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According to recent , more than half of marketers say fragmented or outdated data prevents them from acting in the moment.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.

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听,听,听,听, and听.

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�

With the successful , 麻豆原创 has reached an important milestone. This achievement strengthens the foundation of the 麻豆原创 Sovereign Cloud portfolio in one of the most security-conscious markets in the world.

IT-Grundschutz confirms secure operation of 麻豆原创鈥檚 German data center facilities

IT-Grundschutz is the German Federal Office for Information Security鈥檚 (BSI) structured security methodology, and serves as a reference framework in public tenders and supplier assessments.

The certification on the basis of IT-Grundschutz confirms that the secure operation of the physical infrastructure of 麻豆原创鈥檚 German data centers has been positively assessed against Germany鈥檚 defined security requirements. It validates that physical protections, environmental safeguards, and facility-level operational processes meet BSI expectations.

In short: The secure facility operation of 麻豆原创-owned data centers in Walldorf/St. Leon-Rot, Germany, has been independently audited and confirmed against Germany鈥檚 national security methodology.

Strengthening one of 麻豆原创鈥檚 key sovereign delivery options: 麻豆原创 Cloud Infrastructure

The IT-Grundschutz certification strengthens one of 麻豆原创鈥檚 key sovereign delivery options in Germany: 麻豆原创 Cloud Infrastructure.

麻豆原创 Cloud Infrastructure is an Infrastructure-as-a-Service (IaaS) platform, operated in 麻豆原创-owned data centers and co-locations worldwide. In the Walldorf/St. Leon-Rot region in Germany, these data centers are owned by 麻豆原创, a German company, operated by approved personnel with the required security clearance, and designed for high availability, scalability, and stringent security requirements.

These data centers are designed to support GDPR-compliant data processing and to meet heightened regulatory and security requirements in Europe and Germany, including standards relevant to critical infrastructure and the processing of sensitive and classified workloads.

In three independent availability zones across separate data centers, interconnected via 麻豆原创-owned fibre infrastructure and using BSI-authorized German security hardware components approved for processing information classified VS-NfD, this foundation is complemented by certifications such as C5 Type II, KRITIS/NIS 2, TSI Level 3 (extended), ISO 22301, SOC 1 Type 2 and SOC 2 Type 2, SOX, EN 50600 and ISO/IEC 22237 (AC 3), and the German federal data center requirement catalogue.

On top of this, 麻豆原创 Cloud Infrastructure provides:

• An open鈥憇ource鈥慴ased, API鈥慺irst IaaS platform: Offering self鈥憇ervice provisioning, automation, and consistent resource management across deployment models
• A Kubernetes鈥慴ased cloud environment: Enabling cloud鈥憂ative workloads, container orchestration, and modern development patterns
• Open standards and proven open source technologies: Leveraging components used, developed, and refined for more than a decade in sensitive, large鈥憇cale environments
• Optimization for 麻豆原创 cloud services: Supporting aligned operations, integrated security, and efficient execution of 麻豆原创 workloads
• Support for 麻豆原创 and third鈥憄arty applications: Allowing 麻豆原创 and customer-specific workloads to run on one coherent, secure, and compliant infrastructure

麻豆原创 Cloud Infrastructure is an 麻豆原创-developed and 麻豆原创-operated IaaS platform for 麻豆原创 workloads and customer applications, ranging from global cloud scenarios to environments with high sovereignty and regulatory requirements, including an offering for the processing of classified information up to VS-NfD level in Germany. With the 麻豆原创 Sovereign Cloud portfolio, it enables both sovereign 麻豆原创 cloud services as well as the operation of customer workloads in a sovereign environment. At its core, it combines secure application operations with 麻豆原创 Cloud Infrastructure, which is designed for regulatory and operational control.

Sovereignty through choice and control with 麻豆原创 Sovereign Cloud

Digital sovereignty is frequently framed as a question solely of vendor origin, data residency, or the reduction of technical dependency. In practice, though, it is about demonstrable control. At 麻豆原创, we frame sovereignty across four interconnected capabilities:

1. Data sovereignty: 麻豆原创 stores data in local data centers or approved countries, avoiding unauthorized cross-border transfers and meeting critical infrastructure requirements.
2. Operational sovereignty: Sensitive operations stay local. Administration and maintenance are performed only by authorized personnel 鈥� either nationally approved personnel or nationals of an approved country 鈥� with the required security clearance.
3. Technical sovereignty: Control planes are hosted locally, with strict separation enforced through encryption or dedicated infrastructure.
4. Legal sovereignty: Governance stays aligned. Cloud providers must be based locally or in approved countries, and foreign authorities must mitigate ownership, control, and influence risks.

麻豆原创 Cloud Infrastructure meets these requirements. On this basis, data, operations, architecture, and legal control are brought together under clearly defined requirements.

Importantly, 麻豆原创 Cloud Infrastructure is embedded in 麻豆原创鈥檚 broader approach to offering customers choice in sovereign cloud. Different customers face different regulatory, operational, and transformation realities. Sovereign requirements cannot be met with a single model.

麻豆原创 Sovereign Cloud offers a range of delivery options to address different customer needs. Depending on specific requirements, customers can choose between the following options:

• 麻豆原创 Cloud Infrastructure: 麻豆原创鈥檚 IaaS platform is based on open-source technologies and is operated in 麻豆原创 data centers worldwide. Depending on the selected operating model, customer data processing and storage can be restricted to defined regions, for example, within the EU or exclusively in Germany, to meet specific data protection and compliance requirements.
• 麻豆原创 Sovereign Cloud On-Site: With 麻豆原创 Sovereign Cloud On-Site, 麻豆原创 provides and manages the full 麻豆原创 technology stack in a customer-designated data center, from hardware to 麻豆原创 Cloud Infrastructure and the 麻豆原创 Sovereign Cloud portfolio. It combines physical control on site with our operational expertise, for full autonomy while maintaining 麻豆原创鈥檚 support and compliance standards.
• Sovereign hyperscaler-based delivery models: 麻豆原创 partners with premium hyperscalers in specific markets to provide customers the ability to swiftly scale their resources based on their needs. This flexibility, paired with seamless integration, enables customers to innovate faster while maintaining operational efficiency.
• National sovereign cloud platforms such as Delos Cloud: For public sector customers in Germany, Delos Cloud combines hyperscaler technology with sovereign ownership and a nationally defined operating model, helping ensure regulatory alignment and clearly structured operational control.

麻豆原创 enables customers to select the model that aligns with their regulatory requirements, risk profile, and operational strategy.

Sovereignty is built, not declared

For customers, digital sovereignty is not a theoretical aspiration; it is an operational requirement that must function under real-world conditions. The IT-Grundschutz certification of 麻豆原创-owned data centers in Germany marks an important step in that direction.

As regulatory expectations evolve and sovereign requirements become more differentiated, 麻豆原创 continues to enable customers to choose the sovereign setup that aligns with their obligations and risk profile.

Sovereignty is ultimately measured by the ability to operate systems securely and reliably. With 麻豆原创 Cloud Infrastructure, that capability is deliberately embedded into the operating model.

Martin Merz is president of 麻豆原创 Sovereign Cloud.
Jonathan Bletscher is head of Global Cloud Infrastructure & Delivery for Global Cloud Operations at 麻豆原创.

According to the World Economic Forum鈥檚 Future of Jobs Report, analytical thinking ranks as the top sought-after skill in the job market. Yet traditional teaching often struggles to connect theory with practice in a way that truly engages students.

It鈥檚 not a shortage of content or tools; rather, it is a gap in relevance and inspiration that leaves students disengaged from the very skills that could define their careers. Learning needs to be anchored in real-world data, meaningful contexts, and hands-on experience that sparks curiosity and excitement. The best learning doesn鈥檛 come from memorizing concepts, it comes from doing, especially when theory is tied to a topic that learners care about.

This is where , in collaboration with the NHL, comes in.

We have created a new Business Builders game that brings hockey into the classroom鈥攏ot just as a sport, but as a rich, real-world data environment for teaching analytics and critical thinking.

In this latest edition of games under the Business Builders umbrella, students take on the role of a hockey analyst responsible for identifying the factors that drive goal scoring using real NHL Game data.

鈥淗ockey is fast, dynamic, and full of rich data, a perfect environment for teaching critical thinking,鈥� said Brant Berglund, senior director of Coaching and GM Technology at the NHL. 鈥淟everaging a strategic partnership with NHL, 麻豆原创, and HEC Montr茅al, we鈥檝e created a pathway for universities to access approved NHL.com data for academic initiatives, without compromising the integrity of the League鈥榮 data.鈥�

Through our collaboration with the NHL, we provide a learning platform for educators that is full of authentic data students can relate to. The NHL generates just under 1.5 million data points per game, including about 120 shot attempts, 1,000 passes, and 5,000 puck touches鈥攔aw material for deep, practical analysis.

Business Builders can ignite an interest in STEM and help students build real data skills. The hockey-focused game was developed by the team at ERPsim Lab at HEC Montr茅al led by Prof. Pierre-Majorique L茅ger, as well as the support of academics from other universities. This reinforces a core principle of Business Builders: It is created by educators, for educators.

鈥淲hen the question feels meaningful, learners lean in, stay focused, and keep pushing forward,鈥� L茅ger explained. 鈥淔or students in sport management or business management, real sport data can also elevate the learning experience. It adds context, complexity, and constraints that traditional teaching methods cannot provide. Students learn to judge what truly matters, justify their decisions, and manage trade-offs. This develops professional judgment, confidence in analytics, and the ability to communicate strategy and decisions clearly. These skills translate directly to real careers in sport management and business.鈥�

Students explore questions such as:

• What sets top NHL scorers apart?
• Does shot angle affect scoring?
• Which NHL players lead in goals scored, and from what distances?
• Which shot speeds and shot types yield the highest goal conversion rates?

