AI buyers that ruthlessly and continuously optimize for relevance and value. If your systems can鈥檛 keep pace, AI will select your competitor whose systems are operationalized for success.

11. When it comes to customer engagement maturity, 79% of brands have yet to integrate data, systems, and teams across their business; only two in five decision-makers see their departments as actually coordinated

The Customer Engagement Maturity (CEM) scoring model assesses how well brands align people, processes, and technology to deliver cohesive, intelligent experiences. Looking at the 麻豆原创 Engagement Maturity Index:

• 16% of brands reside at low maturity
• 63% sit in the moderate middle
• 21% have high maturity

Despite year-over-year progress, most organizations are stuck in developing or evolving mode, able to execute campaigns but not orchestrate truly connected, enterprise-wide engagement. And leaders agree, with only two in five decision makers believing there is effective collaboration across departments.

12. Just 21% of brands are high-maturity, and they are gaining ground against their competition

High-maturity brands rise above the competition because they connect data and intelligence across marketing, service, sales, commerce, and operations. They use AI and automation to deliver personalized, omnichannel engagement in real-time, at scale.

And the maturity gap is becoming a performance gap. As top performers turn real-time intelligence into growth, the cost of competing with them rises for everyone else.

13. Personalized means personal: 58% of consumers respond positively to localized content

Personalization is more than a word or industry term. It means actually understanding and empathizing with your customer, including their regional traditions and social norms.

When engagement is done right, consumers respond:

• 63% say their favorite brand delivers seamless, connected experiences across mobile, web, and in-store
• 58% value localized content and product recommendations
• 55% appreciate highly personalized content
• 50% believe their favorite brand uses data to make interactions better

Customers aren鈥檛 against data or AI at heart. However, they are opposed to wasted data collection and bad experiences. It鈥檚 the job of brands to provide a great CX. If that job isn鈥檛 taken seriously, you can bet that other brands are willing to roll up their sleeves to fill the gap.

14. 77% of businesses plan to invest in AI-powered engagement in 2026

When it comes to the future state, 77% of businesses plan to invest in AI-powered customer engagement in 2026, and 76% are investing in omnichannel engagement technologies. At the same time, 29% say their top priority is connecting customer and stakeholder data across marketing, sales, service, commerce, and ERP systems.

The signal is clear: investment alone won鈥檛 close the Engagement Divide. The winners will be the brands that invest in connection鈥攐f data, teams, and systems鈥攏ot just in tools.

15. 15% say seamless integration will be the biggest driver of success

Lastly, and possibly most importantly, 15% of businesses believe seamless integration of engagement systems will be the single biggest driver of success. While that may sound like a small number, it captures a critical strategic shift: engagement is no longer a marketing problem or a channel problem. It鈥檚 an enterprise discipline that depends on unified data, coordinated teams, and embedded AI.

Artificial intelligence provides an evolving service for businesses. Employing cloud-based systems that can store, analyze, and route data will be the differentiator for brands in the marketplace.

Loyalty is transactional, and driven by great CX and a connected enterprise

Digital engagement has raised the bar when it comes to customer expectations, with more demands and a plethora of competitive choices if a brand doesn鈥檛 deliver.

It鈥檚 not a big leap to state that better customer experiences increase customer loyalty, which in turn leads to more purchases, augmented product utilization, and increased brand affinity and sentiment. And let鈥檚 not forget that an enhanced CLV lowers customer acquisition costs.

After all, loyalty is transactional and forged by the experiences customers encounter. In my conversations with customers across the globe, it鈥檚 clear that only the brands with truly at the heart of their operations will retain and grow their customer bases in the enterprises of the future.

That ambition relies on a technology foundation that can consistently deliver those experiences at scale. For British-founded luxury fragrance brand Molton Brown, moving from legacy systems to 麻豆原创 Commerce Cloud provided a high鈥憄erformance platform built for peak鈥憇eason resilience and continuous innovation. The impact was immediate: 100% uptime during peak trading, even as volumes surged to one order every three seconds during major events.

This kind of reliability is increasingly critical as the moments that shape experience and loyalty expand beyond owned channels. As product discovery shifts to social platforms and AI鈥憄owered assistants, consistent content and availability help the brand remain visible and trusted wherever customers engage. 麻豆原创鈥檚 evolving agentic commerce innovations are designed for this reality, keeping products discoverable, credible, and actionable across both human and AI interactions.

Ultimately, technology and AI are not the goal鈥攖he experience is. The brands that succeed will be the ones that use AI to show up more human, not less, turning insight into relevance and automation into trust.

The future of CX is for companies that operationalize intelligence across the enterprise鈥攃onnecting data, systems, and teams so AI can orchestrate experiences, not just analyze them.

Manos Raptopoulos is global president of Customer Success Europe, APAC, Middle East & Africa, and a member of the Extended Board 麻豆原创 SE.

AI alone is no longer a differentiator: What matters is where intelligence鈥痮perates鈥痠nside of a business. As demand volatility increases, fulfillment windows tighten, and customer expectations鈥痳ise,鈥痮rganizations need more than insights or task鈥痑ssistance. They need intelligence inside quotes, product content, service interactions, and campaigns, guiding decisions as they happen and continuously adapting as conditions change.

This shift lays the foundation for a new generation of executional AI, where capabilities evolve from supporting users to actively鈥痬onitoring鈥痜lows,鈥痑nticipating鈥痳isk, and over time acting as intelligent agents within core customer-facing processes.

With the Q1 2026 release of鈥� solutions, 麻豆原创 advances this shift by bringing AI closer to day-to-day customer-facing execution across sales, service, commerce, and engagement. Intelligence now operates closer to where outcomes are realized鈥攈elping organizations protect revenue, reduce friction, and deliver consistent, trusted experiences at scale.

Below, explore more of the highlights from the Q1 2026 release. And for full sub-solution details, see recaps for聽,听,听,听, and聽.

Optimize revenue streams with confidence

Revenue becomes more reliable when customer intent is captured early and executed consistently across sales and commerce workflows. The execution depends on speed and accuracy: accurate product information, relevant content, and seamless handoffs from inquiry to quote creation. When these are disconnected, teams face delays, manual rework, and missed revenue opportunities.

From customer inquiry to executable quote

• Email to quote with AI:鈥疉utomatically add SKUs from a deal using opportunity and email data with the Microsoft Outlook add-in for 麻豆原创 Sales Cloud. Users can choose to generate a quote, and the quote is quickly created in 麻豆原创 Sales Cloud in just a few clicks. After review, sellers can hit send; it is that easy.  
• Deep research: Accelerate account planning and reviews by synthesizing 麻豆原创 Sales Cloud and 麻豆原创 Service Cloud data with external market intelligence. For example, the deep research capability can deliver a detailed brief that can be used to better understand the account, their industry, and other crucial information like news and SWOT. Sellers will be able to engage prospects and buyers more effectively while customers will have more relevant and personalized information delivered.  
• Media attachments for product descriptions: Use AI to extract details from product documents, such as manuals, spec sheets, and PDFs, and automatically generate or enrich product descriptions in 麻豆原创 Commerce Cloud. This accelerates catalog updates and improves product data quality so that shoppers, search engines, and agentic commerce are rich with the most accurate product descriptions鈥攅nsuring product descriptions are detailed, differentiated, and discovered.

Delivering鈥痳别濒颈补产濒别鈥痵ervice at鈥痵肠补濒别

• Digital Service Agent handoff鈥痜or case creation: Connect every step of the service journey from conversational AI self-service to field resolution so service teams can resolve customer issues鈥痜aster and provide personalized service engagements that build trust.鈥疷sing conversational cues, Digital Service Agent鈥痵ummarizes intent identification for ticket creation while capturing essential information required for handoff to underlying solutions like 麻豆原创 Service Cloud.
• : Give service teams a single, real-time command center in 麻豆原创 Service Cloud, consolidating cases, tasks, and service orders into one view with visual workload insights so agents can prioritize faster, stay on top of commitments, and resolve more issues per day. 
• Retail Intelligence (麻豆原创 Early Adopter Care): Announced at NRF, Retail Intelligence provides one closed-loop, AI-enhanced retail supply chain planning environment that ties together planning, execution, and engagement. The result: human and agentic teams that don鈥檛 just execute tasks but reshape strategies, reimagine retail supply chain planning, and master autonomous growth and lasting differentiation.
  Learn more at the session.

Orchestrating engagement across the customer life cycle

Customer engagement spans browsing,鈥痯urchasing, fulfillment, and service across multiple channels. 麻豆原创 CX connects engagement directly to operational context.鈥�&苍产蝉辫;

• delivers鈥痯ersonalized, AI-personalized communications and interactions across every channel powered by connected customer and operational data all fully integrated across 麻豆原创. Teams鈥痗an鈥痙eliver consistent, intelligent engagement that builds loyalty and drives鈥痓usiness鈥痠mpact.

• :鈥疎xtend conversational analytics to SMS campaigns. A new data context model narrows analysis to the right dataset, returning faster, more precise answers to natural language questions, such as 鈥淲hat was SMS revenue last month?鈥�

• :鈥疨redictively鈥痠dentify鈥痗ontacts鈥痺ho are鈥痩ikely in the next鈥�30 days to engage,鈥痓ecome inactive, or remain inactive,鈥痵o marketers can target outreach鈥痺here it will deliver the strongest results.鈥��&苍产蝉辫;

Accelerate transformation鈥痺颈迟丑鈥痶丑别鈥痑dvanced success plan鈥痜or 麻豆原创 CX

To鈥痑ssist鈥痗ustomers鈥痮n their鈥痶ransformation鈥痡ourneys, 麻豆原创 launched the new Advanced Success Plan in the鈥�. This will鈥痟elp customers increase the value of individual applications, accelerate cloud transformation across 麻豆原创 Business Suite,鈥痑nd enable consistent adoption of new innovations and 麻豆原创 Business AI.

With expanded coverage with additional 麻豆原创 CX solutions, including and , the advanced offering is comprised of three powerful elements:

• Success expert: Regular 麻豆原创 expertise driving strategic customer outcomes
• Adoption guidance: Structured, AI-driven enablement accelerating adoption
• Activation and optimization services: Hands-on services to maximize performance and impact

Check out the鈥痺ebinar鈥痶o learn how the new service offering unlocks more of the transformative value of 麻豆原创 solutions:鈥�.

Intelligence where execution happens鈥�&苍产蝉辫;

With 麻豆原创 Customer Experience, AI moves beyond isolated鈥痑ssistance鈥痶o鈥痮perate鈥痙irectly within business execution flows. Intelligence is embedded where work happens鈥攊nside quotes, product content, service interactions, and campaigns鈥攈elping organizations respond in real time and deliver consistent customer outcomes at scale.

Learn more about 麻豆原创 CX in Q1鈥�2026鈥�&苍产蝉辫;

Read the 麻豆原创 Help documentation to get started with these new capabilities.鈥�&苍产蝉辫;

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience and Consumer Industries.鈥�

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, our new user experience, is gaining momentum and driving significant impact for our customers. Customers are already efficiency, enhancing processes, improving , and .

Joule is now live across 35 solutions and will continue to meet our customers where they are: across the applications they use, with a firm understanding of their business context and data. That鈥檚 why in Q1 we are embedding Joule into more applications鈥攆rom 麻豆原创 Datasphere, where it can now execute tasks or explain specific functionalities, to 麻豆原创 Intelligent Clinical Supply Management, where users can use natural language to retrieve critical data and navigate to relevant applications.

Joule Agents, such as the Tender Analysis Agent, are boosting customer revenue growth by extracting critical requirements and flagging risks in complex documents. While project managers in 麻豆原创 S/4HANA Cloud Public Edition are saving time setting up projects with the new Project Setup Agent. Plus, there are many more agents to discover below.

Agents are becoming a key new user鈥攁nd enabler鈥攐f enterprise software, joining humans as the only other non-deterministic operators while simultaneously expanding enterprise software鈥檚 scope and usefulness. Our agents will continue to deliver trustworthy, repeatable, and auditable results every time.

We now have over 30 specialized agents and more than 2,500 Joule Skills. The agent-to-agent protocol means our agents work across 麻豆原创 and non-麻豆原创 systems. As the number of agents grows across both, 麻豆原创 AI Agent Hub already today provides customers with the essential infrastructure and guardrails to manage, govern, and discover agents in this new ecosystem.

Some highlights from Q1 2026:

• 麻豆原创 Joule for Consultants is a conversational AI solution that provides expert guidance on cloud transformations, drawing on 麻豆原创鈥檚 knowledge base. To improve trust and traceability, citations are now displayed in a dedicated side panel and can be grouped for clarity. Administrators can enable web search, allowing Joule to draw from public content while maintaining clear source attribution. For tailored answers to problems where the system may not have customer-specific documentation, consultants can now upload up to 10 PDF or text files directly into the chat. This is further enhanced by the inclusion of content from the 麻豆原创 Enterprise Architecture Reference Library, which provides more complete and accurate answers to complex queries. Get started here.
• 麻豆原创 Business AI for supply chain minimizes disruptions and simplifies planning. The Project Setup Agent allows project managers to rapidly establish new projects by drawing on data from past initiatives. 麻豆原创 Integrated Business Planning users can now generate complex formulas in Microsoft Excel with natural language. 麻豆原创 Digital Manufacturing can distill complex manufacturing issues into clear descriptions. Joule is also helping 麻豆原创 Integrated Product Development users create problem reports and requirement models with simple, natural-language commands. Explore more below.
• 麻豆原创 Business AI for finance offers greater efficiency and insight across critical processes. Joule now translates complex e-invoicing errors into plain language. The Dispute Resolution Agent automates root-cause analysis for invoice disputes, while payment advice processing significantly reduces document processing time. Unstructured data, such as PDFs, can now be automatically transformed into sales orders, and accountants can access natural language explanations for complex fixed asset calculations. Users can personalize their home page and easily understand system errors using natural language across 麻豆原创 S/4HANA Cloud Public Edition. Learn more below.
• 麻豆原创 Business AI for procurement and customer experience enhances the entire commercial journey with new capabilities. In procurement, automated statement of work (SOW) creation in 麻豆原创 Fieldglass reduces the time to define deliverables. The Catalog Optimization Agent means e-commerce managers can continuously improve product data quality. In retail, managers can get instant, conversational answers from Joule on order management data. There’s so much more to learn below.
• 麻豆原创 Business AI for IT and developers puts the latest tools and greater control directly into the hands of developers and data professionals. Joule is now generally available in 麻豆原创 Datasphere, enabling users to navigate the platform, get answers, and execute tasks using simple conversational language. The generative AI hub in AI Foundation continues to expand, offering developers access to the newest models, including OpenAI GPT 5.2, Gemini 3.0 Pro, Anthropic Claude Opus 4.6, and Claude Sonnet 4.6. Developers also gain greater power through enhancements such as advanced prompt optimization, metadata filtering, and declarative orchestration configurations in the prompt registry. Additionally, 麻豆原创 Document AI now offers more granular control with custom confidence thresholds and expanded document support. Dive into everything below.
• 麻豆原创 Business AI for industries delivers specialized intelligence to solve unique business challenges. Sales teams can accelerate their response process with the new Tender Analysis Agent, which automates the review of complex RFQ documents to improve win rates. Joule now works with 麻豆原创 Commodity Management to turn verbal or written negotiations directly into detailed draft deals. In life sciences, clinical supply professionals can use predictive analytics to reduce inventory waste costs, and Joule dramatically cuts information search time. 麻豆原创 Self-Billing Cockpit automates invoice data extraction from any format, significantly reducing manual processing time. Discover more for industries below.
• 麻豆原创 Business AI for business transformation management provides the critical insights needed to navigate and accelerate organizational change. Joule is now in 麻豆原创 Signavio, enabling natural-language searches that cut information discovery time. Business process model and notation simulations in 麻豆原创 Signavio provide clear, actionable summaries directly within process diagrams. Meanwhile, enterprise architects can leverage guidance in 麻豆原创 LeanIX to surface actionable insights directly from their architecture inventory, accelerating transformation execution and reducing the time to uncover them. Read more about transformation management below.

Joule

Joule, enhancements

User experience is improved by streamlining startup times and introducing cross-thread search functionality that lets end users find information across all conversation threads without manually checking individual histories. The document grounding capability has also seen a substantial upgrade, now supporting seamless integration with Google Drive.

To set up, see: , , and .

Furthermore, scalability has been greatly improved, as the system now supports up to 8,000 documents per pipeline, enabling large-scale data repositories to be processed and utilized efficiently.

For more information, see .

麻豆原创 Joule for Consultants, enhancements

Enhanced Citation Visibility
麻豆原创 Joule for Consultants has improved how citations are displayed for all identified sources returned by the product. Citations have been relocated to the right side in a dedicated panel for clearer visibility, and now also include public web search results when applicable (see below).

A new grouping feature has also been added, allowing citations to be grouped. This update provides users with a more transparent view of where information originates, strengthens trust, and improves traceability across all responses.

To see the sources and panel, click the sources button below each message; the panel will open on the right, showing all grouped sources.

Enable Web Search
Administrators can now enable/disable web search via the control panel for all assigned end users in 麻豆原创 Joule for Consultants.

When enabled, 麻豆原创 Joule for Consultants will consider public web content in its reasoning and cite relevant public sources in responses when they contribute to the answer. This enhancement gives organizations greater flexibility and transparency by enabling broader coverage of information while maintaining clear source citations for all sources used.

File Uploads in the Joule Message Input
End-users can now upload up to 10 files directly from the conversational message input box and reference them throughout the entire conversation.