By analyzing these scenarios with 麻豆原创 Analytics Cloud, students learn to interpret visualizations, tell compelling data stories, and sharpen their data-driven decision-making and critical-thinking skills.

For professors, the platform is equally powerful. Business Builders supports active learning at scale by enabling educators to manage and evaluate larger groups more efficiently while gaining visibility into student engagement. This makes grading easier, supports discussion-based learning, and helps instructors understand how students interact with data.

By introducing a modern, meaningful learning experience鈥攆ar more dynamic than slides alone鈥攑rofessors bring real-world relevance into their classroom and elevate the impact of teaching.

麻豆原创鈥檚 role in this collaboration reflects its broader commitment to education, skills development, and preparing students for the future workforce. In a rapidly changing world shaped by AI, data, and digital transformation, access to practical learning tools that build real competencies is essential. Through the 麻豆原创 University Alliances program, 麻豆原创 works with educational institutions around the world to help bridge the gap between academic theory and real-world practice.

鈥淎ccess to business software and real data is essential for preparing students for the future,鈥� said Dr. Katharina Schaefer, head of Academic Partnerships at 麻豆原创. 鈥淲ith free learning platforms like Business Builders, we empower educators to bring enterprise analytics into the classroom and help students develop the skills that are increasingly in demand across industries, and in a world where data and AI define the competitive advantage. Today鈥檚 learners need more than conceptual understanding; they need practical experience with real software and real data to build confidence and readiness for work life.鈥�

One of the educators closely involved in shaping this new game is Prof. Olivier Caya from the University of Sherbrooke, who contributed his perspective as both a faculty member and practitioner.

鈥淲hat makes this experience so powerful is that it all happens in 麻豆原创 Analytics Cloud, the same solution used by thousands of organizations worldwide,鈥� Caya said. 鈥淭his creates a strong connection between what students do in the classroom and what they will encounter in professional practice. Students are not working with software detached from reality; they are developing skills with the same software used in real business environments.鈥�

The result is a learning experience that is fun, interactive, and relevant. Educators can stand out with a state-of-the-art platform that connects passion with pedagogy, while students gain highly sought-after skills using real software from a global technology leader.

Business Builders is provided free of charge to educators and students and includes access to 麻豆原创 Analytics Cloud. It is designed from beginner-friendly introductions to more advanced analytical challenges optimized for master鈥檚-level courses.

After using Business Builders, students can deepen their analytical knowledge through access to , a free learning platform that offers guided learning content, practice systems, and up to two 麻豆原创 certification exam attempts per year, helping them to boost their career opportunities even further.

Business Builders is about connecting passion with education. Together with academic and industry partners, 麻豆原创 is making analytical thinking tangible and memorable鈥攅mpowering the workforce of tomorrow with the skills that matter most today.

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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.

Get started .

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.

Get started .

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%.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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 .

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

Get started .

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.

We believe this recognition reflects 麻豆原创鈥檚 continued focus on helping organizations run resilient, efficient, and increasingly intelligent transportation operations in a rapidly changing global logistics environment.

Magic Quadrant reports are a culmination of rigorous, fact-based research in specific markets, providing a wide-angle view of the relative positions of providers in markets where growth is high and provider differentiation is distinct.

We believe 麻豆原创鈥檚 placement as a Leader underscores our commitment to ongoing innovation across transportation, logistics execution, and supply chain orchestration.

Addressing today鈥檚 transportation challenges

Transportation operations are under constant pressure, from cost volatility and capacity constraints to sustainability requirements and rising customer expectations. Organizations need solutions that help them plan, execute, and adapt across increasingly complex networks while maintaining visibility and control.

and are designed to support these needs through a holistic, end鈥憈o鈥慹nd approach. By connecting freight procurement, planning, execution, and settlement on a single platform, 麻豆原创 helps organizations respond more effectively to disruptions, align transportation decisions with broader supply chain objectives, and support compliance with regional and industry鈥憇pecific requirements.

A platform built for complex, global operations

麻豆原创 Transportation Management supports organizations operating across multiple modes, regions, and industries. Built to scale with business growth, the solution is designed to support complex, global transportation networks while enabling standardization and process consistency across operations.

Customers across industries鈥攊ncluding consumer products, chemicals, agriculture, mining, retail, wholesale distribution, and industrial manufacturing鈥攗se 麻豆原创 Transportation Management to manage complex transportation networks at scale. Industry鈥憇pecific capabilities from 麻豆原创, such as support for automotive and mill and mining operations, along with integration with , help organizations address specialized requirements while accelerating time to value. Dedicated industry business units further tailor go鈥憈o鈥憁arket strategies and solutions to industry鈥憇pecific challenges.

Advancing transportation management with AI

Data-driven decision-making is increasingly essential for transportation operations. 麻豆原创 continues to invest in AI-driven capabilities that help automate processes, improve responsiveness, and increase productivity.

Recent innovations include AI-assisted use cases such as goods receipt processing, as well as the integration of conversational planning into transportation planning workflows. These capabilities are designed to help planners and operators work more efficiently by reducing manual effort and supporting faster, more informed decisions across execution and settlement processes. 麻豆原创 Joule for Consultants is another recent AI innovation that accelerates solution adoption by offering instant, expert-level guidance and best practice recommendations for solution configuration.

Supporting a connected logistics landscape

Transportation does not operate in isolation. 麻豆原创鈥檚 logistics portfolio brings together transportation, warehousing, and business network collaboration on a cohesive foundation.

This includes the recent general availability of , a new solution designed to support regional and local distribution operations by combining transportation execution, warehouse processes, and carrier collaboration in a single offering. 麻豆原创 Logistics Management complements 麻豆原创 Transportation Management by helping organizations extend standardized logistics processes to satellite locations and growing operations, supporting broader adoption while reducing complexity. 麻豆原创 Logistics Management can be deployed alongside 麻豆原创 Transportation Management to support multi-tier transportation operations, providing the right tool for each level of complexity.

麻豆原创 Transportation Management, together with other logistics solutions from 麻豆原创, helps organizations modernize their logistics operations in a way that aligns with their broader ERP and supply chain strategies as they progress on their transformational journeys via or .

Why organizations choose 麻豆原创 Transportation Management

Organizations choose 麻豆原创 Transportation Management to support complex transportation requirements across global and regional operations. The solution offers broad functional coverage, deep integration across the 麻豆原创 supply chain portfolio, and the flexibility to support both advanced transportation networks and evolving business needs.

With continued investment across 麻豆原创 Transportation Management, 麻豆原创 Logistics Management, warehousing, and 麻豆原创 Business Network for Logistics, 麻豆原创 remains focused on helping organizations operate resilient transportation processes while supporting both global complexity and localized execution models.

Explore how 麻豆原创 Transportation Management can .

Till Dengel is global head of Product Marketing for Logistics and Asset & Service Management at 麻豆原创.

*Gartner, Magic Quadrant for Transportation Management Systems, Brock Johns, Oscar Sanchez Duran, Manav Jain, 30 March 2026.

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.

ANYbotics, a Swiss robotics company, has stepped into this space with a vision to shape a safer future for industrial inspection, one where robots operate as autonomous members of the inspection team, running inspection operations integrated into plant maintenance workflows.听

This vision is embodied in the company鈥檚 鈥淎NYmal鈥�: a four-legged inspection robot designed specifically for heavy industry.

Unlike general-purpose robotics platforms, ANYmal is engineered to operate in 鈥渂ig, dirty, dusty, and dangerous鈥� environments, says Nicole Zingg, director of Technology Partnerships at ANYbotics. Places where stairs, corrosion, heat, and unreliable connectivity are the norm, not the exception.

But hardware, Zingg says, is only one part of the puzzle that makes ANYmal indispensable to customers.

Inspection robotics is about data

鈥淲e build a hardware platform,鈥� Zingg explains, 鈥渂ut inspection robotics is really about data that is consistent and trustworthy.鈥�

ANYmal autonomously navigates industrial sites to collect data that goes beyond what a human can collect alone. Beyond just visual inspection, its sensors also collect multi-modal data, including thermal imaging, ultrasonic leak detection, gas concentration detection, acoustic anomaly detection, and more. The observations are fed into what ANYbotics calls 鈥渋nspection intelligence,鈥� which transforms the collected data into actionable operational insights. The result is higher uptime, longer asset lifecycles, and, most importantly, safer working conditions for humans.

ANYmal can make a huge impact on operations. One offshore wind customer, Zingg says, has used ANYmal to manage all inspections and has eliminated the need to send personnel to a remote platform for months. When human intervention was eventually required, ANYmal鈥檚 data from prior inspections made all the difference. The customer already knew exactly what was wrong, which expert to send, and what equipment to bring鈥攁voiding costly and risky trial-and-error site visits.

Yet for ANYbotics, delivering insights is not enough if those insights are not integrated in the software systems customers use.

鈥溌槎乖� is where ANYbotics needs to be native鈥�

Through extensive user research, ANYbotics discovered that many plant operators, maintenance managers, and field service teams already run their daily operations in 麻豆原创. Work orders, asset histories, performance trends, and decisions all flow through 麻豆原创 systems. 鈥淚f customers are using 麻豆原创, 麻豆原创 is where ANYbotics needs to be native,鈥� Zingg says.

Meanwhile, 麻豆原创鈥檚 Project Embodied AI was looking for robotics companies to partner with. The project focuses on extending the impact of 麻豆原创 Business AI into physical operations by enabling robots to autonomously perform complex tasks with an understanding of the broader business context.

It was clearly a perfect fit and has delivered advantages for both companies.

On the system side, a continuous, unbroken digital thread connects ANYbotics insights from industrial inspections to data in 麻豆原创 systems, helping inform key business and operational decisions across the organization.

For end users, embedding ANYmal directly into familiar 麻豆原创 workflows can also help ease adoption, since introducing robotics into already stretched industrial workforces can trigger anxiety. Concerns about job security, workflow disruption, and complexity are common, but embedding ANYmal directly into familiar 麻豆原创 workflows can help reduce that friction, Zingg explains.

Treating robots as part of the workforce

The first major integration point was听. Rather than sending only human technicians, customers can now dispatch work orders directly to ANYmal as they would to any other field team member. The robot then autonomously executes inspection tasks, gathers data, and reports the results directly back into a company鈥檚 麻豆原创 system.

From there, the integration expanded into asset-related scenarios and is now moving toward broader enablement via 麻豆原创 Business Technology Platform (麻豆原创 BTP), with the goal of allowing robot-generated data to land wherever customers need it in their 麻豆原创 landscape.

The ambition is not to force humans to adapt to robots, but for robots to adapt to human workflows. 鈥淎NYmal has to put data in the 麻豆原创 system, just like human team members,鈥� Zingg notes. ANYmal becomes another worker in the same operational system of record.

Project Embodied AI in practice

This combination of ANYbotics robotic technology with 麻豆原创 bridges the gap between physical operations and enterprise applications and tangibly reflects the goal of Project Embodied AI.

On the 麻豆原创 side, AI agents operate on ANYmal鈥檚 robotic systems to execute physical tasks, such as safety inspections.

On the ANYbotics side, ANYmal is a physical object that moves through space, perceives its environment, and acts within real-world constraints. ANYmal uses 麻豆原创 historic and time-series data to inform decisions while at the same time remaining fully autonomous even in environments with no connectivity.

It鈥檚 important to note, Zingg stresses, that ANYbotics has control over ANYmal鈥檚 behavior and inspection execution, while 麻豆原创 has control over the business context such as work orders, asset data, or operational priorities. It is the 麻豆原创 business context that informs how ANYmal鈥檚 insights are consumed and acted upon while ANYbotics controls ANYmal鈥檚 physical interactions.

Scaling safely and responsibly

Today, more than 200 ANYmal robots are already in productive use worldwide, with inspection deployments in heavy-industry environments that would otherwise require constant human exposure.

Safety remains central to ANYbotics. Each deployment includes extensive testing and an on-site field engineer who helps ANYmal learn and validate its environment and trains customer teams on safe operational procedures. While ANYmal is built to work independently, humans remain firmly in the loop.

A glimpse into the future

As industries face labor shortages and aging workforces, undocumented expertise can all too often be lost. With autonomous inspection robots such as ANYmal, this knowledge is captured and turned into programs that can run day in and day out across multiple sites. The captured data flows into 麻豆原创 to become organizational intelligence that survives any workforce turnover.  

ANYbotics鈥� partnership with 麻豆原创 shows that this combination of robotics and enterprise software is moving swiftly from the experimental stage to real-world implementation.

In the future, industrial inspection will be powered by AI, not as disembodied dashboards or isolated machines, but as an integrated intelligent system where physical robots and digital workflows in 麻豆原创 systems operate as one.

In that future, robots like ANYmal are no longer novelties. They are coworkers, albeit mechanical four-legged ones, quietly extending human capability into places humans were never meant to go. These robots, together with 麻豆原创, are shaping for a future where dirty, dangerous, and dusty industrial inspections are being transformed into business insights.

Top image courtesy of ANYbotics

Once closed, the acquisition will strengthen 麻豆原创 Business Data Cloud (麻豆原创 BDC)鈥攊ntegral for 麻豆原创’s AI-First and Suite-First strategy鈥攁nd accelerate the evolution of 麻豆原创 BDC to a fully interoperable enterprise data platform for enterprise-wide agentic AI. It will provide customers with the tools they need to unify, cleanse and harmonize data across sources for superior enterprise-wide agentic AI.

“Reltio is a natural fit with 麻豆原创,鈥� said Muhammad Alam, member of the Executive Board of 麻豆原创 SE, 麻豆原创 Product & Engineering. 鈥淎cquiring them will further improve our position as a leading business AI provider, combining 麻豆原创 and non-麻豆原创 data to deliver data context that business AI requires. AI cannot reach its full potential when data is fragmented across business units, platforms and domains without connection or context.鈥�

By integrating Reltio after closing the acquisition, 麻豆原创 will make customers’ enterprise data fully AI-ready. Customers will be able to rely on trusted, high-quality data across 麻豆原创 and non-麻豆原创 sources that Joule and Joule Agents use to deliver faster time-to-value for business AI.

Reltio鈥檚 platform helps organizations manage and govern structured and unstructured enterprise data from start to finish. Its AI-based entity resolution identifies and merges related records from different formats and applications into one reliable 鈥済olden record鈥� system of context. Its cloud-native, AI-first design supports a single, consistent view of customers, products, suppliers, locations and employees across both 麻豆原创 and non-麻豆原创 applications. Customers running AI tasks will benefit from increased reliability and consistency of data, bundled in a single source of truth, improving business AI. With that, customers can trust that AI results are correct, and AI-interactions are resolved fast.

鈥淛oining forces with 麻豆原创 presents a tremendous opportunity for us to accelerate our mission,鈥� Reltio Founder and CEO Manish Sood said. 鈥淓nterprise AI needs trusted context that is open and interoperable across the heterogeneous IT landscapes our customers run. This combination accelerates our ability to deliver Reltio as the system of context across 麻豆原创 and non-麻豆原创 environments, while maintaining continuity for our customers and our partner ecosystem.鈥�

Reltio’s data cleansing, unification capabilities and agent-driven workflows will work alongside 麻豆原创 Business Suite applications to improve decisions, reduce integration complexity and deliver trusted, consistent data critical for successful business processes and AI use cases. Low latency delivery and support for the Model Context Protocol (MCP) enable real-time, multiagent workflows across 麻豆原创 and non-麻豆原创 environments, allowing AI agents, such as a procurement agent, to assess supplier risk and trigger actions almost instantly using trusted, real-time data. Reltio offers prebuilt, industry-specific 鈥渧elocity packs鈥� that include data models, rules, matching logic and integrations, and solutions tailored to sectors like life sciences, healthcare and financial services.

By integrating Reltio after closing the acquisition, 麻豆原创 intends to accelerate its customers’ ability to govern and expose master data as trusted and context-rich data products across multiple sources that serve both traditional analytics workloads and AI agents. Reltio will become a core capability within 麻豆原创 BDC, with a flexible commercial model where customers can purchase Reltio as a separate solution or with other 麻豆原创 products. The Reltio portfolio will also remain available as a standalone offering for the foreseeable future.

The transaction is expected to close in Q2 or Q3 of 2026, subject to customary closing conditions, including regulatory approvals.

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About Reltio

Reltio is a leader in data unification and management, delivering cloud-native, AI-native master data management (MDM) to help enterprises create trusted data and unlock context intelligence for analytics, automation, and agentic AI. Designed for complex, multi-vendor environments, Reltio helps organizations unify, cleanse, harmonize, govern, and activate core data from multiple sources in real time鈥攁cross 麻豆原创 and non-麻豆原创 systems. The Reltio Data Cloud uses advanced entity resolution, continuous data quality, and relationship intelligence within an intelligent data graph to connect data across systems and reveal the full context behind customers, products, suppliers, and other key business entities. This enables organizations to reduce data friction, improve operational execution, and accelerate time to trusted decisions. For more information, visit .

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�.

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United States Only: 1 (800) 872-1麻豆原创 (1-800-872-1727)

For more information, press only:
Marcus Winkler, 麻豆原创, +49 151 571 18 691, marcus.winkler@sap.com, CET
Aim茅e Leabon, 麻豆原创, +1 (212) 653-9600, aimee.leabon@sap.com, EST
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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.
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SafetyGuard was created as part of a program at UTUM鈥檚 Digital Product School鈥攚here teams of selected students work on real-world challenges鈥攊n just 12 weeks by a student team, 鈥淢IDAS,鈥� and 麻豆原创 Research & Innovation. This project illustrates just how effective cross-location collaboration with the ecosystem can be in rapidly creating prototypes as a foundation for product development at 麻豆原创.

Embodied AI: a joint focus of innovation

The objective of this particular prototyping project was to identify use cases in which robotics and AI could be seamlessly integrated into business processes. Based on its research and on user studies, team MIDAS pinpointed the reliable detection and documentation of safety risks as one such use case.

Safety inspections are essential in many industries, but they are often time-consuming and error-prone. SafetyGuard could change that: leveraging embodied AI, it makes inspections faster, more efficient, and more reliable, without increasing the workload for employees.

Embodied AI鈥攖he integration of artificial intelligence into physical robot systems鈥攚ill be a focal point of investment and development work at 麻豆原创 going forward.

SafetyGuard combines two technologies: modular robotics and AI-powered autonomy. In this prototype, robots, such as drones and humanoid systems capable of inspecting work environments without human intervention, are equipped with a specialized AI model that is trained, for example, to detect where protective equipment is missing and to automatically document safety-related incidents. What鈥檚 more, the robots can multitask. While they are carrying out inspections, they can transport materials and monitor machinery鈥攁n approach that combines efficiency gains with increased safety levels.