Supported file types include PDF and TXT. Each file should be no more than 10 MB/600K characters; for PDFs, an approximation. A 100-page limit applies; if your file is larger, split it into multiple documents. Image files are currently not processed and will be ignored. We are working diligently to make this feature even more useful to end users. This enhancement enables richer, context-aware interactions by allowing you to incorporate your uploaded documents into its conversational responses throughout the session. Please be aware that the standard data privacy terms apply. See also the help documentation for additional information on the free user quota.

Content: 麻豆原创 Enterprise Architecture Reference Library
麻豆原创 Enterprise Architecture Reference Library data has been ingested and is now available for use in conversations. As more data is added, relevant portions may be included in 麻豆原创 Joule for Consultants鈥� responses, enabling more complete, accurate, and context-rich answers to user queries. Since 麻豆原创 Enterprise Architecture Reference Library content cannot be link-referenced, you won鈥檛 see the additional content listed under sources, even though it will be referenced.

Get started .

SECTION

麻豆原创 Business AI for supply chain

Project Setup Agent
Beta release

Project managers can now rapidly establish new projects by drawing on data from similar past initiatives. The agent bypasses complex interfaces and reduces reliance on the project management office (PMO) to facilitate the swift allocation of key resources needed to launch projects effectively. With a 10% reduction in project creation time, 16% faster resource allocation, and 30% less time spent reworking projects due to incorrect templates, teams can shift focus from operational coordination to improving project profitability and driving efficiency.

Get started .

麻豆原创 S/4HANA Cloud Private Edition, AI-assisted retrieval of equipment information in service management
General availability

Service managers using the AI-assisted retrieval feature in 麻豆原创 S/4HANA Cloud Private Edition gain a complete 360-degree view of customer equipment. The feature provides instant access to warranty information and a full history of service transactions, complemented by an AI summary and actionable recommendations. This allows service managers to more efficiently oversee service schedules, reduce potential downtime, and ensure customer equipment operates at peak performance.

Get started .

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted input recommendations for returns order creation
General availability

Returns clerks can accelerate the creation of customer returns with data field recommendations powered by historical data. This feature analyzes past return documents with similar process variants to automatically suggest the most common input values and return reasons, minimizing manual data entry and reducing errors. Organizations benefit from a one percent reduction in data management costs and a five percent decrease in business and operations analysis expenses, enabling returns teams to process orders more efficiently while maintaining accuracy.

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麻豆原创 Integrated Business Planning, AI-assisted MRO inventory analysis
General availability

Inventory planners get a new analytical assistant in the MRO inventory analysis feature for 麻豆原创 Integrated Business Planning. The feature accelerates root cause analysis by generating clear, natural-language summaries that explain the key drivers behind recommended safety stock and reorder points. By translating complex calculations into understandable insights, this capability enables planners to reduce time spent analyzing inventory runs by 30%, leading to faster adoption of outputs and ensuring that inventory parameters align with strategic business goals.

Get started .

麻豆原创 Integrated Business Planning, add-in for Microsoft Excel, AI-assisted planning
General availability

Supply chain planners can now simplify their work with a new AI-assisted planning add-in for Microsoft Excel. Instead of manually creating complex formulas or formatting rules, which often require technical expertise, they can simply describe their needs in natural language, and the system automatically generates the correct syntax. This intuitive way of interacting with the system removes technical barriers and improves a planner鈥檚 efficiency by 10%, freeing them to focus on strategic analysis rather than implementation details.

Get started .

麻豆原创 Integrated Business Planning, AI-assisted system security check
General availability

Supply chain planners and security analysts gain a robust way to assess system configurations against established security recommendations. The feature evaluates compliance states and provides clear guidance on required adjustments, helping administrators identify and address potential gaps while aligning configurations with 麻豆原创 best practices. Organizations can expect a 27% increase in compliance with hardening guidelines and a 32% reduction in the effort required to meet security recommendations. This feature strengthens the protection of sensitive data and reduces the risk of security breaches.

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麻豆原创 Integrated Product Development, AI-assisted problem report creation
General availability

Maintenance engineers can simplify the creation of formal problem reports by leveraging AI capabilities in 麻豆原创 Integrated Product Development. By describing an issue in their own words to Joule, it intelligently extracts key details like the problem name, tags, and priority, and then automatically generates a structured report. This streamlined process dramatically reduces manual data entry and ensures all reports are consistent and compliant with organizational standards, improving overall efficiency.

and get started .

麻豆原创 Integrated Product Development, AI-assisted requirements model creation
General availability

Requirements managers now have a more direct path to creating requirement models within 麻豆原创 Integrated Product Development by using natural language commands with Joule. This feature allows them to initiate new models, specify names, and apply templates in a single step, completely bypassing the need to navigate through complex folder structures. This streamlined approach provides a much faster starting point for new projects and empowers users to begin their work immediately without requiring deep knowledge of the repository layout.

Get started .

麻豆原创 Field Service Management, AI-assisted automated scheduling analytics
General availability

Field service dispatchers and consultants can now access clear, on-demand explanations of auto-scheduling results that demystify complex system logic. The new feature interprets scheduling reports and translates technical scoring details into business-friendly insights, explaining why specific technicians were assigned, why alternatives were passed over, and why certain activities remained unscheduled. This transparency drives a 12.5% increase in dispatcher productivity and a five percent reduction in erroneous resource allocations, strengthening trust in automated decisions while significantly reducing analysis time.

Get started .

麻豆原创 Digital Manufacturing, AI-assisted description enhancement
General availability

Quality managers documenting complex manufacturing issues can now generate clear, objective, and structured descriptions with minimal effort. 麻豆原创 Digital Manufacturing for issue resolution offers description generation that refines rough initial inputs, removes bias and subjective language, and produces balanced, factual problem statements. With support for multilingual translation and enhanced clarity, organizations can achieve up to five percent improvement in quality engineer efficiency during issue handling and up to 10% reduction in errors throughout the problem resolution process.

Get started .

麻豆原创 Business AI for finance

Dispute Resolution Agent (for 麻豆原创 S/4HANA Cloud Public Edition)
Beta release

When invoice disputes arise, accounts receivable specialists need to act quickly without sacrificing accuracy. 麻豆原创 S/4HANA Cloud Public Edition introduces an agent that automates root-cause analysis, scanning invoices, sales orders, delivery records, pricing agreements, and tax rules to identify the source of discrepancies. The agent detects incorrect charges and recommends compliant solutions, such as credit memo creation, enabling finance teams to resolve disputes faster, minimize manual investigation, and cultivate stronger vendor relationships through transparent, efficient processes.

Get started .

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted smart personalization of my home for applications
General availability

麻豆原创 S/4HANA Cloud Public Edition users can easily configure their home page with the most relevant applications through AI-assisted smart personalization. By describing their task in natural language, the system identifies the appropriate app, which can then be added to their home screen with a single click. This intuitive capability reduces the cost of personalizing the home page by 33%, shortens the learning curve for new users, and improves satisfaction by keeping frequently needed tools readily accessible.

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麻豆原创 S/4HANA Cloud Public Edition, AI-assisted error explanation
General availability

When encountering system errors, 麻豆原创 S/4HANA Cloud Public Edition users can turn to a new feature that generates clear, natural language explanations and resolution recommendations. This capability transforms cryptic error messages into easy-to-understand guidance, helping users of all experience levels quickly rectify issues and continue with their work. By reducing error resolution time by five percent, organizations benefit from increased productivity, improved data quality, and shorter training cycles for new team members.

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麻豆原创 S/4HANA Cloud Public Edition, AI-assisted sales order creation from unstructured data
General availability

Sales representatives benefit from a streamlined order creation process in 麻豆原创 S/4HANA Cloud Public Edition that handles unstructured data like PDF or image-based purchase orders. After uploading a file, 麻豆原创 Document AI automatically extracts the relevant information and proposes the data for a corresponding sales order request. This automation significantly reduces manual data entry, minimizes errors, and improves overall operational efficiency, allowing teams to process orders faster and enhance customer satisfaction.

Get started .

麻豆原创 S/4HANA Cloud Public Edition, AI-assisted processing of payment advices with 麻豆原创 Document AI
General availability

Accounts receivable clerks can accelerate their workflow using the 麻豆原创 Document AI-powered payment advice processing feature in 麻豆原创 S/4HANA Cloud Public Edition. The system automatically extracts payment amounts, references, and currencies from diverse invoice formats across multiple languages, with a self-learning capability that continuously improves recognition accuracy. Organizations implementing this feature can reduce document processing time by 70%, cut template maintenance time by 83%, and decrease value loss from manual processing delays by 40%.

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麻豆原创 S/4HANA Cloud Private Edition, AI-assisted fixed asset key figures explanation
General availability

Asset accountants gain clarity on complex fixed asset calculations through a new AI feature in 麻豆原创 S/4HANA Cloud Private Edition. The feature generates natural-language explanations that detail the origins of displayed values and how figures such as depreciation are calculated; for example, illustrating the impact of mid-year acquisitions with specific depreciation keys. This transparency reduces the effort required to analyze asset values, enables faster responses to asset-related questions, and helps mitigate compliance risks.

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麻豆原创 S/4HANA Cloud Private Edition, AI-assisted settlement rule proposal for asset capitalization
General availability

Overhead and asset accountants can now streamline the complex process of creating settlement rules for investment measures, eliminating the traditionally time-consuming, error-prone manual configuration. The solution automatically determines receivers, calculates percentages, and proposes feasible rules based on contextual data and user-defined instruction profiles. Organizations reduce the effort required to create full settlement rules by 50% while simultaneously improving accuracy in asset capitalization and enhancing overall operational efficiency across their financial processes.

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麻豆原创 Document and Reporting Compliance for 麻豆原创 S/4HANA Cloud Private Edition, AI-assisted electronic document error handling
General availability

Tax accountants navigating the growing complexity of e-invoicing mandates across multiple countries gain an easy way to decode technical errors without wading through intricate XML or JSON formats. Joule, integrated with 麻豆原创 Document and Reporting Compliance, delivers plain-language explanations of electronic document errors, enabling faster root-cause identification and more efficient resolution. Organizations get an 80% reduction in time spent understanding and resolving errors, dropping from 150 minutes to approximately 30 minutes. This results in faster processing cycles, reduced penalty risks, and improved cash flow.

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麻豆原创 S/4HANA Cloud Public Edition, AI-assisted error resolution for cost accounting
General availability

Operations managers in retail organizations can now access Joule via 麻豆原创 Order Management Services, enabling them to query order data and receive real-time, role-specific operational guidance across order processing, orchestration, sourcing, availability, returns, and fulfillment flows. Joule surfaces instant insights and recommended actions directly in the workflow, reducing the need to navigate multiple systems. This enables proactive intervention before issues escalate. The feature offers faster transaction access, improved responsiveness and accuracy, and lower operational risk, which support smarter, quicker decisions across the order lifecycle.

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麻豆原创 Business AI for spend management

Expense Report Validation Agent
General availability

Business travelers can enjoy a smarter, guided approach to expense report completion with an agent that proactively identifies missing items, prompts for necessary details, and clarifies confusing alerts throughout the submission process. By simplifying how users understand and resolve issues, the agent ensures accurate, policy-compliant reports with minimal effort required. This means a 30% reduction in time spent preparing and submitting reports, a 24% increase in first-pass approvals, and a noticeably improved employee experience that removes friction from the expense management process.

Get started .

Expense Pre-Submit Audit Agent
麻豆原创 Early Adopter Care

Expense report submitters can now catch receipt accuracy issues and policy breaches before hitting the submit button, avoiding the frustration of rejected reports and delayed reimbursements. This agent automatically reviews expenses during creation, surfacing compliance problems and offering smart suggestions for quick corrections. The agent uses a non-blocking design that keeps users in control of final decisions. Organizations benefit from a 10% decrease in sent-back expense reports, reduced rework for travelers, managers, and auditors alike, and a noticeably smoother reimbursement process that enhances the overall employee experience.

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Expense Automation Agent
麻豆原创 Early Adopter Care

Employees burdened by the administrative chore of creating expense reports can now delegate the heavy lifting to a Joule Agent. This agent automatically builds expense reports by aggregating transactions, populating custom fields based on contextual details and user history, and preparing everything for a quick review before submission. The outcome is up to 30%鈥� reduction in time on task for auto-generated expense reports. This offers a modern expense management experience that slashes manual data entry, accelerates the submission process, and frees employees to focus on high-value work rather than paperwork.

See the demo .

Concur Expense, AI-assisted configuration for audit rules
General availability

Expense administrators responsible for managing complex audit rule setups can now interact with their configuration environment in plain language, eliminating the need for deep technical expertise or tedious manual adjustments. This AI-assisted feature enables admins to search existing rules, create new ones, and receive real-time explanations simply by asking questions like “What rules apply to meals in France?”, delivering clear, actionable guidance instantly. The outcome is a 40% reduction in audit rule configuration effort, fewer support tickets, and empowered administrators who work with greater independence, accuracy, and confidence in maintaining compliance logic.

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Policy Navigator
麻豆原创 Early Adopter Care

Business travelers seeking quick answers to company travel and expense policies no longer need to sift through lengthy documents or wait for admin responses. Policy navigator in Joule allows employees to ask questions in natural language and receive clear, contextual guidance grounded in approved policies, whether planning a trip, in the middle of a journey, or completing an expense report. The result is in-the-moment policy clarity that prevents non-compliant spend before it happens, reduces support tickets, and empowers travelers to make confident, compliant decisions without disrupting their workflow.

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麻豆原创 Business AI for procurement

麻豆原创 Fieldglass Services Procurement, AI-assisted SOW deliverables creation
General availability

Procurement specialists can accelerate the development of their statements of work using the deliverables feature in 麻豆原创 Fieldglass Services Procurement. The feature analyzes the defined project scope and automatically generates precise, relevant deliverables that ensure tight alignment between buyer expectations and supplier commitments. By adopting this capability, organizations can reduce the time required to manually create SOW deliverables by 70% and cut the risk of poor outcomes by 50%, while fostering stronger collaboration during the negotiation process.

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麻豆原创 Business AI for customer experience

Catalog Optimization Agent
General availability

E-commerce product managers tasked with maintaining large 麻豆原创 Commerce Cloud catalogs gain an always-on agent that continuously reviews product descriptions, attributes, and translations against company quality standards. This agent pinpoints merchandising gaps and delivers actionable recommendations to enhance catalog accuracy, ensure consistency across languages, and improve product discoverability. The business impact is a 70% reduction in time to translate catalog data, 65% less time spent adding descriptions per asset, and a five percent reduction in data quality costs, all of which contribute to higher conversion rates and a more agile merchandising operation.

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麻豆原创 Revenue Growth Management, AI-assisted trade promotion creation
General availability

Key account managers in consumer industries can benefit from a streamlined, single-view promotion-creation experience in which simply naming a promotion automatically populates key fields. Drawing on master data, historical promotions, and learned preferences specific to each retailer, the system suggests dates, types, durations, and sell-in periods, then continuously refines its recommendations based on user edits over time. The impact is a 75% reduction in promotion setup time, 30% fewer data-entry errors and rework, and increasingly personalized suggestions that eliminate repetitive manual effort across promotion cycles.

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麻豆原创 Business AI for IT and developers

Joule Studio code editor and Joule Studio CLI

Building on the transformative capabilities of Joule studio low-code, 麻豆原创 is expanding the Joule studio family with two powerful new offerings designed to meet developers exactly where they work: Joule Studio code editor, a Visual Studio Code IDE extension, and Joule Studio CLI, a versatile command-line interface. Together, these tools deliver a unified, AI-assisted development experience that spans the full spectrum of development personas and preferences on Joule.

• Joule Studio code editor brings the intelligence of Joule directly into Visual Studio Code, the world’s most popular development environment, empowering pro-code developers with AI-guided scaffolding, contextual code generation, intelligent recommendations, and seamless integration with Joule, all without leaving their preferred IDE. 
• Joule Studio CLI extends this same power to the terminal, enabling developers and DevOps teams to automate project creation, manage configurations, execute deployments, and orchestrate CI/CD workflows through scriptable, command-line commands鈥攊deal for headless environments, automation pipelines, and teams that value speed and precision at the command line.

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Joule with 麻豆原创 Datasphere
General availability

Data professionals working within 麻豆原创 Datasphere can now accomplish informational, navigational, and transactional tasks through natural conversation with Joule. Whether asking how to use specific functionalities, retrieving details about a 麻豆原创 Datasphere instance, or switching system settings like language preferences, users receive instant answers with direct references to product documentation. Joule can even execute tasks directly from the conversation without requiring interaction with the standard interface. This direct execution reduces reliance on internal IT support and enables faster, more intuitive navigation throughout the platform.

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麻豆原创 Document AI, enhancements

Document level confidence
Customers now set confidence ranges for fields in the Schemas feature. When customers edit field settings, they can define their own thresholds for low, medium, and high confidence. These custom settings are reflected in the extraction results displayed for the relevant fields on the document details screen. See and .

Expanded Transportation Management
Customers can now use the Transports feature to export and import channels and workflows. See .

New schemas: business partner + delivery note for WM
The service plans embedded edition and premium edition now also support the standard document type, business partner document. See the list of supported document types in . Get started with 麻豆原创 Document AI, and .

Generative AI Hub in AI Foundation, enhancements

Metadata
Customers can now manage metadata for documents, collections, and chunks created with the Vector API to enable advanced filtering and organization of their content. For more information, see .

Retrieval API
Customers can merge and rank search results across multiple data repositories using the Retrieval API’s post-processing capabilities. For more information, see .

Prompt optimizations
Custom metrics are supported in prompt optimizations, enabling customers to define and optimize prompts based on their specific evaluation criteria. Only LLM-as-a-judge metrics with numerical or Boolean output types can be used in optimization tasks.For more information, see and . Customers can provide separate test and train datasets for prompt optimization. For more information, see .