鈥淪afetyGuard demonstrates just how effective our ecosystem approach is. In this project, an 麻豆原创 team in Potsdam and a group of students in Munich joined forces and very quickly built a prototype that will have a real impact on product development,鈥� Tobias Riasanow, head of Ecosystem Development at 麻豆原创 Labs Germany, says. 鈥淚t鈥檚 the perfect example of what 麻豆原创 understands by 鈥榚cosystem development.鈥欌��

The project is also strategic to 麻豆原创 in that SafetyGuard addresses real-life industry requirements and complements 麻豆原创鈥檚 solutions for environment, health, and safety management. The prototyping approach that led to SafetyGuard could therefore become part of the 麻豆原创 portfolio in the future to help further reduce the time it takes to get from an idea to a product.

Programs with impact

To date, 13 prototypes have been developed for 麻豆原创 under programs run by UTUM, all in close collaboration with product teams at 麻豆原创 and directly related to their respective road maps. The programs offered by UTUM include:

• Innovation Sprint: Here, students have just one week to work on prototypes for solving specific user challenges. The most recent sprint, The Future of Retail with 麻豆原创 Joule, produced five such prototypes, including solutions for intelligent inventory optimization, virtual shelf monitoring, and retail assistance systems.
• Digital Product School: This 12-week program for students is designed as a platform for developing executable software prototypes. One prototype created out of this program was Carbon Data Exchange, which is now part of 麻豆原创 Sustainability Control Tower. Another is an application that makes it easier for developers to access the extensive documentation for 麻豆原创 Field Service Management. Instead of wasting valuable time searching, they can simply type their questions into a chatbot and receive helpful answers, including code examples and direct links to the documentation they need.
• Multistakeholder projects: Additional prototypes have been created in longer-term programs such as Digital Hub Mobility and Circular Republic. Programs like these bring together experts from companies, startups, and research institutions over several months and allow 麻豆原创 to test innovations in real-world customer and partner environments at an early stage in their development.

Co-innovation gets results鈥攆aster

The collaboration between 麻豆原创 and UTUM shows how quickly ideas can lead to tangible results when students, researchers, and 麻豆原创 teams work together to apply scientific approaches to real-life industrial challenges. SafetyGuard is an example of how embodied AI innovations can be created and how different groups of experts can benefit from one another.

鈥淪afetyGuard demonstrates the extensibility of 麻豆原创鈥檚 approach to embodied AI. 麻豆原创鈥檚 embodied AI layer integrates the business context and triggers actions across the suite. SafetyGuard鈥檚 AI-native, manufacturer-agnostic design is scalable across different use cases and enables multitasking, allowing, for example, robots to process safety incidents while performing other tasks such as industrial asset inspections. SafetyGuard is a proof point for 麻豆原创 for the added value of using cognitive robotics in safety scenarios.鈥�

Adelya鈥疐atykhova and Dr.鈥乽kasz鈥疧strowski, Initiators and Supervisors of the student challenge

This first appeared on the German 麻豆原创 News Center.

鈥淭here鈥檚 so much data; I would say in esports, too much data,鈥� said Thom Valks, partnerships manager at Team Liquid, referring to the 1 trillion points of data his company deals with. 鈥淗ow do you figure out what the right questions are to ask? And then how do you get quick answers to those questions? That was the main problem.鈥�

Founded more than two decades ago, Team Liquid has become a global powerhouse in professional gaming.

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鈥淲e鈥檙e the biggest esports organization in the world,鈥� Valks said. 鈥淕aming is a huge industry, a billion-dollar industry nowadays. And esports is at the tip of the pyramid. People come to watch with thousands in stadiums like normal sports. And we are the best team in the world at it.鈥�

Before partnering with 麻豆原创, Team Liquid relied on spreadsheets and manual analysis.

鈥淲e were doing everything in Excel and manually combing through the data, which turned out to be really not doable,鈥� Valks explained. In 2018, the team began working with 麻豆原创 Business Technology Platform (麻豆原创 BTP), connecting directly to game publishers鈥� APIs for League of Legends and Dota. This allowed analysts to build dashboards and streamline data processing.

The impact was immediate: 鈥淏efore we partnered with 麻豆原创, I think we had something like four or five analysts per game. If we can off source that to a tool and focus on really important data questions, that鈥檚 way more beneficial. And I would say the last year or so with AI, it鈥檚 really taken a next step.鈥�

Now, Team Liquid is taking its relationship with 麻豆原创 one step further by turning to Joule to sort through the data and make decisions even faster.

鈥淛oule has taken the data that we have in our database and you can now ask it: 鈥楩ind me the best hero to play against this team over the last six months.鈥� It will turn out an answer that actually makes sense. That’s revolutionary for us.鈥�

Looking ahead, Team Liquid hopes to expand access to Joule across the organization. 鈥淚f we can get Joule to everyone, it really innovates their gameplay,鈥� Valks said. 鈥淭hat鈥檚 something our competitors should be really afraid of.鈥�

Matt Dillman is a senior videographer at 麻豆原创.

This decision will help Haleon operate, scale and serve consumers in new ways by building stronger, more agile foundations for delivering its trusted everyday health products. It marks a significant milestone in Haleon鈥檚 transformation into a world-class consumer company.

鈥淒elivering a better consumer experience starts with strong foundations, and leading digital technology and infrastructure are at the heart of this,鈥� said Claire Dickson, Haleon鈥檚 chief digital and technology officer. 鈥淥ur latest partnership with 麻豆原创 is another important step in our journey to becoming a world-class consumer company. It will revolutionize how we operate, with AI-enabled systems driving faster, simpler, more integrated ways of working. This will allow our people to focus on what matters most鈥攕erving consumers and unlocking growth.鈥�

麻豆原创 Business Suite will drive the simplification and standardization of critical processes across Haleon鈥檚 global operations, enabling more integrated, automated end-to-end processes across diverse parts of the organization.

With clearer visibility across markets and more intuitive systems replacing fragmented workflows, the business can operate with greater speed, consistency and resilience. These improvements strengthen supply chain responsiveness, support innovation and help Haleon better respond to changing consumer needs. This enables Haleon to deliver trusted everyday health products at scale while strengthening collaboration with the healthcare professionals who recommend its products to consumers worldwide.

Haleon can drive greater business efficiencies by integrating core processes across finance, supply chain, HR and sales in one connected system with real-time data. By building AI into everyday work and embedding it within Haleon鈥檚 digital infrastructure and across its functions, teams can make better data-driven decisions and respond more quickly to changing consumer needs. The automation of routine work across multiple functions frees up employees鈥� time so they can focus on more strategic work that delivers value for the business and consumers while accelerating growth.

This digital transformation program builds on a long-standing relationship between the two companies, with the transition from Haleon鈥檚 current platform on 麻豆原创 ERP Central Component beginning later this year.

鈥淎I outcomes depend on connected processes and trusted data,鈥� said Peter Maier, 麻豆原创鈥檚 senior vice president for strategic customer engagements. 鈥淲ith 麻豆原创 Business Suite, Haleon is building an AI-ready foundation that embeds intelligence across the enterprise, helping simplify operations, improve resilience and scale innovation.鈥�

Haleon plans to adopt 麻豆原创 Cloud ERP applications with embedded AI and deploy the 麻豆原创 Business Data Cloud solution to harmonize 麻豆原创 software and third-party data in a governed, single source of truth. This connected platform will be able to support AI-assisted innovation and enable agentic AI, where AI agents can identify issues earlier and recommend actions across key business processes.

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Media Contacts:
Lawrie Benfield, 麻豆原创, +44 7776515259, lawrie.benfield@sap.com, GMT
Sonya Domanski, 麻豆原创, +44 7345465928, sonya.domanski@sap.com, GMT
麻豆原创 麻豆原创 Room; press@sap.com
Gemma Thomas, Haleon, gemma.x.thomas@haleon.com

The agreement referenced in this announcement was signed outside 麻豆原创鈥檚 first quarter reporting period.

Top image courtesy of Haleon

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.

We believe this recognition reflects our continued investment in a modern, scalable AI-ready integration platform that meets the needs of organizations operating across increasingly complex hybrid and multicloud landscapes.

Why orgnizations continue to choose 麻豆原创 Integration Suite

Part of 麻豆原创 Business Technology Platform (麻豆原创 BTP), 麻豆原创 Integration Suite brings together API management, event鈥慸riven architecture, process integration, and AI鈥慳ssisted development in one unified offering. It gives customers a reliable way to connect distributed systems, orchestrate workflows, and operate securely across hybrid and multi-cloud environments鈥攚hether those landscapes run primarily on 麻豆原创 solutions or a mix of third鈥憄arty applications.

By using metadata, events, and APIs as its backbone, the suite provides an integration foundation that supports AI agents and increasingly autonomous enterprise processes. Organizations in manufacturing, logistics, retail, and other highly regulated industries rely on this foundation to maintain performance and stay compliant at global scale.

Innovation that scales with your business

Over the past year, 麻豆原创 expanded its AI鈥慳ssisted capabilities to help customers move faster and operate with security and reliability. New AI-assisted features include anomaly detection, script optimization, traffic prediction, and integration鈥慺low generation. Combined with more than 4,000 prebuilt integration flows and over 250 connectors, organizations can accelerate design and reduce manual effort.

麻豆原创 Integration Suite now runs in more than 40 data centers worldwide, giving customers flexibility for in鈥憆egion processing and data鈥憇overeignty requirements. These enhancements help teams detect issues earlier, optimize performance, and shorten time鈥憈o鈥憊alue across complex hybrid landscapes.

Accelerating agentic AI adoption

骋别产谤.听贬别颈苍别尘补苍苍 modernized its global retail checkout platform with 麻豆原创 Integration Suite and advanced event mesh, enabling the company to process 300,000 price鈥慶hange events in 30 minutes without system degradation.

“Advanced event mesh has completely changed the way integration and process orchestration run. Everything works better.”

Benedikt Althaus, team lead, Integration Services and Platform Solutions, Gebr. Heinemann SE & Co. KG.

Shimano Europe benefits from the efficient, scalable, and future鈥憄roof integration foundation of 麻豆原创 Integration Suite to accelerate its go鈥憈o鈥憁arket process. By streamlining integrations across systems, the company improves operational efficiency and enhances the overall customer experience through a more agile and reliable integration landscape.

“To accelerate the go-to-market process, we provided an effective and efficient integration platform with 麻豆原创 Integration Suite, a future-proof and scalable solution that improves our customers鈥� experiences.”

Fernanda Ribeiro, IT application architect, Shimano Europe

Siemens AG relies on 麻豆原创 Integration Suite to harmonize global reporting processes and ensure compliance with evolving regulatory requirements. By standardizing integrations across regions and supporting diverse country鈥憇pecific tax protocols, 麻豆原创 Integration Suite helps Siemens streamline compliance operations and maintain consistent reporting quality worldwide. This foundation strengthens Siemens鈥� ability to adapt to changing regulatory environments with greater confidence and efficiency.

“Managing international tax requirements is much easier. It will be implemented around the globe.”

Andrea Spandau, head of Digital Tax Ecosystem, Siemens AG

Looking ahead

We believe this year鈥檚 recognition underscores our commitment to advancing 麻豆原创 Integration Suite with deeper AI capabilities, more reusable business content, broader industry coverage, third-party adapters, and an improved developer experience. Our goal is to help customers automate more of their operations, innovate with confidence, and scale as their businesses evolve.

Learn more

Sid Misra is chief marketing officer for 麻豆原创 Business Technology Platform.

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.

Now, however, many economists and policymakers view AI as a potential catalyst for reversing that slowdown. AI鈥攅specially the rise of generative AI and AI agents鈥攊s widely expected to shape the next phase of productivity growth in advanced economies, including those in the U.S. and Europe.

The key question for business leaders is not whether AI will matter, but how large the productivity gains will be, how quickly they will materialize, and which region will benefit most.

Productivity growth

The (OECD) estimates that AI could raise annual labor productivity growth in advanced economies by roughly 0.4 to 1.3 percentage points, depending on adoption intensity and sector exposure. These gains would be meaningful because even an additional half percentage point of annual productivity growth compounds significantly over a decade.

However, the OECD and other economists stress that outcomes depend heavily on complementary investments in digital infrastructure, workforce training, and organizational change, rather than on technology alone.

Between 1995 and 2019, U.S. labor productivity grew at 2.1% annually compared to one percent in Europe. This disparity arose in part because companies in the U.S. invested more aggressively in information, communications, and technology while those in Europe were constrained more by regulatory and other factors.

Expectations for AI-driven productivity gains remain generally stronger in the U.S. than in Europe. suggests that widespread adoption of generative AI could raise U.S. labor productivity growth by around one to 1.5 percentage points per year.

Several structural factors support this view. The U.S. has a deep technology ecosystem, global leadership in AI research and venture capital, and a large, digitally intensive services sector, including finance, professional services, and IT, where generative AI tools can be rapidly deployed.

Agentic AI

In both Europe and the U.S., AI agents represent a particularly important development. Unlike earlier automation tools that handled isolated tasks, AI agents鈥攍ike Joule Agents from 麻豆原创鈥攁re designed to plan, reason, and execute multi-step workflows. For example, an agent might manage customer service tickets, draft responses, query databases, escalate issues, and update systems鈥攁ll with limited intervention.

In knowledge-based industries, this kind of workflow automation could significantly raise output per worker. But rather than replacing entire occupations, AI agents may reduce time spent on repetitive administrative and 鈥渓ong-tail鈥� tasks, enabling workers to focus on higher-value analysis, strategy, and interpersonal activities.

Despite stories about failed corporate AI projects, which can typically involve bolt-on or stand-alone AI pilots rather than a more integrated, holistic approach, recent evidence from the U.S. suggests that productivity gains are already emerging in some sectors. For example, financial institutions have reported significant efficiency improvements in back-office operations through AI deployment.

Similarly, experimental studies in professional services show that generative AI can increase output quality and speed, particularly for less experienced workers, effectively narrowing skill gaps within teams.

European outlook

The outlook for productivity gains in Europe from AI is more mixed. According to a recent the medium-term gain in productivity from the AI alone would vary considerably across countries, and for Europe as a whole would be rather modest: about 1.1 percent cumulatively over five years.

But with pro-growth reforms, the IMF suggests that much bigger gains are possible over the longer run. Like the OECD, the IMF emphasizes that regulatory frameworks, labor market structures, and the pace of technology diffusion will strongly influence outcomes.

Several structural differences shape Europe鈥檚 trajectory and the size of what has been called the 鈥淎I growth dividend.鈥� First, AI adoption among small and midsize enterprises (SMEs), which form a larger share of the European economy than in the U.S., tends to be slower. Second, Europe鈥檚 digital market remains more fragmented across national boundaries, languages, and regulatory systems, which can complicate scaling technology platforms. Third, the European Union has taken a more precautionary regulatory approach to AI governance. While this may reduce certain risks, it could also dampen short-term productivity gains if compliance burdens slow deployment.

Europe鈥檚 strengths

That said, Europe has strengths. It leads in advanced manufacturing and industrial engineering, sectors where AI-driven optimization, robotics, and predictive maintenance can raise capital productivity. In these areas, AI agents embedded in industrial systems could significantly enhance supply chain efficiency and reduce downtime.

In addition, as 麻豆原创 executives have pointed out, Europe has an enormous repository of structured business and manufacturing data, which is essential for reliable and effective AI systems as well as trust in AI Agents.

If AI adoption accelerates in manufacturing and energy systems and if European companies seize the opportunity to build advanced AI agents and apps using their business data, Europe could see much more robust medium-term productivity gains. As an example, 麻豆原创’s internal use of AI tools has already significantly improved its own developer productivity.

Labor flexibility

A critical factor in both the U.S. and Europe is labor market adjustment. Historically, the U.S. labor market has demonstrated greater flexibility, with higher rates of job switching and occupational mobility. This flexibility may facilitate faster reallocation of workers into AI-complementary roles, amplifying productivity gains, though this could be offset by more effective existing workforce retraining.

As the (BIS) has noted, AI鈥檚 productivity effects are unlikely to be automatic. Productivity gains from AI depend on complementary investments in skills, management practices, and digital infrastructure. The BIS warns that without these, AI tools may produce only marginal efficiency improvements.

The historical lesson from past general-purpose technologies, such as electricity and IT, is that productivity surges occur only after organizations redesign processes to exploit new capabilities and take a holistic rather than piecemeal approach toward implementation.

No AI bubble

While some investors have expressed concerns about an AI bubble, total AI spending in the U.S. is still below one percent of GDP. Joseph Briggs, senior global economist at Goldman Sachs, notes that this is well below historical infrastructure cycles. For comparison historical infrastructure investments such as IT spending, railroads and canals typically represented between two and five percent of GDP.

Like these previous investment waves AI, particularly agentic AI, is likely to generate significant productivity growth and a corresponding boost to GDP in those regions and sectors that seize the AI opportunity.

Over decades, our customers have built powerful digital foundations on 麻豆原创 to run end-to-end business processes across their enterprises鈥攐ften extending and customizing these systems to support their unique business needs. Now, many are entering the next phase of transformation: modernizing their 麻豆原创 landscapes to unlock the full potential of AI.

As companies move to cloud-based 麻豆原创 environments and clean-core architectures, they are preparing to embed intelligence directly into business processes. This enables new forms of automation, with AI agents that operate across enterprise systems and execute increasingly complex tasks.

Modernizing these systems while introducing AI at scale is a significant undertaking. It requires technologies that integrate with existing applications, operate reliably within mission-critical workflows, and meet the governance standards enterprises demand.

That鈥檚 why, over the past few years, we have partnered with to combine advanced AI technology with deep business context. Our goal is to help organizations accelerate modernization and apply AI across the applications and processes key to their success. This collaboration will be showcased at NVIDIA GTC.

Building the foundation for enterprise-grade AI

Through our collaboration with NVIDIA, we are accelerating the entire life cycle of enterprise AI鈥攆rom model development to high-performance runtime execution鈥攁nd powering AI scenarios across our portfolio. ,  which consists of open libraries such as and , helps accelerate large-scale model training across distributed RL environments. It enables teams to build and refine enterprise-grade AI models faster.

Models are hosted through  and , where our customers and partners leverage those best suited to their use cases. microservices optimize inference performance, and we have observed up to a 20% improvement compared to another popular open source serving engine. Enabled by NVIDIA GPUs and NVIDIA NIM, the increased performance allows organizations to combine advanced AI models with trusted 麻豆原创 business data and processes to ensure that AI operates within the workflows that drive business operations.

Modernizing the business logic that runs the enterprise

AI models trained on 麻豆原创 knowledge and accelerated using NVIDIA technologies are already helping customers tackle some of their most pressing modernization challenges. For example, evolving business logic embedded in the 麻豆原创 systems that run their operations.