Prompt registry
The prompt registry now enables customers to create and manage orchestration configurations declaratively, allowing them to version and track complex AI workflows alongside their prompts for better governance and reproducibility.For more information, see .

Secrets
Customers can now enter generic secrets using a form instead of JSON. The form appears in the Add Generic Secret dialog when you activate document grounding. A dropdown menu lets them choose the type of document repository. Depending on their selection, the remaining fields adjust dynamically, allowing them to complete the data. Some fields are already prefilled.If they prefer working directly with JSON, switch to the code view by clicking the 顒� icon. For more information, see .

New models available
New models are supported, including OpenAI GPT 5.2, Gemini 3.0 Pro, Perplexity Deep Research, and Anthropic Claude Opus 4.6.For more information on new and deprecated models, .

麻豆原创 Joule for Developers, ABAP AI capabilities, enhancements

New ABAP AI capabilities mean developers can expect a 20% reduction in time and effort to write ABAP/JAVA code, 25% reduction in time and effort to test ABAP/JAVA code, and 4.4% faster time to realized value.

This quarter, developers can now easily generate ABAP Unit tests for:

• Public, protected, and private methods of global ABAP classes
• Public methods of local classes within global class pools

See .

In addition, the documentation chat allows developers to interact with documentation on the 麻豆原创 Help Portal, providing context-aware answers and links to relevant documentation. This capability enhances productivity by offering quick access to related documentation directly within the development environment. See .

Finally, developers can now get AI-powered explanations of their ATC findings and code in the Custom Code Analysis/Custom Code Migration app. See and .

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麻豆原创 Business AI for industries

Tender Analysis Agent
General availability

Sales teams can elevate their tender response process with the Tender Analysis Agent, which automates the review of complex RFQ documents. The agent extracts critical product requirements, flags potential risks and policy gaps, and suggests optimized configurations tailored to customer needs. By reducing the effort to process incoming tenders by five percent and improving win rates, organizations can achieve measurable revenue growth while accelerating sales cycles and uncovering valuable cross-sell and up-sell opportunities.

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麻豆原创 Commodity Management, AI-assisted commodity work center
General availability

Commodity traders can transform how they capture and manage complex deals using the commodity work center in 麻豆原创 Commodity Management. Working alongside Joule, the feature converts verbal or written negotiations into detailed draft deals, automatically populating the numerous fields that traditionally require extensive manual entry. This enables traders to redirect their focus toward negotiating better commercial outcomes, while improving data accuracy and driving greater operational efficiency across their trading activities.

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麻豆原创 Intelligent Clinical Supply Management, AI-assisted predictive subject dynamics
General availability

Clinical trial coordinators seeking to boost their supply planning capabilities will find a powerful ally in 麻豆原创 Intelligent Clinical Supply Management. The predictive subject dynamics feature analyzes historical and real-time data to forecast patient enrollment trends and dropout rates, automatically generating insights that would otherwise require extensive manual analysis. This enables supply chain teams to redirect their focus to strategic decision-making, while reducing clinical inventory waste costs by up to two percent and improving demand forecasting accuracy across their trial operations.

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Joule with 麻豆原创 Intelligent Clinical Supply Management
General availability

Clinical supply professionals juggling multiple tasks and complex systems need quick access to information without disrupting their workflow. Together with Joule, 麻豆原创 Intelligent Clinical Supply Management delivers an intuitive, conversational interface that understands natural-language requests, enabling users to retrieve critical data and navigate to relevant applications effortlessly. This streamlined experience results in an 83% reduction in time spent on information searches, freeing teams to concentrate on higher-value activities and significantly boosting overall productivity.

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麻豆原创 Self-Billing Cockpit, AI-assisted document processing
General availability

Billing clerks managing self-billing workflows frequently encounter invoices arriving in a mix of formats鈥擡xcel, PDF, CSV, or text files鈥攐ften unstructured and spanning multiple languages. 麻豆原创 Self-Billing Cockpit addresses this challenge by leveraging intelligent document processing to parse and extract invoice data from virtually any format, converting it into structured payloads ready for automated billing. The result is significantly reduced time spent processing invoice line items, fewer customer-specific interfaces for integration specialists to build and maintain, and improved extraction accuracy through minimized manual intervention.

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麻豆原创 Business AI for business transformation management

Joule with 麻豆原创 Signavio solutions
General availability

Process analysts and optimization specialists working across complex organizational workflows require rapid access to diagrams, documentation, and performance metrics. 麻豆原创 Signavio solutions integrate with Joule to enable natural-language keyword searches across process diagrams, dictionary items, and help resources. At the same time, best-practice KPI recommenders guide users to the most relevant success measures. This intuitive approach delivers 50% faster information searches and navigation, ensuring teams make data-driven decisions with improved search quality and an enhanced overall user experience.

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麻豆原创 Signavio solutions, AI-assisted business process model and notation simulation insights
General availability

Process analysts leveraging 麻豆原创 Signavio can now access embedded business process model and notation simulations directly within their process diagrams, eliminating the need for fragmented tools and manual interpretation. Key metrics such as costs, cycle times, and resource utilization are automatically translated into clear, actionable summaries that highlight bottlenecks and opportunities for improvement. This streamlined approach reduces time to access process modeling insights by 50%, empowering teams to compare scenarios effortlessly and communicate findings to stakeholders with greater confidence and clarity.

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麻豆原创 LeanIX solutions, AI-assisted architecture guidance
General availability

Enterprise architects seeking to accelerate transformation initiatives can leverage 麻豆原创 LeanIX to surface actionable insights directly from their architecture inventory. The feature analyzes enterprise architecture data to identify opportunities and guides users through the workflows and tasks needed to efficiently act on recommendations. Organizations benefit from a 95% reduction in time to discover insights, 80% faster transformation execution, and a five percent reduction in value erosion from delayed action. Overall, this feature drives greater architectural productivity and more agile decision-making.

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Jonathan von Rueden is chief AI officer of 麻豆原创 SE.

*Disclaimer: This article provides estimated benefits. All calculations are estimates based on 麻豆原创 customer case studies, 麻豆原创 benchmarks, and other research. Actual benefits may vary and may be affected by additional factors not considered by this article. The information is provided 鈥渁s is鈥� without warranty of any kind, expressor implied, and in no event shall 麻豆原创 be liable for any damages whatsoever in relation with the use of this article. See Legal Notice on for use terms, disclaimers, disclosures, or restrictions related to this material.

These critical pre-purchase moments generate interest and open pathways toward deeper customer relationships. Organizations that convert interest into measurable outcomes with clarity, accuracy, and speed strengthen the overall customer experience, thereby boosting loyalty and bottom lines.

CX becomes even more meaningful as opportunities progress into clear agreements supported by accurate configuration, pricing, and quoting. This transition from opportunity to agreement represents one of the most consequential stages in the customer journey.

Lead-to-cash represents a coordinated motion across sales engagement, pricing precision, service alignment, and performance visibility. When these capabilities operate together, organizations deliver consistent customer experiences while maintaining operational clarity.

Eight years running: a leadership signal at the heart of lead-to-cash

Within the lead-to-cash journey, quoting connects sales engagement, performance management, service continuity, and ERP alignment. It represents a critical moment where customer intent is translated into accurate pricing, configuration, and agreement terms.

When 麻豆原创 CPQ operates within 麻豆原创 Customer Experience, it becomes part of a connected lead-to-cash motion that spans 麻豆原创 Sales Cloud, 麻豆原创 Service Cloud, sales performance management solutions, and 麻豆原创 ERP. Sales teams engage with structured opportunity data and guided pricing logic. Service teams inherit full visibility into agreed terms. Performance leaders access insights grounded in accurate pipeline and quoting data.

When it comes to this level of intelligent, real-time, connected processes, very few companies can compete. 麻豆原创 was again recognized as a Leader in the 2025 Gartner庐 Magic Quadrant™ for Configure, Price, and Quote Application Suites. This marks the eighth consecutive year 麻豆原创 has been positioned in the Leaders quadrant based on Ability to Execute and Completeness of Vision.

麻豆原创 CPQ supports organizations in producing accurate quotes — even in environments with advanced configuration and pricing requirements — helping accelerate sales cycles and improve sales execution across complex selling environments.

Extending CPQ leadership across 麻豆原创 Customer Experience

In modern enterprises, quoting connects directly to demand generation, pipeline management, contract processes, fulfilment, and service delivery. brings together commerce, customer data, marketing, sales, service, and sales performance management into an integrated portfolio designed to support truly connected customer journeys.

Within this portfolio, 麻豆原创 CPQ plays a pivotal role in the lead-to-cash journey. When integrated with 麻豆原创 CX solutions, it helps align pricing strategy, product configuration, customer agreements, and sales performance insights across the revenue lifecycle. The result is a more reliable transition from opportunity to revenue realization.

Connected lead-to-cash experience

For CX leaders, lead-to-cash is a core driver of experience differentiation and revenue execution. A connected lead-to-cash strategy ensures that:

• Customer intent is translated into accurate configuration and pricing.
• Sales engagements reflect approved pricing and product standards.
• Customer agreements are consistently captured and supported across systems.
• Sales performance and revenue outcomes remain visible and aligned across teams.

Business impact of connected lead-to-cash

Lead-to-cash determines how consistently organizations translate customer engagement into measurable outcomes.

By combining 麻豆原创 Customer Experience capabilities with a CPQ solution recognized for its ability to execute and completeness of vision, organizations strengthen alignment across sales, pricing, service, performance management, and ERP systems, transforming engagement into measurable outcomes with confidence and precision.

In today鈥檚 environment, customer experience and operational precision are closely connected. Strength in one reinforces performance across the other.

You can learn more about how 麻豆原创 CX connects 麻豆原创 Sales Cloud, 麻豆原创 CPQ, 麻豆原创 Service Cloud, sales performance management solutions, and 麻豆原创 ERP across the lead-to-cash journey .

Sindy Conway is senior Product Marketing consultant for 麻豆原创 Customer Experience.

In today鈥檚 omnichannel reality, delivering that elevated experience consistently and at scale is essential to protecting brand trust and loyalty. Peak moments like Black Friday and Cyber Monday amplify the challenge, when traffic surges and expectations for fast, personalized service are at their highest.

The team recognized that legacy systems couldn鈥檛 provide the speed, stability, or connected view required to meet those expectations at scale, prompting a shift to a modern customer experience (CX) foundation with 麻豆原创.

Modernizing the digital core with 麻豆原创 Commerce Cloud

Moving from legacy technology to gave Molton Brown a high鈥憄erformance engine designed for peak鈥憇eason reliability and continuous innovation. The results came quickly: 100% uptime during peak trade, even as volumes spiked to one order every three seconds during major events, freeing teams to focus on enhancing the customer experience rather than firefighting, and ensuring uninterrupted service for customers across global markets.

鈥淧eak performance isn鈥檛 a one鈥憈ime effort; it鈥檚 about reliability. We have to rely on technology operations to achieve 100% efficiency so the business can succeed, which in turn helps our customers succeed. Technology should enable business success, not block it鈥攁nd 麻豆原创 has proved that multiple times.鈥�

Naresh Krishnamurthy, Senior Manager 鈥� Business Transformation, Prestige, Kao UK Ltd

That stability also matters as product discovery increasingly begins beyond owned channels鈥攆rom social platforms to emerging AI鈥憄owered assistants鈥攚here consistent, trustworthy content and availability help the brand stay visible and credible wherever customers choose to engage. 麻豆原创鈥檚 evolving agentic commerce innovations anticipate this shift, ensuring products remain discoverable, trusted, and actionable across both human and AI agents.

A seamless luxury journey across channels

With and (formerly 麻豆原创 Emarsys) working together, Molton Brown aligns what customers see online with what they experience in store. Product categories, storytelling, and navigation are mirrored across channels; store associates can act on online browsing signals; and store teams are enabled with real鈥憈ime insight to deliver high鈥憈ouch clienteling experiences.

The result is an unbroken, premium journey that reduces friction and reinforces trust in the brand鈥攅xactly what luxury shoppers expect.

Personalization that builds loyalty, not just transactions

麻豆原创 Engagement Cloud helps Molton Brown deliver channel鈥慳ppropriate experiences, from mobile鈥慺irst engagement to email and in鈥憇tore clienteling, aligned to evolving customer preferences. These programs are complemented by thoughtful gifting moments, personalized birthday acknowledgments, and sustainability鈥慺ocused communications that strengthen repeat鈥憄urchase behavior.

Crucially, the team treats every holiday period as a data鈥憆ich learning cycle: months of performance testing, UX refinements, and campaign iteration inform what customers experience in the following season. Those insights help the team refine the experience so it remains consistent, intuitive, and premium, even under peak pressure. That consistency is what sustains loyalty, not just the promotions themselves.

As Naresh Krishnamurthy explains: 鈥淏lack Friday is not just about revenue; it鈥檚 about brand engagement and building the strong foundation that enhances the relationship through loyalty.鈥�

Ready for the next era of intelligent commerce

With a dependable CX core in place, Molton Brown is now exploring to anticipate risks ahead of campaigns, sharpen decision鈥憁aking, and streamline fulfillment鈥攁ugmenting the experience behind the scenes without compromising luxury standards.

This direction aligns naturally with 麻豆原创鈥檚 broader agentic commerce vision, where AI systems help interpret intent and keep trusted products discoverable and transactable across new surfaces鈥攁nother reason a reliable, 鈥渕achine鈥憆eadable鈥� CX foundation matters.

“Everything we鈥檙e doing ladders up to one goal: a truly connected customer experience鈥攑ersonal, consistent, and effortless in every channel.”

Molton Brown鈥檚 partnership with 麻豆原创 CX has reset what鈥檚 possible at peak, and every day after: dependable operations, consistent omnichannel experiences, and personalization that earns loyalty. The brand now scales confidently during its biggest moments, and stays ready for what鈥檚 next as AI changes how people (and agents) discover and buy.

This transformation positions Molton Brown to adapt quickly as customer expectations and digital commerce behaviors continue to evolve.

To explore how 麻豆原创 Commerce Cloud can elevate your customer experience, visit .

麻豆原创 is recognized in the 2026 Gartner庐 Magic Quadrant™ for Personalization Engines. 麻豆原创 Engagement Cloud now brings 麻豆原创鈥檚 trusted enterprise backbone to the customer experience, enabling organizations to connect customer insight and operational execution in real time. It builds on market-leading personalization capabilities.

麻豆原创 Engagement Cloud also incorporates AI鈥慹nabled insight to support responsible, efficient scaling of personalized engagement.

As part of this evolution, 麻豆原创 also announced 麻豆原创 Engagement Cloud, enterprise edition, which provides advanced administration, governance, and content and data鈥慶ontrol capabilities for organizations operating across multiple brands, regions, and teams.

鈥淭his approach helps organizations maintain consistency, compliance, and brand standards globally, which is increasingly important in an age of AI decision-making and automation, while also staying responsive to local needs,鈥� said Joanna Milliken, Head of 麻豆原创 Engagement Cloud.

For example, a global consumer goods company operating dozens of brands and regional teams can manage engagement roles, permissions, and data centrally while allowing local teams to execute the relevant interactions. When inventory levels, fulfillment delays, or service disruptions occur, engagement can adapt without manual coordination across disconnected systems.

Existing capabilities of the 麻豆原创 Emarsys solution remain available within 麻豆原创 Engagement Cloud. Customers can adopt new capabilities incrementally, based on their priorities and readiness. 麻豆原创 Engagement Cloud, enterprise edition, will be available beginning February 19, with additional innovations delivered through 麻豆原创鈥檚 innovation road map.

Visit the . Get 麻豆原创 news via  and .

Media Contact:
Mallory Kuno, +1 (425) 239-9362, mallory.kuno@sap.com, ET
麻豆原创 麻豆原创 Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.聽 Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 2026 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

We believe this recognition reflects the continued momentum of in helping enterprises orchestrate real鈥憈ime, AI鈥憄owered engagement at a global scale, connecting data, channels, and experiences to drive measurable business impact.

Helping brands scale AI-powered engagement across channels

Leading brands鈥攊ncluding , John Frieda, PUMA, and Gibson鈥攗se 麻豆原创 Engagement Cloud to deliver connected, personalized journeys that increase engagement, accelerate growth, and build long-term customer loyalty.

According to the report, 麻豆原创鈥檚 ability to support enterprise鈥慻rade, real鈥憈ime engagement across channels remains a key differentiator. 麻豆原创鈥檚 personalization capabilities are powered by advanced segmentation, embedded AI decisioning, and intelligent triggering to deliver timely, relevant, and consistent experiences.

Organizations using 麻豆原创 continue to see measurable outcomes, including improved customer loyalty, higher conversion rates, and increased average order value.

Driving measurable business impact with event鈥慴ased and behavior鈥憀ed orchestration

We believe this year鈥檚 placement also reflects 麻豆原创鈥檚 strength in orchestrating engagement using real鈥憈ime behavioral, transactional, and operational signals across the business.

With 麻豆原创 Engagement Cloud, brands can activate journeys triggered by events occurring across their business to:

• Boost retention through timely, context鈥慳ware engagement
• Increase conversions with more relevant, personalized interactions
• Strengthen loyalty through connected, lifecycle-driven touchpoints

These results demonstrate 麻豆原创鈥檚 ability to move enterprises beyond channel execution toward true omnichannel orchestration.

Unifying customer experiences with native 麻豆原创 integration

麻豆原创 Engagement Cloud connects marketing, commerce, service, loyalty, sales, and operational data, creating a unified, real-time customer view that powers intelligent engagement across every touchpoint.

This bi鈥慸irectional flow of data gives every customer鈥慺acing team access to the same real鈥憈ime customer view, helping brands drive revenue impact, reduce churn, and improve service outcomes.

Global scale, flexibility, and trust

麻豆原创鈥檚 long鈥憇tanding global footprint and enterprise-ready architecture continue to support its leadership positioning. With a cloud鈥憂ative, composable foundation, embedded privacy and compliance capabilities, and a robust partner ecosystem, 麻豆原创 enables organizations to securely and reliably scale personalized engagement across regions and business models.

Whether operating in five markets or 50, enterprises rely on 麻豆原创 to deliver personalized experiences with confidence.

Customer success reflecting real鈥憌orld impact

Customers on Gartner庐 Peer Insights™ continue to recognize 麻豆原创 for ease of integration, deployment support, and customer partnership. Recent examples include:

• , which uses 麻豆原创 for CRM and marketing automation that supports interaction and communication with customers to increase buyback, retention, and loyalty. This includes CRM ads, push notification apps, personalization campaigns, e-mail and SMS campaign execution, and website and app personalization and recommendations.
• , which increased sales by 30% in three years by using 麻豆原创 solutions, to interact directly with customers within highly personalized omnichannel journeys.
• , which saw a more than 40% increase in CRM revenue and more than 150% in commerce traffic during the holiday season by using 麻豆原创 Customer Experience solutions that empower CHRIST to put customers at the center of everything the company does.

These results highlight the tangible value organizations are achieving with 麻豆原创鈥檚 AI-powered personalization capabilities.

We feel 麻豆原创鈥檚 recognition as a Leader in the 2026 Gartner Magic Quadrant for Personalization Engines underscores the strength of its strategy and continued innovation across 麻豆原创 Engagement Cloud. 麻豆原创 remains committed to helping brands activate data, personalize interactions, connect experiences, and scale engagement with confidence.

Visit 麻豆原创 Engagement Cloud area of sap.com to .

Sara Richter is CMO of 麻豆原创 Emarsys.

Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.
Gartner, Magic Quadrant for Personalization Engines, By , , , , 3 February 2026
Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner鈥檚 Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

鈥痚nables organizations鈥攈owever complex, across however many channels, and regardless of which CRM they run鈥攖o produce quick and聽accurate聽quotes, accommodating the most advanced configuration and pricing requirements,听resulting in聽a better sales experience and faster sales cycles.

Gartner evaluated 16聽vendors and聽named 麻豆原创 a Leader based on our Ability to Execute and Completeness of Vision.聽We believe this聽recognition serves as an acknowledgment of 麻豆原创鈥檚聽ongoing聽commitment to providing customers with a CPQ solution that can meet聽and exceed聽their needs.聽

麻豆原创 CPQ is an essential聽component聽of the 麻豆原创 product portfolio that help automate the quote-to-cash process, which enables organizations to convert sales opportunities into profitable repeat customers. 麻豆原创 customers can transform to 鈥渆verything-as-a-service鈥� with innovative revenue models, quickly adapt to聽market聽changes,听support multiple sales聽channels,听and support聽regulatory聽compliance with end-to-end automation.听听

Our customers are the reason we do this, and they participated in the  process by providing reviews that included: 

• 鈥淚t just makes the whole sales cycle move faster.鈥�
• 鈥淚t was relatively simple to onboard when I was a new user鈥澛爌latforms and creating value for customer.鈥�
• 鈥淲e had a very positive experience with 麻豆原创, the platform is scalable, stable.鈥�
• 鈥淎n intuitive user interface that simplifies configuration, robust integration capabilities. Powerful customization options.鈥�
• 鈥溌槎乖� CPQ is amazingly stable and consistent product with the ability to connect with different platforms and creating value for customer.鈥�

Customer case studies provide descriptions of specific value. For example, , has increased聽the number of quotes created per month by 70 percent.聽

鈥淵ou聽basically give聽the salesperson one to two days of their week back by using 麻豆原创 CPQ,” noted Dominic Kasten, director of Sales Technologies for聽.聽“When you give time back to salespeople, you are encouraging them to sell solutions to customers instead of just reacting to specifications.”

Hear from other customers and learn more about how 麻豆原创 helps to automate quote-to-cash with鈥槎乖� CPQ,鈥�,鈥�, and鈥� at sap.com.

David Imbert is head of Product Marketing for Finance at 麻豆原创.聽
Lawrence Martin is chief product officer for Finance at 麻豆原创.聽

Gartner, Magic Quadrant for Configure, Price, and Quote Application聽Suites, Luke聽Tipping, Mark Lewis, January 22, 2026聽
Gartner does not endorse any company, vendor,听product聽or service depicted in its publications, and does not聽advise technology users to聽select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner鈥檚 business and technology insights organization and should not be construed as statements of fact. Gartner聽disclaims聽all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.
Gartner and Magic Quadrant are聽a trademark聽of Gartner, Inc., and/or its聽affiliates. This聽graphic was published by Gartner, Inc. as part of a larger research document聽and should be evaluated in the context of the entire document. The Gartner document is available upon request from 麻豆原创.聽

Agentic AI was everywhere at NRF, emblazoned across the booths of technology exhibitors and the focus of many of the daily conference sessions. The message was simple: retailers face a major upheaval as consumers switch from traditional browser-based search to AI-enabled product discovery.

Consumers are rapidly adopting AI agents to help them find, compare, and, increasingly, buy products鈥攖his while many brands are still optimizing for search engines and are quietly disappearing from the models driving the next generation of product discovery.

鈥淎gentic commerce鈥攕hopping powered by AI agents acting on our behalf鈥攔epresents a seismic shift in the marketplace,鈥� McKinsey, the strategic management consultancy, noted in a . 鈥淚t moves us toward a world in which AI anticipates consumer needs, navigates shopping options, negotiates deals, and executes transactions, all in alignment with human intent yet acting independently via multistep chains of actions enabled by reasoning models.鈥�

This, as speakers and panelists at the NRF conference acknowledged, isn鈥檛 just an evolution of e-commerce; it鈥檚 a rethinking of shopping itself, in which the boundaries between platforms, services, and experiences give way to an integrated, intent-driven flow through highly personalized consumer journeys that deliver a fast, frictionless outcome.

As the McKinsey report noted, the stakes are high. By 2030, the U.S. B2C retail market alone could see up to US$1 trillion in orchestrated revenue from agentic commerce, with global projections reaching as high as $3 trillion to $5 trillion.

This means all the participants in the retail chain, from brands and retailers to logistics and payment service providers, will need to adapt to the new paradigm and successfully navigate the challenges of trust, risk, and innovation.

To help retailers address the immediate challenges posed by the shift to agentic commerce, 麻豆原创 argues that three steps are necessary: first, restructuring web-page product data to be machine-readable; second, adding semantic summaries for LLM reasoning; and third, tagging products by the problems they solve, not just their attributes.

麻豆原创 announced a series of AI-enhanced retail innovations at NRF 2026, including a new storefront model context protocol (MCP) server that enables retailers to make their digital storefronts intelligible to AI and the new AI-native Retail Intelligence solution in 麻豆原创 Business Data Cloud that leverages data from across 麻豆原创 software and third-party systems to help provide accurate demand planning, improved forecast accuracy, and lower inventory costs to drive more seamless omnichannel engagements.

麻豆原创 Customer Experience has also unveiled a recently that can be combined with the聽, creating one conversational AI that can handle the entire journey from product discovery and transaction to post-sales support.

These moves reflect a recognition that that LLMs have become a legitimate shopping channel, and that product discovery is moving from search engines to AI recommendations.

This shift challenges years of SEO and brand building. To stay relevant, 麻豆原创 believes retailers must take an AI-first approach and have strong, connected data that helps agents understand products, predict demand, and respond quickly. Without this strong data foundation, brands will be at risk because if customers get poor recommendations and errors in pricing, trust can disappear fast.

Although some early agentic AI adopters in the retail sector are already seeing the benefits of agentic commerce, many global retailers are still ill-prepared for the holistic transformation they need to succeed in this new retail environment.

As McKinsey noted in a separate , 鈥渨hile most retail merchandising teams have invested in automation tools聽and experimented with AI, 71% of merchants say that AI merchandising tools have had limited to no effect on their business so far.鈥�

鈥淭he challenge,鈥� McKinsey said, 鈥渙ften lies less in the technology than in how it鈥檚 integrated and used. Systems remain fragmented, data is too messy to use to deliver useful recommendations, and adoption is uneven: 61% of respondents say that their organization isn鈥檛 at all or is only slightly prepared to scale AI across merchandising.鈥�

Onstage at NRF, Andre Bechtold, president for 麻豆原创 Industries & Experience, also emphasized that retailers should prepare now for agentic commerce and noted that simply “bolting on” AI tools to existing systems is not enough.

鈥淩etailers are operating in an environment defined by volatility鈥攖ariffs, margin pressure, supply chain disruption, and customers that expect real-time, hyper-personalized experiences everywhere,鈥� Bechtold said during a discussion with Gymshark, the workout apparel retailer. 鈥淎t the same time, boards and investors are asking a tougher question than ever before: what outcomes are we actually getting?鈥�

鈥淭he challenge,鈥� he said, 鈥渋sn鈥檛 a lack of innovation. In fact, most retailers have plenty of tools, pilots, and point solutions. The real issue is that disconnected technology doesn鈥檛 translate into resilient growth. That鈥檚 why the conversation is shifting. It鈥檚 no longer about isolated AI use cases or shiny new features. It鈥檚 about whether AI and data are embedded across the business鈥攃onnecting supply chains, finance, merchandising, and customer engagement鈥攊n ways leaders can trust.鈥�

Echoing the same point, Thomas Saueressig, member of the Executive Board of 麻豆原创 SE, Customer Services & Delivery, commenting in a this week about a PwC survey of global CEOs that found that companies rarely achieve lower costs or higher sales through the use of AI, emphasized that AI only contributes value when consistently embedded in business processes. 聽鈥淎s long as AI runs alongside the core business as an isolated project, the effects remain limited,鈥� he said.

Our vision for agentic commerce is bold. In , we showcase a future where humans and AI agents collaborate to drive intelligent recommendations, proactive operations, efficient business processes, and deeper customer relationships. While this vision points forward, 麻豆原创鈥檚 focus is firmly grounded in helping retailers take practical steps today. This isn鈥檛 about flashy demos of a distant future鈥攊t鈥檚 about building the foundation now for how consumers will buy and retailers will sell in the years ahead.

Unlike traditional AI systems that respond to prompts, agentic systems act on intent. They learn from preferences, make proactive recommendations, and can complete transactions on a shopper鈥檚 behalf. These agents are increasingly becoming the starting point of the buying journey, reshaping how brands compete for visibility, trust, and loyalty.

This evolution introduces both opportunity and risk. As AI agents mediate more interactions between brands and consumers, retailers must rethink how they capture intent, transact with agents, and deliver post-purchase experiences that reinforce trust.

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Discovery is moving from search to assistants

Historically, product discovery revolved around search engines, marketplaces, and brand-owned storefronts. That model is shifting quickly. Answer engines and AI shopping agents are becoming new entry points for commerce鈥攐ften before a shopper ever visits a retailer鈥檚 site.

Like marketplaces before them, AI agents introduce a new layer between brands and customers. The difference is speed and autonomy. Agents don鈥檛 just surface options; they reason, decide, and act.

For retailers, success is no longer about ranking on a page. It鈥檚 about ensuring products are visible, understandable, and trusted by machines that influence purchase decisions on behalf of humans.

At NRF, 麻豆原创 expanded its agentic commerce vision with the announcement of the storefront MCP server for 麻豆原创 Commerce Cloud, planned for Q2 availability. The storefront model context protocol (MCP) server can enable channel-less commerce by allowing businesses to safely and reliably engage with multiple AI agents鈥攚hether embedded in a retailer鈥檚 own experiences or originating from third-party assistants like ChatGPT or Perplexity.

The storefront MCP server helps merchants surface products and can enable buying across channels for both people and machines. It鈥檚 the first of many steps 麻豆原创 is taking to help customers fully participate in agentic commerce by supporting MCP, ACP, UCP, and other emerging agentic protocols.

Product content becomes the currency of visibility

In an agent-driven world, product content is no longer just marketing鈥攊t鈥檚 operational infrastructure. AI agents cannot recommend what they cannot interpret. Every attribute, image, specification, availability signal, and proof point directly impacts whether a product is surfaced, compared, or selected.

This is where generative engine optimization (GEO) is evolving. Optimization must now serve two audiences: humans and machines. Product data must be structured, consistent, and enriched, so AI agents can confidently represent it to shoppers.

The in helps transform how merchants manage product data at scale. It can clean catalogs, enrich attributes, standardize details, fill gaps, and support multilingual content using real-time data. The agent can scale to catalogs with more than 10 million items, helping teams improve content 70% faster, increase data completeness by 5%, and reduce maintenance effort by 63%.

With AI-ready product data as its foundation, retailers can better match shopper intent, optimize merchandising by channel, and improve pricing and delivery decisions with precision.

Payments must evolve for autonomous commerce

As buying journeys fragment across devices, channels, and agents, payments must become more flexible and nearly invisible. Consumers expect to pay how and when they choose, including through agent-initiated transactions.

New payment rails like FedNow, RTP, and stablecoins are enabling faster, lower-cost transactions, while wallets and bank-based payments continue to converge. Networks such as Visa and Mastercard are already preparing for autonomous commerce by allowing consumers to set spending limits and controls for AI agents.

For retailers, the priority is delivering frictionless, secure payment experiences that integrate seamlessly into agent workflows.

The can enable this flexibility through a no-code, low-code approach. Its headless, extensible architecture helps support diverse payment methods, ensure compliance through automatic updates, and integrate natively with 麻豆原创 Commerce Cloud鈥攚orking to give retailers agility without sacrificing control or scalability.

Returns become a strategic intelligence engine

Returns are one of retail鈥檚 biggest challenges. According to IHL Group, global returns have surpassed US$1.9 trillion and are growing faster than sales. What was once a cost center is now a strategic differentiator.

The next phase of returns management is defined by intelligence. AI enables 鈥渒eep, reject, or return鈥� decisioning based on loyalty history, behavioral signals, margin impact, and lifetime value. Returns data becomes a feedback loop that improves forecasting, product quality, and merchandising decisions.

Complete, connected data is essential. 麻豆原创 can deliver this through native integration between 麻豆原创 ERP and 麻豆原创 Commerce Cloud, creating a single source of truth across inventory, costs, and transactions. found that organizations using both platforms achieved up to 80% lower TCO, up to 90% productivity gains, and 105%鈥�245% revenue uplift from hyper-personalized experiences.

can extend this foundation across the full returns journey, helping to orchestrate centralized rules, guided returns, real-time inventory visibility, and faster refunds鈥攖urning returns into a loyalty-building growth lever rather than a revenue drain.

Commerce is detaching from the storefront

As predicted at the end of 2025, AI agents are taking on more shopping tasks, pushing commerce beyond traditional storefronts. A shopper may simply state an intent and let an agent handle research, selection, and checkout.

Discoverability now depends on structured, trustworthy signals鈥攔eviews, ratings, social proof, and consistent data that agents rely on to evaluate quality and brand credibility.

Retailers must move beyond transactional efficiency to deliver connected, personalized experiences across every touchpoint. Loyalty programs must reward engagement, not just purchases. Inventory visibility, accurate delivery promises, and proactive issue resolution become table stakes.

can enable retailers to design adaptive loyalty strategies for this new environment, personalizing rewards and offers based on real-time behavior鈥攚hether purchases happen through traditional channels or AI agents. These insights can then feed transactional agents, helping to improve relevance and outcomes across the journey.

Operational reliability remains critical. 麻豆原创 Order Management Services help unify order, inventory, fulfillment, and POS data, while agentic innovations like the Order Reliability Agent can proactively resolve fulfillment issues before they impact customers.

Trust is the core retail responsibility

As agentic systems influence more of commerce, trust becomes the most valuable asset retailers can protect. Consumers must trust that their data, preferences, and payments are secure and governed responsibly.

Retailers and commerce providers increasingly act as AI trust custodians, balancing intelligence with deterministic constraints and governance. On-site AI can scale associate expertise and personalization while preserving brand integrity and customer confidence.

Commerce is becoming an ecosystem of intelligent interactions鈥攚here discovery, payments, fulfillment, and returns are connected by agents acting on behalf of shoppers and businesses alike.

The winners will be those who align product intelligence, flexible payments, data-driven returns, and trust across every touchpoint. Agentic AI can make commerce more personal, efficient, and scalable鈥攂ut only for those who build the right foundations today.

To learn more about how 麻豆原创 Commerce Cloud is powering AI-driven commerce, visit .

Kollen Glynn is global head of 麻豆原创 Commerce Cloud for 麻豆原创 Customer Experience.

This isn鈥檛 just a consumer trend; it is reshaping engagement models across industries.

The Q4 2025 (麻豆原创 CX) release propels this transformation further with new out-of-the-box agents designed for customer service and the ability to easily build custom agents with Joule Studio. Additionally, AI features like predictive segmentation and AI-assisted reporting expedite planning and decision-making鈥攆oundational catalysts for future-ready businesses.

With WalkMe Premium now available across 麻豆原创 CX applications, teams can upskill and reskill with in-the-moment guidance. And 麻豆原创 Customer Loyalty Management takes new engagement models to the next level, helping businesses strengthen relationships and drive long-term growth.

Here, explore more of the highlights from the Q4 2025 release. And for full sub-solution details, see recaps for , , , , and .

Better customer engagement with out-of-the box agents and custom tools

With 麻豆原创, customer experience applications, data and AI come together as one鈥攑owered by 麻豆原创 Business Technology Platform. Whether it鈥檚 resolving an issue or managing inventory, CX applications connected to 麻豆原创 ERP keep processes running smoothly. AI agents take it further, by reasoning and acting directly in core processes, turning complexity into clarity. One of the most critical areas is in customer support.