For decades, organizations have extended 麻豆原创 applications with custom ABAP code that reflects how their businesses operate. That logic captures years of operational knowledge across finance, supply chain, service processes, and more. But modernizing these environments for the cloud and preparing them for the next generation of AI-driven innovation can be complex.

To help accelerate this journey, 麻豆原创 developed . a foundation model trained exclusively on real-world ABAP code and the business logic used across 麻豆原创 environments. The solution incorporates specialized models for code-related tasks, including StarCoder2 for code completion, and Codestral for deeper code understanding and explanations. These models are served through NVIDIA NIM microservices to deliver high-performance inference.

brings these capabilities into the developer experience, helping teams analyze existing ABAP code, understand how customizations interact with core business processes, and generate new code when needed. By making decades of embedded business logic easier to interpret and update, we help organizations accelerate modernization and preserves the knowledge that makes their operations unique.

Connecting AI to business operations

The collaboration between 麻豆原创 and NVIDIA also explores how AI can operate within enterprise workflows to help organizations apply intelligence across both physical operations and complex planning environments. One emerging area is embodied AI, in which intelligence extends beyond software systems into the physical world. By combining AI reasoning with sensors, robotics, and enterprise data, organizations can connect real-world observations directly with digital business processes.

For example, predictive maintenance alerts from can trigger robotic inspections that analyze equipment using thermal, visual, and acoustic signals. These signals are evaluated alongside asset histories and maintenance records to identify potential issues. then orchestrates follow-up actions through , prioritizing work orders and guiding technicians with the right operational context. By linking physical-world insights with enterprise workflows, organizations can turn physical-world signals into coordinated enterprise actions.

The same principle applies to complex planning environments. Supply chains today must manage a constantly shifting web of constraints, from supplier availability and transportation disruptions to evolving customer demands. With NVIDIA, we are exploring technologies, such as NVIDIA Metropolis and NVIDIA Cosmos, to bring the latest AI advancements into warehouse management, safety, and asset inspection.

Together, we are also bringing new capabilities to  that combine agent-based reasoning with the  GPU-accelerated optimization engine. This enables planners to simulate complex supply chain scenarios and evaluate alternatives with more speed and accuracy. By integrating advanced optimization with 麻豆原创鈥檚 supply chain planning capabilities, organizations can dynamically model constraints, adapt plans as conditions change, and make more confident decisions in increasingly complex environments.

Collaboration with large-scale 麻豆原创 customers helps identify real operational bottlenecks, paving the way for AI-driven solutions. . The Taiwan-based global electronics manufacturer and manufacturing solutions provider will work with 麻豆原创 to develop AI-powered innovations for manufacturing and supply chain operations.

By combining 麻豆原创鈥檚 enterprise applications and business context and Foxconn鈥檚 manufacturing expertise, organizations can enhance operational efficiency, increase resilience, and advance decision-making across complex production and supply networks.

Experience agentic AI at NVIDIA GTC

麻豆原创 is enabling Joule Agents across its application portfolio, helping organizations automate tasks and coordinate complex workflows within business processes. At NVIDIA GTC, visitors will see how these capabilities are extended using  on to build agents tailored to specific enterprise scenarios.

And because 麻豆原创鈥檚 AI architecture is model-agnostic, organizations can bring their own models into these workflows, in addition to those deployed through 麻豆原创 AI Core. The hands-on experience at NVIDIA GTC will demonstrate how organizations can build AI-driven workflows that operate directly within the enterprise systems that run their business.

It all happens at , taking place March 16-19, 2026. Join us to see how 麻豆原创 and NVIDIA are helping organizations modernize enterprise systems, accelerate AI adoption, and move toward the AI-native enterprise:

• Attend our session: on Tuesday, March 17, from 2:00-2:40 p.m.
• Visit the 麻豆原创 booth, #2001, to explore agentic AI in action, participate in hands-on vibe-coding with Joule Studio, and witness next-generation enterprise automation

.

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

麻豆原创 is expanding the Joule solution across 麻豆原创 Concur solutions and introducing new automation capabilities:

• A new integration between Joule and Microsoft 365 Copilot, now available, embeds travel and expense tasks into everyday productivity tools. Employees can create and submit expense reports, upload receipts, book travel and receive policy guidance in 麻豆原创 Concur solutions without leaving Microsoft applications.
• Two new Joule Agents further streamline expense compliance and reporting.
  • Expense Automation Agent automatically creates and populates expense reports for employees so all they have to do is review, refine and submit.
  • Expense Pre-Submit Audit Agent validates receipts and flags discrepancies before submission to reduce report rejection and reimbursement delays.
  • Both agents are currently available through the 麻豆原创 Early Adopter Care program with general availability expected later this year.
• New AI-based rule creation tools simplify the complex task of managing policy rules in the Complete by 麻豆原创 Concur and Amex GBT, Concur Travel and Concur Expense solutions.
• The 麻豆原创 Sales Cloud solution now integrates with Booking Agent to streamline workflows and enhance productivity for sales teams.

麻豆原创 Concur and American Express Global Business Travel (Amex GBT) , an AI-enabled codeveloped solution for booking, servicing, payments and expensing. New capabilities include AI-enabled travel support with handoff to a live travel counselor and a specialized home page for travel managers. Concur Expense also integrates with Amex GBT Egencia for customers worldwide.

Joint customers of 麻豆原创 Concur solutions and can now create and manage American Express Virtual Cards in Concur Expense, supporting employee spending with controls and added security. The virtual cards can also be used in Concur Travel. This capability is available now to select U.S.-based American Express庐 Corporate and Business customers using Concur Expense with availability for all such customers planned for Q3 2026.

麻豆原创 Concur teams up with Visa to integrate Concur Expense and Visa through the Visa Commercial Integrated Partner program. Initially, real-time notifications (RTN) from Visa card swipes will automatically create expenses in Concur Expense. This capability is planned to be available through 麻豆原创 Early Adopter Care in Q3 2026. 麻豆原创 Concur solutions will now support RTN from all major credit card networks.

Additionally, 麻豆原创 Concur solutions are advancing corporate travel with enhanced booking, expanded global access and intelligent traveler support. The new experience in Concur Travel supports guest bookings, expanded Cleartrip content in India and additional airline options. TripIt Pro adds Image to Plan with Apple Intelligence and expanded Risk Alerts to help travelers organize itineraries and monitor disruptions.

Learn about鈥痶丑别se or join the . 

Visit the . Get 麻豆原创 news via  and .

Media Contact:
Kelly Sheldon Murray, +1 (978) 708-6821,鈥�kelly.murray@sap.com, ET

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.

This has led to a 鈥淭erminal Renaissance,鈥� a return to text-in, text-out interaction.

For many applications, text works, letting users express intent naturally with no onboarding. However, text struggles to convey structured data that is common in business, and without real-time updates, static text results lose relevance the moment they鈥檙e generated.

Structured data is easier to digest when users can filter, sort, and visualize it鈥攖hat is why graphical user interfaces (GUIs) excel at presenting structured data and guiding users through complex workflows. But GUIs are expensive to build and rigid, forcing generic, one-size-fits-all solutions that struggle to provide the fluid, tailored experiences users now demand.

Text is flexible but limited; GUIs are robust but rigid. Generative UI is the unmet need between them and the new frontier for business software.

From static dashboards to dynamic workspaces

Imagine a procurement manager investigating a supply chain disruption. Instead of navigating five different applications and manually cross-referencing data, she asks: 鈥淪how me the suppliers at risk in Southeast Asia and model alternative sourcing scenarios.鈥�

This request sets agents to work behind the scenes. They gather and analyze live data, simulate outcomes, and calculate the projected impact of every alternative. Execution agents are also pre-positioned and ready to act on command.

The user doesn鈥檛 have to deal with any of this complexity. For them, a dynamic interface materializes in seconds鈥攏ot a generic dashboard, but a purpose-built mission control center. Interactive maps highlight affected regions and supply chain graphs update in real time. As the user tweaks parameters, risk scores adjust instantly. Embedded controls stand ready to trigger purchase orders or notify suppliers, enabling the user to decide and execute. Collaboration is simplified; colleagues can join a living workspace: no briefing decks, no context-setting calls.

This is the future: a business suite where a user鈥檚 intent defines their interface and their decisions drive action. To get there, we are combining Joule and Joule Agents with our vision for generative UI. This is not just about on-demand dashboards; it鈥檚 about steering a business with interfaces that adapt to each user’s role, context, and tasks. This is 鈥渧ibe coding鈥� for enterprise operations: shifting focus from syntax to intent.

We are entering an era where AI constructs UIs on the fly, allowing users to engage with them immediately. Generative UI marks the transition from static software suites to 鈥渂atch size 1鈥� applications that act like ephemeral control centers tailored to a specific problem.

Challenges and 麻豆原创鈥檚 answers

Delivering an intent-driven business suite at enterprise scale requires addressing complex realities. We are building generative UI because we understand its promise and its perils鈥攁nd we have unique assets to bridge that gap.

Accuracy

Large language models (LLMs) can produce plausible but incorrect outputs, or 鈥渉allucinate.鈥� A consumer chatbot that hallucinates a movie plot is tolerable; a procurement system that misrepresents supplier terms has real consequences. Our generative UI approach addresses this by visualizing data directly from systems of record with transparent lineage. Grounding the UI in real-time, trusted data is our first defense against inaccuracy.

Trust

If every interface is generated on the fly, how do users know it is reliable? Trust is built on consistency and predictability. Our generative UI is built on the familiar and proven architectural grammar of 麻豆原创 Fiori for lists, dashboards, and workflows. The content is bespoke and the structure is consistent and familiar, so users can always judge and adjust with confidence.