• : Deliver instant and accurate self-service by putting knowledge at customers鈥� fingertips. Deflect common inquiries, resolve complex questions with AI, and escalate seamlessly to human agents when needed鈥攔educing contact center load while improving customer satisfaction.
  
  Digital Service Agent can be combined with , creating one conversational AI that handles the entire journey鈥攆rom product discovery and transaction to post-sales support. Customers can ask questions, get answers, and complete purchases in a single frictionless interaction. Together these agents unlock agentic commerce and intelligent service, which strengthens customer relationships and deliver experiences that truly stand out.

• : Create custom, business-ready AI agents for 麻豆原创 Customer Experience Cloud applications鈥攆ast and without complexity. Joule Studio, a part of , gives developers a powerful low-code, no-code environment to create and deploy AI agents and connect them seamlessly to Joule, 麻豆原创 CX apps and third-party systems. These agents can retrieve information, complete tasks, and run autonomous actions grounded in enterprise data from 麻豆原创 CX, 麻豆原创 Knowledge Graph, and non-麻豆原创 systems.
  
  For example, users can build a sales assistant agent that instantly pulls historical purchase records, analyzes buying patterns, and recommends the most relevant products or offers鈥攈elping sales teams increase conversion rates and shorten sales cycles. Learn how to .

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Boost insights and workforce skilling with AI-powered guidance

AI is no longer optional; it鈥檚 the engine behind smarter, faster customer engagement. As digital experiences raise the bar, customers expect speed, personalization, and simplicity in every interaction. Meeting those expectations requires more than automation. It demands AI-driven insights and skills that scale across the organization.

• : 麻豆原创 is embedding AI upskilling into the core of customer experience applications with WalkMe Premium for 麻豆原创 CX solutions. This solution empowers employees to work smarter and learn faster, driving better outcomes from day one. With real-time, role-based guidance and automation across , , , and , teams can unlock the full potential for 麻豆原创 CX solutions without complexity.

• : Easily generate custom reports and comparisons in 麻豆原创 Emarsys, and uncover campaign and customer insights instantly.

• : Enable service agents in 麻豆原创 Service Cloud to quickly understand key consumption trends for a premise. With AI-generated summaries of consumption graphs, agents can immediately identify usage fluctuations, anomalies, and important patterns to support faster resolution for utilities customers.
• : Check the overall health of the sales pipeline in 麻豆原创 Sales Cloud and display opportunities based on quantity and probability score.
• Promotion and account plan configuration: In , customers can configure promotion types and account plan types, defining scope, levels, spend, and baseline management, in order to enable flexible planning and support future indirect promotions.

• Engagement events: In 麻豆原创 Emarsys, ingest inbound events from external data sources to further enhance segmentation and personalization throughout the journey.
• (pilot): Use predictive AI segments in 麻豆原创 Emarsys to reach audiences that are most likely to engage based on a contact鈥檚 behavior, status, or channel preference.

Build lasting connections with 麻豆原创 Customer Loyalty Management

Customer loyalty is more than a metric; it鈥檚 a long-term strategy for growth. As expectations rise, organizations need solutions that create meaningful, lasting relationships. 麻豆原创 Customer Loyalty Management helps businesses deliver personalized experiences, reward trust, and strengthen engagement at every touchpoint, turning everyday interactions into enduring connections.

• : Empowers businesses with AI-driven insights to capture and unify customer data in a dynamic, cloud-based loyalty profile. These profiles provide deep insights into individual motivations, enabling smarter segmentation and highly targeted marketing campaigns. From managing global programs on a unified platform to forming strategic alliances and scaling initiatives for impact, 麻豆原创 helps transform loyalty into a measurable, powerful engine for sustainable engagement and success. 麻豆原创 Customer Loyalty Management has integrations for 麻豆原创 Service Cloud and 麻豆原创 S/HANA Cloud Private Edition to make the transformation faster.

The future of engagement is here, get ready with 麻豆原创

How we engage is changing faster than ever. 麻豆原创鈥檚 Q4 2025 innovations in customer experience anticipate this shift on every level. 麻豆原创 CX is enabling organizations to move beyond reactive strategies and into a world of proactive, personalized experiences.

Businesses that embrace and integrate these new models throughout their enterprise, pairing agentic AI with human intelligence and creativity, will set new standards for customer loyalty and growth.

Learn more about 麻豆原创 CX in Q4 2025

Read the 麻豆原创 Help documentation to get started with these new capabilities.

• 鈥�&苍产蝉辫;
•   
•   

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience and Consumer Industries.

Since the launch, has empowered organizations to streamline operations for increased efficiency, reduced manual workloads, and untangled multi-channel complexity. With this approach, businesses can deliver on customer promises with seamless customer experience. This momentum has also been recognized in the market, as 麻豆原创 Order Management Services was named a Leader in by IHL Group for its robust capabilities and enterprise readiness.

, a leading German home improvement retailer, is already seeing the benefits. With 麻豆原创 Order Management Services, Hornbach connects digital and physical stores with full visibility into day-to-day transactions, providing omnichannel retail experience at scale to its customers.

However, the retail landscape is evolving continuously. While profitable growth is critical to businesses, earning and sustaining customer loyalty now is becoming more important. Ahead of the curve, 麻豆原创 has heavily invested in expanding capabilities in the 麻豆原创 Order Management Services bundle to help retailers deliver on customer promises with intelligence, scalability, and adaptability, leading to boosts in customer loyalty.

At NRF 2026, 麻豆原创 is unveiling new and enhanced capabilities that power retailers to not only operate more efficiently but also achieve loyalty-led growth through every order.

AI in 麻豆原创 Order Management Services

Joule in 麻豆原创 Order Management Services: 麻豆原创鈥檚 AI copilot, Joule, is now available in 麻豆原创 Order Management Services. Access order-related data, analysis, and insights through conversations in natural language and visual display.

Order Reliability Agent: Accelerate operational efficiency with the Order Reliability Agent in 麻豆原创 Order Management Services. Proactively mitigate and resolve any potential issues and gaps, such as stock discrepancies or process bottlenecks, to help ensure every order is fulfilled seamlessly and to boost customer loyalty.

AI-assisted copy generation and translations: Create promotional copy in seconds and translate it into any language with AI assistance, helping to reduce manual workload and accelerate time-to-market.

UI enhancements

Workflow-optimized UI: The enhanced and unified UI in 麻豆原创 Order Management Services can deliver a consistent user experience across order, inventory, and fulfillment operations. Teams can now work faster, reduce training time, and maintain full visibility across every step of the order lifecycle.

Watch the 麻豆原创 Order Management Services  to get a closer look at the AI capabilities in action. Visit the 麻豆原创 booth at NRF 2026, January 11 鈥� 13, to learn more about 麻豆原创 Order Management Services and catch an in-person demo.

Emilie Fournelle is head of Product Management for 麻豆原创 Order Management Services at 麻豆原创.

NEW YORK 鈥� (NYSE: 麻豆原创) today announced a new generation of AI-enhanced retail innovations at NRF 2026: Retail鈥檚 Big Show.

麻豆原创 continues to infuse AI into the DNA of every part of its retail solutions, reinforcing its suite-first strategy and helping retailers operate with greater intelligence, resilience and trust while delivering better experiences for customers everywhere.

鈥淩etailers face a landscape where AI is no longer optional,鈥� said Balaji Balasubramanian, President and Chief Product Officer for Customer Experience and Consumer Industries, 麻豆原创 SE. 鈥溌槎乖� provides one closed-loop, AI-enhanced retail operating system that ties planning, execution and engagement together. We put data and AI at the heart of retail, delivering speed, personalization and growth across every channel and segment.鈥�

AI that turns retail data into actionable intelligence

The Retail Intelligence solution in provides accurate demand and inventory planning, leveraging retailers’ data from across 麻豆原创 software and third-party systems to drive profitable growth through actionable, real-time insights. Purpose-built for retailers and direct-to-consumer businesses, it will be generally available in the first half of 2026.

Harmonizing real-time data from sales, inventory, customers and suppliers, Retail Intelligence uses AI-generated simulations so planners can anticipate outcomes and optimize inventory. This improves forecast accuracy, reduces manual planning effort, lowers inventory costs and raises service levels. All this drives more seamless omnichannel engagements, which strengthen customer loyalty and enable growth without adding complexity for retailers.

鈥淩etailers are seeking built-in, embedded AI solutions to help balance daily operations, future planning and agility to manage a dynamic market,鈥� said Ananda Chakravarty, Vice President of IDC Retail Insights. 鈥淲hat sets 麻豆原创 apart is the holistic nature of its approach, offering an agentic operating system that works in the background, connects data and orchestrates agents. 麻豆原创 makes it an easy lift for retailers to achieve enterprise-wide intelligence, avoiding the complexity of many point solutions.鈥�

AI that streamlines modern retail operations

Retailers must make fast, confident decisions across assortments, pricing and planning. To meet that need, 麻豆原创 announced new AI-assisted assortment management capabilities, allowing planners to create, modify or retire assortments using natural language through the Joule copilot. This reduces the bottleneck on expert users, enabling faster responses to market shifts and freeing time for higher-value merchandising decisions.

麻豆原创 also introduced omnichannel sales promotions in sales orders, integrating the 麻豆原创 Omnichannel Promotion Pricing solution with the 麻豆原创 S/4HANA Cloud Public Edition, retail, fashion and vertical business solution. This enables advanced promotions such as bonus buys to be applied consistently across diverse channels, enabling a single source of truth for pricing and promotions in store and online, so retailers can deliver a consistent experience.

In addition, 麻豆原创 is delivering deeper merchandising, segmentation and manufacturing support in the solution, tailored to fashion wholesalers and manufacturers. These enhancements provide the data and process foundation needed for AI-assisted fashion operations across the business.

AI that drives better customer engagement

As shopping journeys increasingly begin with AI assistants rather than storefronts or search engines, retailers need new ways to be present wherever buying decisions are made. 麻豆原创 helps retailers connect products, pricing, inventory and promotions directly to AI-enabled discovery and shopping experiences, unlocking agentic commerce with its new storefront MCP server, part of the 麻豆原创 Commerce Cloud solution.

Retailers can now make their storefronts intelligible to AI, driving shopping experiences not only on their storefronts but also on platforms such as ChatGPT.聽This creates a truly channel-less commerce experience, one where engagement, discovery and transaction happen more seamlessly across human and AI-assisted touch points.

AI that builds customer loyalty

As customer expectations rise and fulfillment networks grow more complex, retailers need confidence that every order will be delivered as promised, using AI solutions that provide proactive visibility and guidance to help keep operations running smoothly and at scale. And as brand visibility shifts in the age of agentic commerce, reliable and consistent shopping experiences are more important than ever to drive sustained customer loyalty and trust.

麻豆原创 announced Order Reliability Agent as part of the 麻豆原创 Order Management Services bundle, planned for release in the second quarter of 2026. The new agent proactively identifies and resolves potential order issues, helping associates answer common questions about order status, stock availability and fulfillment risks before they impact customers.

By combining agentic autonomy with human oversight where judgment matters, these innovations from 麻豆原创 drive insightful planning and improve operational efficiency, both enhancing the customer experience and driving profitable growth.

Visit the . Get 麻豆原创 news via  and .

Media contact:
Mallory Kuno, +1 (425) 239-9362,听mallory.kuno@sap.com, ET
麻豆原创 麻豆原创 Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.聽 Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 2026 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

Seismic shifts are not new for retailers鈥攂ack in 1999, e-commerce was still an afterthought. By 2000, everything changed as retailers went all-in on digital.

In聽2025,听we are聽living in yet聽another pivotal year.聽This holiday season might feel familiar as you scroll through deals, compare brands, and race to beat shipping deadlines. But beneath the surface, something far more transformative is happening.聽The year 2025 will聽likely be聽the last consumers shop as they do now.听听

Agentic AI is reshaping commerce by making shopping faster, smarter, and effortless. Discovery is moving from people browsing their favorite brands to intelligent orchestration. Instead of opening 10 tabs to hunt for the right deal, shoppers will simply ask: 鈥淔ind me the highest rated black, puffy winter coat, size 10, under $200 that ships in two days.鈥�

The agent will handle the rest鈥攕canning thousands of options, validating reviews, confirming delivery timelines, even factoring in loyalty perks. That future isn鈥檛 tomorrow; it鈥檚 already here, and by next holiday season, most shopping journeys will begin, evolve, or end with AI agents.

While this type of shopping creates convenience for shoppers, it creates a challenge for retailers that have focused on brand campaigns and poured millions of dollars into advertising to be the 鈥渂rand of choice鈥� in the discovery process. Decades of investment into SEO, paid traffic, and brand recognition are losing their edge. While not abandoning these strategies entirely, they must evolve for the AI-first world.

However, there is something that hasn鈥檛 changed over the course of decades: the need to create loyal customers who make repeat purchases and give the greatest share of their wallets. This, too, is more challenging than ever. In fact, 72% of consumers report that this holiday season they will only that consistently meet their needs in the moment.

Creating customer loyalty in the age of agentic commerce means conquering two critical fronts:

• Optimizing for discoverability: Agents will favor retailers that make buying seamless.
• Creating customer loyalty post-purchase: With discovery being augmented by AI agents, humans will now give their ongoing loyalty based on post-purchase experiences. On-time delivery, easy returns, and rewards that feel personal are the new battleground for brand equity.聽 And with agents learning from human behavior, exceeding shopper expectations post-purchase can ultimately impact a brand鈥檚 likelihood of being recommended in the discovery phase.

The question remains: how do we move from esoteric AI conversations to practical strategies?

Discovery and loyalty: How to win in the age of agentic AI

• Make your catalog agent-ready: Treat AI as a new kind of shopper. Ensure product feeds are rich, structured, and machine-readable, complete with attributes, use-case-driven descriptions, real-time pricing, and accurate inventory. Clean, structured product data is now the foundation of intelligent discovery.
• Create solutions, not just SKUs: AI-driven traffic behaves differently. Design bundles, add-ons, and value stacks that solve specific problems and allow agents to match shoppers with outcomes, not just product lists.
• Build trustworthy, accessible information: Operationalize trust by surfacing verified reviews, transparent pricing, sustainability details, and clear return policies. Make this data accessible through well-structured APIs, not scraping, so agents and humans see the same reliable truth.
• Let prediction power personalization: Use unified data and AI to predict what customers want before they act, enabling real-time next-best-actions across email, SMS, push, in-app, and other emerging channels. This predictive intelligence turns fragmented campaigns into that deliver higher engagement and revenue.
• Make loyalty the thread that ties every experience together: Loyalty is no longer a program. It鈥檚 a relationship. Use every interaction to tailor meaningful, emotional moments that adapt, remember, and feel consistent across channels in order to help convert agent-driven traffic. Then, use personalized exclusives and perks to foster high-value relationships with those new customers.
• Deliver on your promises, every time: Eighty-eight percent of customers leave a brand after one bad experience. That鈥檚 why operational reliability is the new loyalty. Bring order, inventory, payments, and fulfillment into alignment, so customers receive what they were promised, when they were promised. Loyalty now begins at checkout.
• Prepare for the new return economy: Agent-driven buying makes it easy for consumers to purchase first and decide later. Set clear limits to protect margins and reduce friction in the returns journey because a seamless return can build more loyalty than the purchase itself.

麻豆原创 is already helping brands prepare for this future with AI-enabled technologies across , , , and .

A brand already building for the future

Global sports brand . Historically reliant on seasonal campaigns, Mizuno wanted a more sustainable way to engage its diverse customer base across 10 product categories and multiple channels. Mizuno unified its customer data and used AI to create personalized journeys, turning one-off interactions into long-term relationships.

The results speak for themselves:

• 52% year-over-year (YoY) increase in active customers
• 62% increase in revenue from premium customers
• 35% increase in customer win-backs
• 33% increase in the number of orders

麻豆原创: A partner built for scale, stability, and growth

As customer behavior evolves and AI reshapes what鈥檚 possible, one thing remains constant: 麻豆原创鈥檚 commitment to helping brands win their biggest commercial moments. This year鈥檚 holiday results make that clearer than ever. We鈥檙e not just helping brands plan for peak season鈥攚e鈥檙e helping them execute it with precision, intelligence, and confidence.

Nearly 20% YoY growth in total messages sent underscores the trust brands place in 麻豆原创 Emarsys to deliver at scale. Mobile and emerging channels surged鈥攊n-app (+61%), SMS (+32%), push (+27%), and inbox (+91%) all saw significant YoY gains鈥攁s brands met customers exactly where they were browsing and buying. Omnichannel maturity accelerated with brands using a richer mix of channels to create connected, high-value experiences across every stage of the shopping journey. And with 100% uptime and flawless reliability, teams executed independently and confidently, even during their highest-volume moments.

Paired with exceptional commerce performance, the story becomes even more compelling: brands used more intelligent engagement to guide shoppers toward higher-value purchases (+18% YoY average order value) and ultimately drove substantial YoY revenue growth (+40% gross merchandise value)鈥攁ll powered by a that delivered uninterrupted performance with 100% uptime through the holiday shopping rush, ensuring we鈥檙e here for our customers when it matters most.

This is what partnership looks like: scale, intelligence, reliability, and results so brands can focus on creating exceptional customer experiences, not managing technology.

Looking ahead

The year 2025 will be remembered as the last holiday season where brand mattered more than the overall experience.

This year, and 48% of shoppers would support brands bringing more AI into their buying experience. This sets the stage for growth in 2026 as AI agents deliver relevance, trust, and immediacy, making shopping simpler, smarter, and more satisfying for people everywhere.

The brands that win won鈥檛 be the ones shouting the loudest. They鈥檒l be the ones using 麻豆原创 to be most discoverable, dependable, and unforgettable.

By anticipating needs and creating better, personalized journeys, AI will enhance every stage of commerce. And 麻豆原创 is here to make that future happen.

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience.

The solution helps businesses worldwide stay ahead of changing customer expectations with a powerful, future-ready platform that delivers unified commerce through connected data, intelligence, and AI innovation.

Organizations across industries use 麻豆原创 Commerce Cloud to unlock sustainable growth through personalized commerce at scale.

麻豆原创 Commerce Cloud is embedding into the tools that employees and customers rely on every day. With AI built into key moments in commerce, the solution and its AI agents help create real business outcomes through faster response times and streamlined touchpoints. Agents like the bring the vision for a connected, intelligent business suite where applications, data, and AI work together in a continuous, virtuous cycle to anticipate needs, act in real time, and elevate experiences.

Another new innovation also helps support profitable growth: 麻豆原创 recently launched the . Natively integrated with the 麻豆原创 ERP application, it makes ordering, invoicing, and promotions more intuitive while giving business buyers a positive digital experience.

, a global leader in wood products and furniture, relies on 麻豆原创 Commerce Cloud as an integral part of managing a complex supply chain. The Chilean forestry company connects customers with on-demand insight into their orders through a self-service portal.

鈥溌槎乖� Commerce Cloud provided us with the tools to create a portal that has exceeded our customers鈥� expectations again and again,鈥� said Diego Tuleski, director of IT at ARAUCO North America Inc.

Other global leaders are realizing measurable impact as well. uses 麻豆原创 Commerce Cloud to streamline complex service orders and improve customer account management. For , 麻豆原创 Commerce Cloud helps digitalize and manage complex order processes, making them intuitive experiences through integration with existing ERP applications. delivers favorable guest experiences across theme parks, hotels, and retail with 麻豆原创 Commerce Cloud, enabling millions of transactions on a single commerce platform integrated with 麻豆原创 Cloud ERP solutions.

To learn more about 麻豆原创鈥檚 position as a Leader and see an in-depth analysis of the digital commerce landscape, .

Kollen Glynn is global head of 麻豆原创 Commerce Cloud, 麻豆原创 Customer Experience.

_{Gartner, Magic Quadrant for Digital Commerce, Aditya Vasudevan, Ant Duffin, Mike Lowndes, Sandy Shen, Jason Daigler, Penny Gillespie, 3 November, 2025.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.}

_{麻豆原创 was recognized as 麻豆原创 Hybris in 2014, 2016 and 2017.}

Before diving into the heart of the keynote, Steinhaeuser invited 麻豆原创 solution area CMOs to deliver lightning-fast recaps of news from the various 麻豆原创 Connect event tracks. In just under two minutes each, they covered finance, procurement, supply chain, HR, and customer experience. From autonomous accounting and next-gen procurement to AI-driven talent acquisition and smarter customer loyalty, the message was clear: across every business function.

The real challenge: connecting priorities

As Steinhaeuser pointed out, 鈥淭he reality is each business area has its own unique priorities and, of course, all-important urgent matters.鈥� The real challenge is not just launching new features; it鈥檚 aligning processes, data, and teams to conquer uncertainty and achieve true customer focus. 鈥淪imply putting an [AI] agent on top of a broken process will solve nothing,鈥� he said.

The flywheel: AI, data, and apps in motion at 麻豆原创

So, how does it all work together? Enter the 鈥渇lywheel鈥� model: the dynamic cycle of AI, data, and applications that drives synergy across the enterprise. This is not just a theoretical approach. Steinhaeuser showed how 鈥溌槎乖� runs 麻豆原创鈥� using the flywheel model.

First, he said, 麻豆原创 uses 鈥渞ole-based AI assistants, powered by specialized agents, [to] support team members across all areas of 麻豆原创.鈥�

Next comes data. Earlier this year, 麻豆原创 became 鈥渃ustomer zero鈥� for (麻豆原创 BDC), connecting all enterprise data in a single layer to generate faster and better insights across financial, workforce, and sales planning. 鈥淲e’re excited to go live with the first set of intelligent apps, starting with People Intelligence,鈥� he added.

Finally, the app layer: 麻豆原创 has moved from 麻豆原创 ERP Central Component (麻豆原创 ECC) to and , through RISE with 麻豆原创. 鈥淭he 麻豆原创 Business Suite is where data is created and where AI delivers impact,鈥� Steinhaeuser said.

But processes continuously evolve with AI, he said, noting that business transformation management, powered by solutions like and , helps 麻豆原创 and its customers continually improve processes and architecture, with AI embedded everywhere. The company also uses to ensure employees stay informed and engaged at every step.

鈥淒riving 麻豆原创’s own transformation, I understand the challenges you face,鈥� Steinhaeuser said. 鈥淚 am convinced leveraging the flywheel of AI, data, and apps across the entire 麻豆原创 Business Suite is how we win together.鈥�

Embedded AI: tangible value, secure, and seamless

Brenda Bown, chief marketing officer of Business AI at 麻豆原创, took the stage to highlight how business AI is showing up in day-to-day work. 鈥淚’ve heard three consistent themes in conversations [with customers]: first, you want AI that can provide tangible value; second, that is secure and properly governed; and third, that works seamlessly across your teams and business. We’re here to deliver just that,鈥� she said.

Joule is now embedded in use cases in trusted 麻豆原创 applications and is making work faster and easier across the enterprise. 鈥淏y the end of this year, we will have more than 400 of these AI use cases,鈥� Bown said. Joule Agents automate tasks across departments, and the new agent builder in (generally available in December) helps customers extend, build, or customize their own agents. 麻豆原创 LeanIX AI Agent Hub and agent mining capabilities in 麻豆原创 Signavio provide governance and transparency for AI agents.

Bown noted that customers like Matur Fompack are using Joule in 麻豆原创 SuccessFactors to hire faster and improve career development. 鈥淭he results are phenomenal: a 48 percent reduction in HR process execution time and 40 percent faster employee development and career planning, and, most importantly, a better employee and candidate experience,鈥� she said.

For processes that require multi-step workflows and nuanced decisions, 麻豆原创 introduced a new generation of role-based AI assistants. 鈥淭hey know your role in the organization, because they are role and context aware,鈥� Bown said. These assistants tap into the right agents for the job, removing any guesswork and helping humans unlock new levels of insight and productivity.

She also showcased how agents collaborate across departments, automate workflows, and even extend 麻豆原创鈥檚 business logic to autonomous devices like robots. Early pilots with partners like NEURA Robotics are already showing Joule Agents planning and executing real work in the real world.

Data and intelligent applications: unified and actionable

Data is only valuable when it is actionable. Irfan Khan, president and chief product officer for 麻豆原创 Data and Analytics, highlighted 麻豆原创 BDC, which unifies enterprise data and powers intelligent applications. 鈥溌槎乖� BDC offers the most powerful foundation for connecting your existing data, building next-generation applications, and the ability to foster and deploy reliable AI,鈥� he said. And the new 麻豆原创 Business Data Cloud Connect solution enables secure, bi-directional data sharing with partners like Databricks and Google Cloud.

Intelligent applications bridge the gap between people and AI. They support smarter decisions and collaboration. 鈥淭hese applications learn from your data and include business simulations to support every business leader with smarter decisions,鈥� Khan explained. 鈥淚f we don’t have a reliable data foundation built around trust, having reliable and resilient data, it becomes very debatable whether or not AI will succeed.鈥�

From insight to action: transformation in practice

How do organizations turn strategy into action? Michael Ameling, president of 麻豆原创 Business Technology Platform (麻豆原创 BTP), demonstrated how 麻豆原创 Business Suite helps drive innovation by uniting core applications, data, and AI, all powered by 麻豆原创 BTP and Business Transformation Management solutions. 鈥淟et’s say you want to understand and improve a business process,鈥� he said. 鈥溌槎乖� Signavio lets you dive deep and understand every detail, and can suggest concrete actions. Then, use those insights to improve the process in 麻豆原创 Build by automating processes and building your own agents.鈥�

He demonstrated how 麻豆原创 BTP and the Business Transformation Management portfolio can help organizations connect systems, gain visibility, and automate processes. Tools including 麻豆原创 Signavio, 麻豆原创 Build, and 麻豆原创 Integration Suite are helping customers like Blue Diamond Growers streamline operations and accelerate transformation.

Services and support: accelerating innovation and realizing value

麻豆原创鈥檚 Anja Schneider, SVP and global head of Premium Engagement and Advisory, wrapped up this segment of the keynote by focusing on how the company鈥檚 services and support teams help customers realize the full value of their 麻豆原创 investments.

鈥淲e鈥檙e with you every step, like a personal trainer,鈥� she said, highlighting how 麻豆原创鈥檚 suite methodology, integrated tools like WalkMe and 麻豆原创 Cloud ALM, and expert guidance help customers realize the full value of their 麻豆原创 investments. She pointed to IBM鈥檚 transformation project as proof: working with 麻豆原创 MaxAttention teams and a clean core approach, upgrades went smoothly with low incidents for more than 150,000 users across 175 geographies.

Customer perspective: Southern California Edison鈥檚 journey

Real-world impact matters. Southern California Edison (SCE) SVP and CIO Todd Inlander shared how the utility company鈥檚 transformation journey with 麻豆原创 is helping modernize its foundational systems and optimize back-office processes. Facing unprecedented demand and environmental challenges, the company is leveraging 麻豆原创 solutions, including 麻豆原创 Business AI capabilities, to transform its operations.

鈥淲e need to adhere to our mission: to deploy safe, reliable, affordable power,鈥� he said. 鈥淲e can’t do that by doing things the way we’ve always done. We have to incorporate 麻豆原创. We’re using it to transform the way we work in our environment. We need to leverage AI because we don’t have enough humans to do all the work. We have to scale.鈥�

As SCE deploys 麻豆原创 Business Suite over the next year, it鈥檚 focusing on keeping a clean core and reducing customizations. 鈥淲hen we implemented ECC 15 years ago, about 66 percent of our enhancements were never used. We’re learning from that experience,鈥� Inlander said. He went on to note that SCE will use the 麻豆原创 deployment time to continue to transform its back-office operations. 鈥淲e’ll be integrating Joule and other AI solutions because doing things the way we’ve always done them and expecting a different outcome is the definition of insanity.鈥�

Steinhaeuser closed the keynote with a look to the future: 鈥淲e鈥檝e made great progress across all lines of business to deliver a unique experience for you鈥攚ith AI becoming your personal assistant, powered by data that defies boundaries and applications that take insight to action. The cross-capabilities you just saw now make the flywheel spin.鈥�

The future is here, and is powered by the synergy of AI, data, and applications. Every business can turn innovation into impact.

New research shows how business AI delivers ROI

To better understand the opportunity to produce returns on investment from AI, 麻豆原创 commissioned that was shared at 麻豆原创 Connect. In partnership with Oxford Economics, we surveyed 1,600 executives in medium and large enterprises across eight countries.

We found that today, on average, organizations are benefiting from a 16 percent return on AI investments鈥攁 number they expect to nearly double within two years. In addition to impressive financial returns:

• 94% of business leaders say AI is improving innovation within their organizations
• 87% say AI is improving customer engagement
• 78% believe AI agents have the potential to transform their business operations

New deep research and AI assistants in Joule expand what is possible

These innovations were engineered based on what our customers tell us they need: to act quickly, simplify complexity, and unlock better, data-driven decisions across the lines of business and processes that matter. But most of all, our customers need AI that drives significant, measurable business outcomes.

To help every organization accelerate returns on investment from AI, at 麻豆原创 Connect we announced powerful new capabilities for , which makes business data and the entire 麻豆原创 Business Suite immediately accessible through the power of a simple conversation. And because Joule is grounded in your company鈥檚 data, it understands context and delivers insights that are specific, actionable, and relevant to your business.

Deep research in Joule, announced at 麻豆原创 Connect, is a new capability expands what people can do within the Joule interface. It goes beyond quick answers to deliver strategic analysis, reporting, and synthesis in a single, connected experience. It brings together internal 麻豆原创 data and external intelligence so people can ask complex questions and receive comprehensive research and recommendations鈥攚ithout ever leaving Joule. The deep research capability in Joule will be available in beta this December.

We also unveiled the new concept of role-based AI assistants in Joule, built to partner with people in their specific roles. These assistants connect to the right Joule Agents for the job, removing guesswork so teams can unlock new levels of productivity and insight. Whether it鈥檚 a finance leader forecasting working capital, a recruiter evaluating headcount needs, or a planner adjusting inventory, AI assistants surface the right intelligence, at the right time, in the right context. In the background, Joule Agents get work done for you.

These innovations mark the next chapter in how people interact with enterprise systems, helping every role across an organization seamlessly move from inquiry to insight to action.

New Joule Agents autonomously get work done

To help enterprises further accelerate business results, we introduced 14 new Joule Agents at 麻豆原创 Connect. They help people coordinate, decide, and execute tasks with greater precision. Joule Agents are in finance, HR, procurement, and supply chain, in a way that only 麻豆原创鈥攚ith our deep expertise in these functions鈥攃an deliver.

For example, rather than navigating multiple systems or running countless manual checks to release an order, a production manager鈥攁 key role in the supply chain function鈥攚ill be able to turn to our Production Planning and Operations Agent, planned for general availability in the Q1 2026. They can simply ask Joule to do it, safely and in real time. The agent will validate and release orders when conditions are met, accelerating production start times and shortening order-to-delivery cycles.

And starting December 2025, with the general availability of , now in beta release, customers will be able to create and deploy custom Joule skills and Joule Agents tailored to their unique business needs. Agent builder in Joule Studio is your command center for designing, building, and deploying enterprise-ready custom Joule Agents using the same powerful 麻豆原创 technologies鈥攊ncluding 麻豆原创 Knowledge Graph for deep business context, 麻豆原创 Business Data Cloud for comprehensive data access across 麻豆原创 and non-麻豆原创 sources, and 麻豆原创’s central identity and authorization services to ensure responsible agent behavior. These capabilities empower every enterprise to extend, customize, and personalize 麻豆原创 Business AI solutions.

New embedded intelligence across 麻豆原创 applications

To help our customers move faster and make better decisions where work happens, we continue to bring intelligence directly into the applications they rely on every day. These embedded capabilities extend the same AI-driven guidance that powers Joule Agents into core 麻豆原创 solutions, enhancing user workflows with context, clarity, and automation. We will have more than 400 of these AI use cases by the end of the year.

For example, in , starting in February 2026, AI will orchestrate personalized interactions across HR, marketing, and service, bringing harmonized data, relevant context, and better business outcomes into every engagement. In the solution, planned for general release in the first half of 2026, AI will predict shortfalls and fulfillment risks, helping planners simulate and respond with speed and precision.

Additionally, the rebuilt 麻豆原创 Ariba source-to-pay suite, arriving in February 2026, brings a modern, cloud-native experience to every stage of procurement. Embedded AI guides people with intelligent recommendations, accelerates contract reviews, and surfaces supplier insights in real time. By simplifying sourcing decisions and improving compliance, it helps procurement teams strengthen supplier relationships and capture more value, faster.

Governing AI with visibility and control

As our customers continue to adopt these AI innovations embedded across their functions, we know they need transparency into how it operates, what it influences, and the value it creates. That is why we provide tools to give them the visibility they need to deploy AI with confidence and scale it responsibly.

麻豆原创 LeanIX AI Agent Hub helps CIOs and business leaders see their entire AI agents landscape at a glance. From one dashboard, they can understand where agents are deployed, what processes they touch, and how agents are performing. This allows teams to evaluate effectiveness, identify redundancies, and manage AI like any other enterprise asset: aligned to outcomes, governed by policy, and continuously optimized.

Complementing that, agent mining in gives organizations a powerful way to analyze how AI contributes to process performance. It reveals how AI agents decide and act, flags bottlenecks and non-compliance, and uncovers where automation adds value and how to fine-tune it for efficiency and impact. Together, these tools bring clarity to what has often been a black box: transforming governance from reactive oversight into proactive optimization.

What鈥檚 next for business AI

At 麻豆原创 Connect, we also shared a view into what鈥檚 coming and how our innovations will continue to redefine enterprise productivity. For example, we鈥檙e developing an outcome-driven user interface that adapts to context in real time. Instead of navigating menus or searching for data, people will simply express what they want to achieve, and the system will guide them through the right actions, insights, and tools.

We鈥檙e also extending Joule Agents beyond software into the physical world鈥攃onnecting your company’s business intelligence to robotics and industrial systems. This opens a new frontier for automation, combining state of the art electronics that utilize physical AI tools, such as computer vision and collision detection, with AI agents capable of reasoning through complex goals and planning multi-step workflows. this November to learn more.

Ready to start your AI journey?

We know AI is top of mind for most business leaders today. In fact, another finding from the research we commissioned with Oxford Economics is that 41 percent of tasks in global businesses will be supported by AI within two years鈥攗p from 25 percent today.

As you continue to explore what is possible with business AI, we鈥檒l keep innovating to deliver systems that are intelligent by design, trusted in operation, and, most important, measurable in their impact.

For us, it鈥檚 all about what you hope to achieve. We鈥檙e proud to partner with you on your AI journey. If you鈥檙e ready to take the next step, here are three things you can do right now:

• Learn how to bring the potential of AI into your organization by signing up for our .
• In our , get inspired about what鈥檚 possible by exploring how leading companies are transforming with AI.
• Watch 麻豆原创 Connect virtual sessions, , to see our latest innovations in action.

There鈥檚 more to come. Join us at on November 4 for the next wave of AI innovations that will transform the enterprise.

Brenda Bown is chief marketing officer for 麻豆原创 Business AI.