Complexity

Enterprise systems are sophisticated and unique. They are built over decades, encoding massive domain knowledge and business logic. Generative UI builds on Joule鈥檚 existing integration and orchestration capabilities, which already connect to systems across a landscape and coordinate agents to execute complex workflows. Generative UI leverages this foundation, letting users interact with deeply integrated processes through simple interfaces while Joule handles the orchestration underneath.

Why this matters now

The expectations set by consumer AI are real, and the gap between what employees experience at home and what they use at work is widening.

The future of enterprise software isn’t chatbots bolted onto legacy screens. It’s bespoke mission control鈥攊nterfaces that materialize around a user鈥檚 intent, grounded in live data, executed by agents, and governed by the user.

With that, we鈥檙e reimagining how work gets done.

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

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 .

Germany鈥檚 most successful football club and one of the world鈥檚 leading professional sports organizations, FC Bayern has strengthened its long-term partnership with 麻豆原创 by choosing RISE with 麻豆原创 to transition to 麻豆原创 Cloud ERP Private solutions, the digital core of 麻豆原创 Business Suite. This complements the club鈥檚 existing array of cloud solutions. These include 麻豆原创 SuccessFactors, 麻豆原创 Emarsys, 麻豆原创 Concur, 麻豆原创 Analytics Cloud, 麻豆原创 Datasphere, and 麻豆原创 Sports One solutions as well as 麻豆原创 Business Technology Platform (麻豆原创 BTP), 麻豆原创 HANA Cloud and 麻豆原创 Event Ticketing software.

RISE with 麻豆原创 helps position the club to be future ready by unlocking continuous innovation, real-time analytics and AI-enabled insights. The new cloud environment enhances financial management, accelerates merchandise fulfilment and optimizes partner management to help ensure smoother logistics for kits, facilities and the supply chain. Today, more than 9.5 million fan and member data records and more than 25,000 product master data records are managed in 麻豆原创 Cloud ERP applications, providing a unified foundation for fan engagement, merchandising and operational excellence.

Cloud manages match-day peaks

By moving to the cloud, FC Bayern gains faster time to value and elastic scalability to help manage match-day traffic peaks while simplifying IT operations through a unified data platform. The transition also enables a predictable operating expense model, with 麻豆原创-managed security and compliance significantly reducing the club鈥檚 operational burden.

鈥淔C Bayern demonstrates how organizations can leverage the cloud solutions in 麻豆原创 Business Suite to drive innovation and growth,鈥� said Thomas Saueressig, member of the Executive Board of 麻豆原创 SE, Customer Services & Delivery. 鈥淭hrough RISE with 麻豆原创, the club now benefits from continuous updates, integrated analytics and AI capabilities that enhance fan experiences and strengthen operational agility.鈥�

麻豆原创 Cloud ERP Private offers continuous 麻豆原创-driven innovation and integration with services on 麻豆原创 BTP, including advanced analytics, machine learning and process integration. The solutions are hosted in certified data centers with disaster-recovery capabilities, centralized security updates and monitoring, a 99.9% service-level agreement and European Union (EU) data-residency options. This supports compliance with standards such as those of the International Organization for Standardization and the EU鈥檚 General Data Protection Regulation.

The move from a self-hosted model was completed only after rigorous assurance, governance and security measures were taken in compliance with FC Bayern鈥檚 strict operational and privacy requirements.

Putting FC Bayern at the forefront of digital innovation

鈥淥ur partnership with 麻豆原创 ensures that FC Bayern remains at the forefront of digital innovation. By moving to the cloud, we can scale fan engagement, optimize player performance analytics and streamline commercial operations across all global hubs,鈥� said Jan-Christian Dreesen, CEO of FC Bayern M眉nchen AG.

The new environment supports a clean-core approach to cloud ERP and provides a clear road map for adopting current and future 麻豆原创 software innovations including the Joule and 麻豆原创 Green Ledger solutions and additional AI-supported capabilities. This enables FC Bayern to scale fan engagement, player performance analytics, commercial operations, and HR and finance processes more efficiently and sustainably.

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Top image via FC Bayern Media Library

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�.

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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 2024 Annual Report on Form 20-F.
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The hub brings together startups, academia, industry leaders, and defense organizations to co-create solutions that strengthen digital sovereignty, operational resilience, and readiness in response to threats to safety and security.

The launch comes at a pivotal moment. Defense organizations worldwide are shifting from traditional modernization to full digital transformation, with missions increasingly dependent on secure data flows, resilient supply chains, and systems that remain trusted even under stress. In addition, digital sovereignty has become a core component of readiness, requiring architectures that ensure customers maintain full control of their data and operations.

The launch took place in Munich, a new 鈥淪ilicon Valley鈥� for defense innovation, and featured customers, partners, academics, government officials, and representatives from 麻豆原创. The city offers a uniquely powerful foundation for the hub, gathering a fast-growing community of startups, leading research institutions such as the Technical University of Munich (TUM), and established aerospace and defense leaders. The hub unifies the strengths of these experts, connecting them so that they can coordinate their capabilities to meet defense needs rapidly and efficiently.

More than just a physical space, the hub introduces a new framework that breaks down silos and enables a powerful ecosystem that drives defense innovations. Creative startups, leading industry experts, government organizations, academia, and researchers can come together to make ideas mission-ready more quickly and securely, while maintaining the digital sovereignty necessary to protect information and maintain trust.

As a leading technology provider for the hub, 麻豆原创 acts as an enabler, not just an operator. Through our contributions, we have reaffirmed our role as a neutral technology partner, delivering secure digital platforms while leaving mission decisions entirely in customers鈥� hands.

Our long-standing experience and time-tested technology have proved the ability to perform under uncertainty and stress, a must for the readiness that defense demands, providing cyber-resilient architectures and real-time visibility into logistics during crises, as well as full governance and transparency.

Our cloud operations model, auditability frameworks, and strict access controls keep mission-critical systems secure, verifiable, and compliant.

With 麻豆原创鈥檚 involvement and support, the hub represents a significant step forward for defense innovation, serving as an important catalyst in a location with the potential to become a global center for the defense industry.

Andre Bechtold is president of 麻豆原创 Industries & Experiences.

Photography courtesy of Norbert Steinhauser.

Headquartered in Nuuk and 100% owned by the Government of Greenland, Royal Greenland is modernizing its 麻豆原创 platform and moving from on premise to cloud ERP in order to future鈥憄roof core processes and unlock embedded AI across its 麻豆原创 business applications.

鈥淲e are moving from our existing setup to 麻豆原创 Cloud ERP and 麻豆原创 Business Data Cloud because we want access to the capabilities you can consume on a cloud platform,鈥� said Lars Bo Hassinggaard, CIO at Royal Greenland for more than 25 years.

The company brings high鈥憅uality wild鈥慶aught fish and shellfish from the North Atlantic and Arctic Ocean to consumers worldwide. It has been running 麻豆原创 since 1998 but is now embarking on its most significant transition to date: migrating 麻豆原创 ERP Central Component to 麻豆原创 Cloud ERP while simultaneously elevating its business intelligence (BI) landscape into 麻豆原创 Business Data Cloud and later transforming BI into 麻豆原创 Datasphere.

The project follows the structured RISE with 麻豆原创 framework, which consolidates platform transformation, operations, and the innovation cycle into one contract.

Lean, selective data transition: 90% fewer data to move

As part of the migration, Royal Greenland is reducing its data volume significantly using the 鈥淟ean Selective Data Transition鈥� method.

鈥淲e are keeping 10 years of data and cleaning up, so we avoid outdated company codes and historical data that no longer create value,鈥� Hassinggaard explained. 鈥淲e鈥檝e achieved a 90% reduction in what needs to be stored and migrated. The method combines data analysis, scoping, and standardized mapping objects in a guided process, ensuring that Royal Greenland only carries forward what is truly necessary, making the financials of the transformation more predictable and avoiding unnecessary complexity.鈥�

Technology first, innovation next

Go鈥憀ive is planned for March 1, 2027. The year 2026 is dedicated to the platform lift itself. From 2027, Royal Greenland will begin building business鈥慸riven improvements on top of the standardized core鈥攆or example, new user interfaces and process optimization using small AI agents within finance and administration.

鈥淩oyal Greenland and 麻豆原创 have worked together since 1998, and we look forward to getting started on the technical part of the platform uplift this January,鈥� Hassinggaard shared. 鈥淲e鈥檙e keeping the transformation as simple as possible for now and will use 2027 to activate the benefits, such as improved data analysis, better user experience, and more efficient work processes.鈥�

Royal Greenland is following a classic waterfall approach and has already established a 鈥済olden shell鈥� as the basis for further configuration and retrofitting.

麻豆原创 is responsible for implementing the cloud solution, which will run on Microsoft Azure, initially in Sweden, with the option to move later to a Danish data center. External advisor Spektra Analytics has supported contract validation.

From in鈥慼ouse experiments to standardized, 鈥渃onsumed鈥� AI

Although Royal Greenland has already successfully experimented with its own AI solutions, including vision鈥慴ased projects in production, the strategic direction ahead is to leverage embedded, standardized AI data products from 麻豆原创 and models built on the 麻豆原创 Business Data Cloud and its semantic data layer.