Against the backdrop of the event theme鈥�”Connect Everything, Achieve Anything: Agents, Data, and the Business Suite鈥濃�攖hey set out 麻豆原创鈥檚 vision for how 麻豆原创 Business Suite, which combines AI, data, and applications, can transform enterprises and deliver unprecedented business value to customers despite global macroeconomic uncertainties. 

Unique times

鈥淲e are living in very unique times,鈥� Alam said at the start of the keynote. 鈥淯nique in terms of the unpredictability we face from a geopolitical and macroeconomic perspective,鈥痑nd also unique in terms of the advancement in AI and the potential that carries for all of us.鈥�  

He added, 鈥淓ven the most significant challenges can be responded to, navigated, and鈥攚hen approached the right way鈥攖urned into opportunities. And that鈥檚 exactly where 麻豆原创 comes in. Because the best way to face uncertainty is with confidence that you can see what鈥檚 happening across your business and your network.鈥� 

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The CFO perspective 

His comments were echoed by CFO and Executive Board Member Dominik Asam in an onstage discussion with economist and Berkeley professor Ulrike Malmendier, during which they likened the role of the CFO in navigating today鈥檚 business uncertainties to that of co-piloting a modern jet. 

鈥淎I is the next supercycle and has what it takes to create an effective cockpit for the CFO, including recommendations about real actionable options all the way to autopilot for less critical tasks,鈥� Asam said. He also warned that standing on the sidelines of technological progress is 鈥渁 sure recipe for falling behind in competition.鈥�  

鈥淎s in prior tech supercycles, the entire competitive playing field is being completely reshuffled,鈥� he said.

New products

Building on this theme, Alam noted that while uncertainty is real and isn鈥檛 going away, it can be successfully navigated and turned into opportunities. To help customers achieve this, he announced several new and enhanced 麻豆原创 products. 

Among them, 麻豆原创 Supply Chain Orchestration is an AI-native application that uses a network knowledge graph to analyze real-time signals across a company鈥檚 multi-tier supply chain to detect risks and issues, such as extreme weather or tariffs. It then helps customers minimize disruptions by assessing the impact of these risks and suggesting alternatives to help minimize disruptions.   鈥淭hink of it like a GPS in your car which selects an alternative route to avoid traffic or tolls,鈥� Alam explained. In addition, he announced a major update to the 麻豆原创 Ariba solutions for source-to-pay suite, positioning 麻豆原创 Ariba as the most modern platform in the industry and the only truly AI-native source-to-pay solution鈥攁ll built on 麻豆原创 Business Technology Platform.

The human-AI partnership opportunity 

Turning to uncertainties over the future of work itself, 麻豆原创 Chief People Officer and Executive Board Member Gina Vargiu-Breuer, who is leading 麻豆原创鈥檚 own workforce transformation, was joined on stage by Ian Beacraft, founder and chief futurist of Signal and Cipher. 

鈥淎t 麻豆原创, we know firsthand that AI is everywhere, shattering norms and transforming the workforce,鈥� Vargiu-Breuer said. 鈥淎nd we as 麻豆原创 are boldly steering this shift, as requirements for our workforce are simply changing really fast.鈥�  

Vargiu-Breuer emphasized that a successful business AI strategy also depends on leveraging AI alongside human expertise and fostering what she described as 鈥渁 collaborative human + AI approach, rather than just automation.鈥�  鈥淏y integrating AI’s capabilities with human creativity, empathy, and judgment, we move beyond simple automation into real human-AI power couples,鈥� she said. 鈥淯ltimately, the future will favor those who embrace orchestration, delegation, and creative problem-solving.鈥�

Role-based AI assistants

Echoing this human-centric approach, Alam noted, 鈥淓veryone is talking about agents鈥攂illions of agents鈥攁nd agents taking over everything. We want to talk about people, the roles they play, and the tried-and-tested organizational constructs in place today that are running complex businesses across industries.鈥� 

Reflecting this, he said 麻豆原创 is making Joule deeply aware of the workstyle of the person it partners with, their role, and the business process context in which they operate. 鈥淭oday, we are introducing AI assistants, including a receivables assistant for your accounts receivable colleagues, a controlling assistant for your controlling colleagues, a demand Planning assistant for your demand planning colleagues, and an AI assistant for every role.鈥�   Each assistant has agents and AI tools at their disposal to help make the person it partners with smarter and more efficient, Alam explained.

Taking the receivables assistant as an example, he said it can handle collections and dispute resolution today and will soon also be able to help with fraud detection, invoice processing, and payment scheduling. 鈥淥ver time, we will continue to make this assistant even smarter by adding more agents and capabilities鈥攁ll designed to make the person in this role more effective.鈥�

Deep research and new intelligent applications

鈥淲hile efficiency and automation carry potential for great value for the organization, AI鈥檚 greatest strength is in unlocking insights and recommendations based on its ability to do deep research across vast amounts of internal and external data, which is hard for people to do,鈥� said Alam. To address this challenge, 麻豆原创 is introducing deep research in Joule, a capability that can research and analyze complex problems and deliver findings quickly and efficiently. 

Following additional announcements, including an expanded set of 麻豆原创 Business Data Cloud Intelligent Applications and an enterprise wide, multi-stakeholder engagement orchestration solution in 麻豆原创 Engagement Cloud, Alam closed out the keynote by reminding his audience: 鈥淭o create exponential value and to reach the global maxima for your enterprise, the whole matters.  And that鈥檚 what we are focused on: providing you with best-in-class applications, seamlessly and natively integrated across the breadth of finance, spend, supply chain, HCM, and customer experience.鈥� 

麻豆原创 Business Suite delivers unprecedented value

The unmatched value of 麻豆原创 Business Suite is that it brings together the power of best-in-class applications with a semantically rich harmonized data layer to power high-value AI in a singular seamless experience. It helps you manage uncertainty, evolve your workforce, and break down silos to create amazing customer value.

麻豆原创鈥檚 latest customer experience solutions are built to deliver on these expectations, empowering organizations to earn loyalty, drive growth, and create seamless, connected experiences.

In today鈥檚 market, loyalty and retention are the twin engines of repeatable business, the lifeblood of every organization. Earning and keeping customer trust has always been hard-won, but the bar is higher than ever. Recent findings from the show a five-point drop in 鈥渢rue loyalty,鈥� customers who return without incentives. Only 35 percent of B2B customers reach strategic loyalty, defined as repeat purchases and long-term engagement. And nearly one-third of customers are lost to fragmented experiences. Brands now face a new reality: building lasting loyalty requires understanding customers and delivering consistent, connected experiences across every touchpoint.

Meeting the loyalty challenge: 麻豆原创 Engagement Cloud and 麻豆原创 Customer Loyalty Management

To help customers meet this challenge, 麻豆原创 has created two powerful solutions: and .

Yesterday at 麻豆原创 Connect 2025, 麻豆原创 Executive Board Member Muhammad Alam shared the vision for 麻豆原创 Engagement Cloud. Powered by 麻豆原创 Business Data Cloud, it transforms fragmented interactions into AI-driven journeys across marketing, commerce, sales, and service鈥攕trengthening loyalty, deepening relationships, and driving business growth. By connecting every customer touchpoint to real operational data鈥攆rom logistics and finance to supply chain鈥攂rands can deliver accurate delivery estimates, relevant offers, and timely service that reflects actual inventory and fulfillment capacity.

With Joule and embedded AI, 麻豆原创 Engagement Cloud accelerates campaign execution, automates decisions, and scales personalization鈥攅nsuring every interaction is consistent, connected, and meaningful. This comes at a critical time, as according to the 麻豆原创 Emarsys Customer Loyalty Index, only 35 percent of B2B customers achieve strategic loyalty.聽Replacing disconnected systems and outdated engagement models, 麻豆原创 Engagement Cloud makes engagement a strategic advantage, uniting data and AI to deliver smarter experiences across the 麻豆原创 ecosystem. Beta begins November 2025, with general availability in Q1 2026.

麻豆原创 Customer Loyalty Management empowers teams to deliver personalized experiences at scale by giving every customer a single loyalty profile, no matter the brand, region, or partner. With loyalty data unified and natively integrated into 麻豆原创 Private Cloud ERP and 麻豆原创 Business Suite, teams can instantly monitor promotions, track reward usage, and understand financial impact in real time. This actionable insight feeds directly into planning, forecasting, and supply chain decisions, enabling businesses to adapt quickly and serve customers better.

Loyalty isn鈥檛 a separate marketing project, it鈥檚 woven into daily business operations. By centralizing loyalty data, 麻豆原创 Customer Loyalty Management helps organizations understand each customer deeply and deliver consistent, connected experiences across every touchpoint.

The solution will be available Q4 2025.

AI and intelligence: the next imperative

At 麻豆原创 Connect, we introduced how Joule, 麻豆原创鈥檚 AI copilot, is transforming customer experience by embedding intelligence directly into 麻豆原创 Business Suite. Joule is not another layer, it鈥檚 built into the foundation, enabling smarter decisions and faster execution across every customer moment.

AI assistants in Joule bring role-based intelligence to customer-facing teams across service, sales, marketing, and commerce. Each assistant is tailored to the user鈥檚 role and business context, coordinating a network of AI assistants within Joule to automate tasks like resolving cases, chasing invoices, optimizing catalogs, and surfacing insights. This orchestration enables teams to focus on driving outcomes rather than managing operations.

For instance, Digital Service Agent delivers fast, multilingual support by reasoning over customer context and company knowledge. It provides accurate answers, escalates when needed, and continuously improves, reducing manual workload and enhancing customer satisfaction. This is available now.

Deep research in Joule

With deep research in Joule, account planning moves beyond quick answers, delivering deep, strategic research and analysis in a single, connected experience. By tapping into 麻豆原创 data, external intelligence, and trusted resources, users get richer insights for any business need.

Sales leaders and chief revenue officers can use the new account planning that leverages deep research in Joule to compress weeks of manual work into days. It synthesizes customer history, identifies key drivers, and drafts account plans, giving sales teams a complete, real-time view of every relationship.

Deep research in Joule will be available in beta December 2025.

Intelligent applications for customer experience

麻豆原创 Business AI also powers that help businesses turn data into action:

• Revenue Intelligence brings together data from CRM, commerce, and ERP to surface pipeline risks, customer health, and sales performance. Sales leaders and chief revenue officers gain a unified, real-time view to strengthen pipelines, improve win rates, and accelerate profitable growth.
• Consumer Products Intelligence enables manufacturers and consumer packaged goods companies to optimize trade promotions and customer-facing offers. Integrated with and , it uses real-time data from sales, supply chain, and production to analyze margins, monitor performance, and support financial planning, ensuring CX strategies are aligned with operational realities.

These innovations are tightly integrated with 麻豆原创 Business Suite, ensuring every CX insight is grounded in real-time, harmonized data. They are currently in restricted private preview and expected to be generally available in H1 2026.

Adoption that drives value

Building on the Customer Loyalty Index findings about the importance of connected experiences, seamless, guided adoption is essential to delivering value. That is why is now embedded across all 麻豆原创 Customer Experience solutions.

WalkMe is a digital adoption platform that provides real-time, role-based guidance 鈥� right inside 麻豆原创 interfaces. No IT tickets required. Teams get help in the flow of work, with step-by-step instructions that minimize onboarding time and reduce errors. Leaders gain instant visibility into where users struggle, so they can address friction and accelerate adoption.

The path forward

Loyalty is evolving, and so are we. Our priority is to help brands earn trust and adapt quickly.

The 麻豆原创 Customer Experience innovations introduced at 麻豆原创 Connect are designed for this challenge. They connect engagement with execution through solutions like 麻豆原创 Engagement Cloud, Revenue Intelligence, and 麻豆原创 Customer Loyalty Management; turn intelligence into action with embedded AI and automation; and give teams unified, real-time data to deliver measurable results and stay ahead in a rapidly changing market.

See how your business measures up in the and the . .

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience.

麻豆原创 reimagines enterprise AI with role-based assistants in
Joule that coordinate agents across lines of business

LAS VEGAS 鈥� At its inaugural 麻豆原创 Connect event, (NYSE: 麻豆原创) showcases how the integration of AI, data and applications creates unparalleled business value.

These breakthroughs 鈥� including a new network of role-based assistants in Joule that partner with humans to elevate performance, an expanding data ecosystem that drives deeper insights and supply chain software that anticipates disruptions 鈥� once again revolutionize how business gets done.聽

“To thrive when volatility is the new normal, businesses need more than a patchwork of disparate best-of-breed applications,” said Muhammad Alam, member of the Executive Board of 麻豆原创 SE, 麻豆原创 Product & Engineering. “Our announcements today demonstrate the power of 麻豆原创 Business Suite, where AI, data and applications come together in an experience to propel smarter decisions, faster execution and scalable transformation.”

AI that Partners with People

麻豆原创 unveils Joule鈥檚 next stage as the AI force at the center of 麻豆原创 Business Suite鈥檚 value creation. Drawing on the applications and data from across 麻豆原创 Business Suite, 麻豆原创 is introducing a new generation of role-aware assistants in Joule. Each assistant is designed to partner with a human being in their specific business role. Assistants in Joule tap into the right agents for the job, configuring, orchestrating and managing them so humans can focus on unlocking new levels of insight and productivity.

Supporting the assistants in Joule is a , designed to help execute complex workflows within a specific function. For instance, a People Manager Assistant coordinates a team of specialized agents — including the new People Intelligence Agent, which helps spot and resolve issues like compensation anomalies — to support managers as they drive performance. A new Financial Planning Assistant will be aided by a group of expert agents — including the new Cash Management Agent, which optimizes cash flow and improves interest yields — to help finance professionals drive efficiencies. This new roster of role-aware AI assistants not only partner with people to elevate performance in their lines of business but also work together across business functions to solve complex enterprise-wide problems.

Data that Defies Boundaries

Data fuels AI鈥檚 transformative power but it鈥檚 often siloed in different systems. At 麻豆原创 Connect, we are removing those barriers with 麻豆原创 Business Data Cloud Connect. 麻豆原创 BDC Connect securely links 麻豆原创 BDC with partner platforms to enable a bidirectional flow of business-ready data products across organizational and technological boundaries.

With zero-copy sharing, data stays securely in 麻豆原创 systems yet remains instantly accessible in customers鈥� existing data platforms, preserving business context without costly copies. The result: fewer silos, simpler pipelines, no duplication — just trusted data products where and when they鈥檙e needed.

麻豆原创 also announced that Databricks and Google Cloud are the first partners enabled for 麻豆原创 BDC Connect, with more to follow. As announced in February 2025, 麻豆原创 Databricks remains a data service within 麻豆原创 Business Data Cloud, and 麻豆原创 BDC Connect extends its benefits across an open data ecosystem. These partnerships give customers faster access to data products for analytics and AI, helping teams move from raw data to real-time business outcomes with greater speed and simplicity.

Applications that Turn Data into Action

At the heart of 麻豆原创鈥檚 unique value proposition are enterprise applications where data is created and AI-driven insights are experienced. 麻豆原创 Supply Chain Orchestration is a new AI-native solution that combines the power of Joule with a live knowledge graph to detect real-time risks several suppliers deep and orchestrate a coordinated response, helping customers cut costs and keep supply chains moving. 麻豆原创 Engagement Cloud, a new customer experience solution, uses business-critical context to personalize interactions across customers, suppliers and other stakeholders. And our next-generation 麻豆原创 Ariba procurement suite stands out as an AI-native solution, bringing intelligence to every stage of spend management, from sourcing through supplier engagement.

Altogether, these 麻豆原创 Business Suite innovations mark the beginning of a new era powered by self-reinforcing AI, data and applications that drive intelligence, speed and resilience.

Visit the . Get 麻豆原创 news via  and .

About 麻豆原创

As a global leader in enterprise applications and business AI, 麻豆原创 (NYSE:麻豆原创) stands at the nexus of business and technology. For over 50 years, organizations have trusted 麻豆原创 to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

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This weekend, the golf drama will unfold at the storied Bethpage Black Course in New York, as rivalry and camaraderie collide. For the first time, 麻豆原创 will be at the heart of the action as a Worldwide Partner of the 2025 and 2027 Ryder Cup.

Transforming the Ryder Cup fan experience

Since its inception in 1927, the Ryder Cup has united millions of fans around unforgettable moments. Yet behind the emotion and spectacle lies immense complexity. Two distinct organizations, the PGA of America and Ryder Cup Europe, must come together every two years to deliver a seamless tournament experience.

Going into the 2025 event, the Ryder Cup turned to 麻豆原创 for help in transforming what it means to engage fans across the two organizations. With a goal of moving beyond a 鈥渙ne-day鈥� experience to building an 鈥渆veryday鈥� connection, the Ryder Cup wanted to ensure every fan — whether onsite or halfway across the world — feels immersed in the tournament, experiencing the excitement, emotion, and strategy as if they were on the course.

This partnership will allow the Ryder Cup to benefit from using 麻豆原创 technologies to further enhance the experience for fans. 麻豆原创 Customer Data Platform will unify fan data from multiple sources, creating a single, comprehensive profile for each fan. 麻豆原创 Emarsys will then use that data to deliver personalized content across marketing channels. 麻豆原创 Datasphere will harmonize customer and business data and help identify insightful correlations, making it ready for visualization in 麻豆原创 Analytics Cloud, where insights can be turned into action. 麻豆原创 Datasphere and 麻豆原创 Analytics Cloud are part of 麻豆原创 Business Data Cloud.

Together, these solutions will help the Ryder Cup gain a deeper understanding of audience behavior, drive engagement, and deliver personalized experiences at scale, while paving the way for future AI-driven innovation and a globally connected fan journey. Beyond tournament week, this 360-degree view of each fan will provide insights that benefit both organizations year-round, improving planning, marketing, and engagement that can be scaled across other professional tournaments.

Shared values in action

The Ryder Cup is more than a sporting event. It is a showcase of teamwork, resilience, and strategy — qualities that are equally essential in business. At its core, every Ryder Cup moment is defined by a challenge that demands a solution, whether it鈥檚 a player navigating tough conditions, making a critical decision under pressure, or leading a team to victory.

Through this partnership, 麻豆原创 highlights the performance and collaboration that drive success, inspiring organizations and individuals to bring out their best on the course and in business.

Looking ahead

As anticipation builds for Bethpage Black this weekend, fans will see and feel 麻豆原创鈥檚 presence throughout the tournament, from on-course signage to coverage on TV, online, and social channels.

Beyond the event, 麻豆原创 and the Ryder Cup are laying the foundation for a new era of fan engagement, connecting millions of fans around the world and helping to create moments that will be remembered long after the final putt.

These moments are the building blocks of delivering seamless and memorable experiences — and lasting loyalty.

At 麻豆原创, we believe every touchpoint is more than a chance to meet a need. It is an opportunity to deepen trust, demonstrate value, and strengthen the relationship between customer and brand. That belief is at the heart of the 麻豆原创 Customer Experience (麻豆原创 CX) portfolio — now infused with the power of AI.

Our Q3 2025 release reflects this vision. Intelligence is embedded across the entire customer journey. Generative AI helps service teams classify cases the moment they arrive. Autonomous agents in commerce guide customers to the right products with real-time stock visibility. For marketers, AI personalizes campaigns and generates segment descriptions and translations, ensuring relevance at scale. For sales teams, AI keeps data clean and actionable, eliminating duplicates and surfacing the right opportunities at the right time.

 AI isn’t just about efficiency alone; it is about elevating every interaction into a moment where trust can be deepened and loyalty earned.

Here are the highlights from 麻豆原创 CX in Q3 2025.

AI that drives results

From decision-making to customer engagement, AI-powered intelligence and agents streamline processes and remove friction. Teams gain the ability to respond faster, deliver smarter interactions, and grow with confidence while delivering customer experiences that feel effortless, reliable, and personalized.

麻豆原创 Service Cloud

• Business information extraction in cases: Save time by automatically extracting registered product information from the case description, using pre-delivered elements for business information extraction.

麻豆原创 Sales Cloud 

• Contact and individual customer duplicate checks: Maintain clean, accurate records by managing redundant and data. This generative AI capability checks for duplicates and returns a confidence score, leaving the decision-making in human hands.

麻豆原创 Emarsys 

• AI-assisted product finder: Enable marketers to use natural language prompts and keywords to quickly search and locate products for targeted campaigns. Automatic product catalog sync ensures you are always working with the most up-to-date data.
• AI-assisted segment description generator: Generate human-readable segment summaries to improve execution. This ensures that existing segments are easily discoverable with descriptions that are intuitive and straightforward.
• AI-assisted campaign translator (pilot): Translate email campaign copy flexibly and seamlessly within the editing workflow. Localize product descriptions across languages to quickly build, optimize, and launch multi-language campaigns.

麻豆原创 Commerce Cloud 

• Shopping Agent: Using product stock awareness to return real-time inventory data, the configurable Shopping Agent can display or hide out-of-stock products in its recommendations. This makes for smarter recommendations, reducing friction and abandoned carts. For B2B transactions, merchants can also choose whether the agent answers questions about bulk product availability.

麻豆原创 Revenue Growth Management

• AI-assisted promotion creation: Create new promotions quickly by getting recommendations for promotion names, when to run a promotion, what products to include, which spend type to use, and recommendations for discount type.

Scale smarter with greater flexibility

Scaling efficiently while providing flexibility for customers means optimizing operations, offering expanded channel options, and extending visibility to customers and partners.

麻豆原创 Emarsys 

• Microsoft Ads integration: Scale personalized ad experiences across the Microsoft Search Network, including Bing, Yahoo, AOL, and other Microsoft properties.
• Conversational messaging for LINE (): After expanding our offering to in the Q2 release, we now support the popular conversational channel LINE, giving marketers a direct way to connect with customers in the channels they use every day and making it easier to turn engagement into conversion.

麻豆原创 Commerce Cloud 

• Central order service: This feature for seamlessly integrates online and offline transactions, paving the way for flexible customer experience scenarios like “buy online, return in store” (BORIS) and “buy in store, return online” (BISRO).
• Availability push: now allows customers to proactively send real-time product availability information to external systems like webshops and marketplaces, ensuring they have the most current stock data without needing to request it.

麻豆原创 Sales and Service Cloud 

• 麻豆原创 Preferred Success: We are empowering our customers to make the most of their 麻豆原创 investments with the . This interactive workshop helps participants pinpoint which processes to optimize, outsource, or remove for the greatest impact. Learn how to identify critical processes, define roles and responsibilities, and establish a sustainable approach to process governance.
• Integration review V2: A comprehensive solution launch checklist for 麻豆原创 Sales Cloud and 麻豆原创 Service Cloud Version 2 integrations ensures successful rollouts and compliance with 麻豆原创 best practices. The checklist systematically evaluates authentication mechanisms, interface configurations, middleware settings, and 麻豆原创 Integration Suite implementation. 

麻豆原创 Enterprise Service Management

Updates to include:

• Case summary enhancements: Sentiment trend and sentiment graph can now be enabled in the interaction summary for additional information on a customer. Internal and external case notes can be configured and used to generate the resolution summary overview.
• Custom services: Gain more flexibility and extend capabilities without modifying the core application. Integrate external functionality into 麻豆原创 Service Cloud V2 with custom services.
• Template visibility and restrictions: Every document is also an opportunity to establish trust. Now you can strengthen document security by limiting template access to those who need it.

麻豆原创 Revenue Growth Management 

New to  are:

• Custom KPIs: Assess the performance of your account and promotion planswith custom KPIs, tracking metrics that suit your planning and reporting processes. Save time by creating KPI profiles to define a set of standard pre-defined KPIs.

• Promotion calendar export to PDF: Reduce uncertainty, lower costs, and build relationships with better alignment on annual promotions and EDLP agreements with customers. Key account managers can now share a promotion calendar and associated promotion details in a PDF file, making collaboration easier and decisions faster.

Trust advantage in AI-powered customer experience

AI is now woven into the fabric of the 麻豆原创 CX road map, guiding how data, processes, and experiences come together. This deep integration sets the stage for a new era of customer engagement, one where intelligence anticipates needs, adapts in real time, and continuously strengthens loyalty at every touchpoint.

Learn more about what is new in 麻豆原创 CX Q3 2025

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Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience.

This makes a lot of sense given that today However, the results aren鈥檛 always matching the hype.

A recent found that while enterprise AI adoption is rising, real impact is often elusive. The reason? Many businesses are still operating with disconnected systems and disjointed data. Without a strong foundation, AI can鈥檛 deliver what it promises.

Siloed systems aren鈥檛 just a technology problem鈥攖hey鈥檙e a business barrier.

The CX Disconnect: When Fragmentation Undermines Intelligence

Too many organizations still rely on a patchwork of tools for customer experience, supply chain, finance, and HR. While these point solutions solve individual challenges, they create friction and disconnect across the business. In an AI-powered world, friction is the enemy.

AI thrives on complete, clean, and . If your marketing, sales, service, and fulfillment teams cannot see the same data in real time, or trust that it鈥檚 accurate, your AI strategy will not be set up to succeed.

With the best intentions to embrace AI in an effort to achieve incredible efficiency, instead, customers will still lose valuable time on manual integration, inconsistent customer experiences, and AI outputs that are only as good as the (fragmented) feeding them. The delightful experience aspirations turn into trust lost and frustration all around.

Modular Innovation, Meet Enterprise Intelligence 

麻豆原创 has reimagined enterprise management with , representing a fundamental shift from traditional ERP systems to a modular, composable architecture that integrates AI, data, and applications into a unified platform.  

Grounded in harmonized, semantically rich data, this architecture allows businesses to make sense of data that has traditionally been scattered across systems and trapped in silos, so AI has the comprehensive data it needs to quickly generate meaningful insights.

麻豆原创 Business Data Cloud (麻豆原创 BDC) with native integration of 麻豆原创 Databricks, serves as a data backbone for business AI. It seamlessly connects all 麻豆原创 data and third-party data and provides integrated governance to enable real-time AI-driven decision making. 聽

Companies do not lose precious time locating and preparing data for AI. AI systems work on trusted, contextualized data, not just generic data. This produces accurate, reliable, and actionable AI recommendations that enable organizations to scale AI innovation rapidly across business domains.聽

麻豆原创 BDC is the foundation for , 麻豆原创鈥檚 AI copilot that acts as an intelligent orchestrator across the entire business suite. 麻豆原创 BDC ensures that Joule has structured business context for natural language processing and that its outputs are accurate so that Joule can provide always-on assistance to break down silos between business operations.聽

For example, when a customer service or sales representative handles a complex order issue, Joule can: 

• Check real-time supply chain constraints

• Respond to RFPs faster
• Personalize the response by pulling in relevant customer history from
• Speed response with automated case routing and research

The results are faster resolutions, happier customers, empowered employees, and incredible business outcomes with less effort and overhead.

CX + AI + ERP = Real Results

Integrating CX AI with core ERP systems enables end-to-end process optimization that was previously impossible with fragmented systems. When CX systems connect natively to back-office systems, organizations gain:聽

• Real-time personalization powered by operational data
• Intelligent workflows that prioritize high-value customers
• Predictive insights that help teams act before issues arise

The numbers speak for themselves. According to an , customers using this approach reported these benefits:

• Up to 60% reduction in the number of issues service and support teams deal with due to fewer manual errors, automated self-service support functions, automated self-service, and AI chatbots
• 25% to 50% improvement in time to resolution for issues that did require service or support resources
• 25% to 70% improvement in productivity of digital marketing and customer operations teams
• 50% to 90% improvements in sales team productivity by offloading smaller transactional sales, faster quote generation, and streamlined order management
• 20% to 40% increase in productivity of business operations due to less time spent on invoices, payments, shipments, and returns and more informed decision-making

This is not just incremental change; it鈥檚 enterprise transformation, driven by customer needs and powered by AI.

The Future of Intelligent Enterprise Operations 

Embedded within a composable business suite represents a bright future that takes the possibility of AI and makes it a reality.聽

• Businesses can seamlessly orchestrate intelligence across all functions, delivering experiences that feel effortless to customers while optimizing operations behind the scenes.聽
• Artificial intelligence won鈥檛 just automate individual tasks, but also orchestrate entire business ecosystems to deliver superior outcomes.听听
• Maintaining enterprise-grade reliability and enabling modular innovation will allow organizations to adapt to changing market conditions while creating competitive advantages.聽

With the rise of AI, businesses face a pivotal moment in time. Taking advantage of all that technology has to offer demands more than point solutions and departmental optimizations; it requires unified platforms, complete clean underlying data, and a clear unified strategy.

Jessica Keehn is chief marketing officer of 麻豆原创 Customer聽Experience.

Research from multiple industry sources indicates that this isn鈥檛 just an emerging trend — the emphasis on consolidation is growing at an unrelenting pace.

According to ADAPT’s CIO Edge , a comprehensive study of more than 140 CIOs, are planning to consolidate their vendor landscape.

This trend is not just about making minor adjustments to meet market demands; a majority of organizations are targeting a , which represents a significant and fundamental shift in how enterprises approach their technology ecosystems.

The urgency for CIOs to transform their vendor landscape is palpable across all sectors and industries. A of more than 1,000 technology professionals revealed that 90 percent of IT professionals identified software consolidation as a priority, with 73 percent predicting their organizations will continue growing software investments while simultaneously consolidating vendors.

This paradox — expanding capabilities while reducing complexity — defines the modern CIO’s challenge.

The false promise of best-of-breed

This vendor consolidation trend contrasts with movements like the MACH alliance, which  promotes a pure 鈥渂est-of-breed” approach. While its underlying architectural approaches (Microservices, API-first, Cloud-native, Headless) are sound and arguably have become table stakes in the SaaS world, MACH created unexpected challenges for enterprises.

Initially lauded for its flexibility and agility, MACH ended up creating significant complexity 鈥� more than most enterprises can handle 鈥� at a time when they are looking for simplicity more than ever.

The economic reality is stark: fully MACH implementations usually upfront compared to a unified solution that is pre-configured. Companies must consider not only the purchasing of multiple services, but also the cost and time required for employee training and adoption. Running MACH architecture requires people with highly specialized skills in cloud infrastructure, APIs, microservices, and tools designed to streamline development of the user-facing part of a website or web application. The job market for that talent is uber-competitive, even in the age of AI, meaning you’ll need to have the resources to pay them well or else your competitors will.

The hidden costs of fragmentation

Research reveals several critical drawbacks to the fragmented fully best-of-breed  approach:

• Increased complexity: Managing hundreds of microservices becomes exponentially daunting and expensive rather quickly, with system issues potentially impacting multiple services simultaneously. The management and expertise required to oversee such architectures can be daunting 鈥� and expensive. Once system issues are discovered, they could impact numerous services, which requires deep knowledge coordinated across multiple areas of expertise for troubleshooting and debugging. This can make resolution complicated and cost prohibitive.
• Integration challenges: Trying to make connections between services and systems that were not designed to work together requires additional development expertise, which is expensive.聽 Incompatibilities between functions like search, customer service, catalog management, and OMS can lead to degraded customer experience and loss of loyalty.
• Security concerns: The beauty of MACH architecture is also the beast: all of the composable microservices, APIs, and cloud offerings represent security risks. Comprehensive security requires consistent implementation across all components, which can be challenging when using solutions from different vendors. Businesses must develop robust security frameworks and governance models to ensure protection across their entire MACH ecosystem.
• Vendor management complexity: Best-of-breed usually means working with dozens of vendors rather than a few, which can add vast complexity to development and customer support depending on the long-term viability of each vendor, which must provide critical functionality for services or tools that could be discontinued or significantly changed in the future.

The strategic advantage of unified platforms

As CIOs prioritize vendor consolidation, 麻豆原创’s approach to “Suite as a Service” or “best of breed as a suite” offers a pragmatic solution that addresses the fundamental challenges of fragmented architectures. Rather than forcing organizations to choose between flexibility and integration, the (麻豆原创 CX) portfolio provides both through a unified yet composable business suite that spans front and back-office operations, in conjunction with a pre-integrated and certified rich ISV ecosystem that allows businesses to compose with intention, wherever this makes sense business-wise.

The flywheel effect: applications, data, AI

The true power of consolidated platforms lies in what 麻豆原创 calls the “flywheel effect.鈥� In this model, applications generate data, data trains AI, and AI optimizes applications. This creates a virtuous cycle where:

• Better data feeds better AI
• Better AI feeds better applications
• Better applications generate better data

This integrated approach is only possible when organizations move beyond siloed point solutions to embrace unified platforms that can leverage the full spectrum of business data. Companies already invested in 麻豆原创 technologies have discovered that a to the data architecture that AI requires.

Quantified benefits: the economic case for consolidation

of 麻豆原创 CX solutions reveals compelling evidence for the vendor consolidation approach:

• Operational Efficiency Gains
  • Faster time to value: Organizations can fully connect and integrate their CX and ERP data in as few as six months
  • Reduced implementation time: Companies avoid roughly 25 to 50 percent of the time and effort required to build integrations from scratch
  • Improved productivity: Depending on job function, customers report 10 to 300 percent improvement in daily productivity
• Cost Optimization
  • Lower total solution costs: While individual solutions may appear cheaper, the holistic end-to-end solution approach is far more cost-effective
  • Reduced maintenance overhead: Organizations can eliminate up to 70 percent of the time required to manage and maintain systems
  • Resource optimization: Companies avoid having to grow teams by up to 2x to support custom development and integrations
• Strategic Advantages
  • Enhanced customer experience: Seamless connectivity between customer and operational data enables superior customer service
  • Faster innovation: End-to-end visibility enables quicker, more informed decisions leading to faster product launches
  • Reduced operational risk: Standard iFlows provide more reliable connections with fewer potential connectivity issues

The AI-driven imperative

AI is driving the consolidation trend as much as the need to reduce costs. AI models demand high-quality, accurate data to be useful. When — often the result of disconnected digital tools — AI efforts fall short of expectations or stall entirely.

麻豆原创’s unified approach addresses this challenge directly. By providing harmonized SLAs, UX, data models, and provisioning across the stack, along with embedded AI via 麻豆原创 Business AI and a unified and semantically rich data layer via 麻豆原创 Business Data Cloud, organizations can fully leverage AI capabilities across domains without the complexity of integrating multiple disparate systems.

The consolidation acceleration

The trend toward vendor consolidation is accelerating across multiple dimensions:

• Seventy-five percent of organizations pursued vendor consolidation in 2022, up from 29 percent in 2020, according to
• that by 2027, 70 percent of organizations will optimize cloud-native application vendors to a maximum of three
• For midsize companies, the average number of SaaS tools in the last two years

The path forward: strategic consolidation

The evidence is clear: 2025 marks a pivotal moment for CIOs. Organizations that embrace strategic vendor consolidation and choose unified platforms over fragmented point solutions will gain significant competitive advantages in operational efficiency, cost management, and AI readiness.

麻豆原创 CX represents the future of customer experience technology 鈥� not as a collection of disparate tools, but as a unified, intelligent platform that can adapt and evolve with business needs. As CIOs navigate the challenges of 2025, the choice between complexity and consolidation will define their success.

The question isn’t whether to consolidate; it’s whether to lead the trend or be left behind.

With 68 percent of CIOs already planning consolidation initiatives, organizations that act decisively on vendor consolidation will be best positioned to win when it comes to the future of enterprise technology.

Geert Leeman is chief revenue officer of 麻豆原创 Customer Experience.