鈥淲e are a company that prefers to tap into existing AI solutions rather than invent them ourselves,鈥� Hassinggaard said. 鈥淚t鈥檚 far more efficient for us. There is no reason for us to spend resources reinventing what 麻豆原创 already provides. The initial focus will be on process optimization within administrative functions such as finance鈥攕mall AI agents that can streamline daily work.鈥�

Advice to others: Allocate more time, and understand your method

Hassinggaard is clear that the RISE with 麻豆原创 contract, methodology, and preparation work require time and organizational maturity. His advice to other companies facing a similar cloud ERP decision: 鈥淒o it thoroughly鈥攁nd allocate more time than you think. Study the methodology, pricing, and contracts. And bring a competent advisor on board.鈥�

Ellen Vig Nelausen is an integrated communications expert for 麻豆原创 Regional Communications.

The hub is launched as armed forces and security institutions face increasing pressure to manage complex missions across allies, domains and supply chains while maintaining resilience, transparency and control. At the defense innovation hub, 麻豆原创 brings together software, data, AI and industry expertise to demonstrate how integrated digital systems translate strategic requirements into operational readiness. This enables comprehensive integration across key areas such as personnel readiness, logistics, procurement, manufacturing, training and maintenance. Together, these capabilities form the digital backbone required for real-world defense operations.

鈥淒efense readiness today is no longer defined by equipment alone: It is defined by how well people, processes and partners are connected,鈥� said Thomas Saueressig, member of the Executive Board of 麻豆原创 SE, Customer Services & Delivery. 鈥淚n an increasingly volatile security environment, armed forces need systems they can trust鈥攕ystems that are resilient, interoperable and sovereign. With our defense innovation hub, 麻豆原创 is demonstrating how digital platforms can strengthen operational readiness while preserving control, compliance and freedom of action.鈥�

A Hub Built on Munich鈥檚 Defense and Technology Ecosystem

Munich鈥檚 strong defense and technology ecosystem, combining innovative startups, established industry leaders, academic excellence and public institutions, provided the ideal setting for the new hub. Supported by the Technical University of Munich’s academic excellence and the presence of key government institutions, the Munich region is uniquely positioned for cross-sector collaboration. At today鈥檚 launch, the setting provided a fitting backdrop for hands-on demonstrations translating innovation into operational reality. Attendees experienced hands-on scenarios illustrating how 麻豆原创 for Defense & Security solutions connect people, assets and supply chains in a unified, more secure operational picture.

鈥淭he Technical University of Munich is pleased to collaborate with 麻豆原创 in translating advanced research into operational security and defense capabilities,鈥� said Chiara Manfletti, head of the Aerospace and Geodesy Department at TUM and scientific lead of the newly launched TUM Security and Defense Alliance. 鈥淎s technological innovation accelerates, strategic partnerships such as this ensure that cutting-edge scientific developments can be rapidly deployed to strengthen operational readiness.鈥�

The launch also served as a lead-in to this week鈥檚 Munich Security Conference, where questions of resilience, interoperability and technological sovereignty will dominate the agenda. Throughout the week, 麻豆原创 will continue engaging with policymakers and partners on how digital innovation can support security and defense in an increasingly fragmented world.

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Media Contact:
Dana Roesiger, +49 6227 7 63900, dana.roesiger@sap.com , CET
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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 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听accurate听quotes, accommodating the most advanced configuration and pricing requirements,听resulting in听a better sales experience and faster sales cycles.

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

麻豆原创 CPQ is an essential听component听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听market听changes,听support multiple sales听channels,听and support听regulatory听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鈥澨齪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听the number of quotes created per month by 70 percent.听

鈥淵ou听basically give听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听.听“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.听
Lawrence Martin is chief product officer for Finance at 麻豆原创.听

Gartner, Magic Quadrant for Configure, Price, and Quote Application听Suites, Luke听Tipping, Mark Lewis, January 22, 2026听
Gartner does not endorse any company, vendor,听product听or service depicted in its publications, and does not听advise technology users to听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听disclaims听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听a trademark听of Gartner, Inc., and/or its听affiliates. This听graphic was published by Gartner, Inc. as part of a larger research document听and should be evaluated in the context of the entire document. The Gartner document is available upon request from 麻豆原创.听

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听, 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听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. 听鈥淎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.

Recent  shows that almost all organizations now use AI in some form, yet most are still at the beginning of scaling it responsibly and effectively. At the same time, there is no question that technological change continues to happen at a remarkable pace, and it demands careful guidance through constant organizational transformation, strong leadership, and the key ability to learn and unlearn.

I am convinced that the future will not be human versus AI, despite this still-dominant narrative. It will be determined by how effectively human insight, judgement, and expertise shape AI鈥檚 integration into work and society. The real opportunity lies in combining human and AI across creative and analytical domains, applying the right competencies in the right context.

Built on trust and ethical intent, AI can amplify human potential while inevitably transforming certain roles and tasks. The Intelligent Age is not about technological dominance, but about purposeful progress through human-AI collaboration.

The rise of human-AI power couples

Imagine working with a new colleague who has not been trained in a classroom but by algorithms processing vast datasets. Simply put, this AI teammate delivers speed, scale, and precision while you bring judgement, context, and creativity. Together, you achieve outcomes neither could deliver alone.

This is already happening across industries. The real differentiator is how well humans and intelligent systems complement each other鈥檚 strengths鈥攎ainly combining AI鈥檚 capacity for data-driven execution with human adaptability and vision. These human-AI power couples are becoming a new source of competitive advantage, able to solve problems faster, spot opportunities earlier, and innovate more boldly.

Yet this potential only materializes when people trust the AI tools they use: trust built not just on transparency, but on daily experience of systems that help them succeed.

Designing the new architecture of work

To set these human-AI power couples up for success, organizations must rethink the very architecture of work. Trust and collaboration are not enough if the underlying structures remain rigid. Traditional roles and hierarchies cannot keep pace with continuous technological change. Work will become increasingly fluid, shaped by skills, collaboration, and shared intelligence. Our time demands adaptive organizations that continuously learn and enable their teams to take on new challenges as they arise.

Consequently, this shift also places new expectations on leaders. As AI progresses, human leadership becomes increasingly important, not less. Leaders must design environments where human and artificial intelligence reinforce each other, and they must actively drive the effective use of AI to deliver business outcomes. This requires adopting a new model, in which leaders fluently manage integrated systems of people and AI agents. They are accountable not only for their human teams鈥� performance, but also for the limitations of the AI models they deploy. This means creating a working environment where experimentation is encouraged and where people feel supported as their roles evolve.

As shown in 麻豆原创鈥檚 own , employees express growing openness toward AI-enabled coaching and support. When AI takes on parts of the coaching role, leaders must focus on what only humans can provide: context, empathy, and the ability to inspire. AI can track progress, but it cannot build trust or shape culture.

The human skills that will shape the Intelligent Age

As humans and intelligent systems collaborate more closely, the skills people need will also continue to evolve. Research from the  and the  shows that skills have a shorter lifespan than ever before. Traditional job profiles no longer keep pace. The real differentiator is how quickly people can learn and keep up as technology advances.

A skills-led organization takes a holistic view of employees鈥� skills across the entire employee life cycle鈥攆rom recruiting and learning to talent development and succession management. Its defining capability is the ability to adapt with speed to external changes and disruptions. A company can adjust required skills almost in real time. This is a prerequisite to staying competitive and responding quickly to customer and market needs.

AI is the catalyst for this adaptability: it identifies skill gaps in real time, personalizes learning journeys, and enables talent to move fluidly to where it is most needed. This turns skills management from a static process into a dynamic system, preparing a workforce that evolves alongside technology rather than being overtaken by it.

Culture as the true algorithm

At the same time, culture becomes equally decisive. Technology may accelerate change, but culture determines its impact. Responsible AI adoption depends on strong cultural foundations. A culture of trust enables people to take ownership and try new approaches without fear of failure. The goal is to have a workforce with a true growth mindset. A mindset that is defined by the inner drive to grow turns change from uncertainty into progress. It is the ability to learn and unlearn, to let go of outdated approaches and embrace new ones.

In fast-moving industries like technology, the pace of transformation is beyond any single person鈥檚 control; what can be shaped is how we respond to it. When curiosity and adaptation become a constant core element of organizational agility, change is met with confidence.

Building inclusive and forward-looking societies

When such strong organizational cultures guide responsible AI adoption, their influence naturally extends beyond the workplace, shaping how technology transforms societies, economies, labor markets, and education systems. Whether this shift leads to broader opportunity or deeper inequality depends on the decisions we make now.

AI is already widening access to learning, democratizing coaching, creating more opportunities, and enabling people to focus on meaningful, uniquely human work. The challenge now is to scale these gains, so the Intelligent Age drives shared progress鈥攏ot deeper inequality鈥攗nder a responsible, human-centric approach.

What matters now

In the Intelligent Age, technological progress will not wait鈥攏or should it鈥攂ut it does require leaders to redesign how work and organizations function so that human and artificial intelligence advance together.

This demands a radical rethinking of structures, skills, and leadership models to match the pace of innovation. Three imperatives stand out.

• Design for trust: Ensure transparent governance and explicit human accountability, embedded in every stage of AI design; this is essential to building trust in human-AI collaboration.
• Build human capability: Make continuous learning, upskilling, and mobility the default, powered by AI insights that connect talent to opportunity in real time.
• Lead with humanity: Anchor empathy, purpose, and ethical judgment in every decision.

Technology can amplify performance and even inspire to think out of the box, but only when guided by clear intent and values. The future will favor organizations that reimagine work at the speed of technology鈥攁nd keep humanity at its core.

AI will accelerate our potential, and while technology鈥檚 advance is largely unstoppable, it is our values and leadership that will determine how we respond to and guide its impact. AI without humanity is simply incomplete.

Gina Vargiu-Breuer is chief people officer, labor director, and a member of the Executive Board of 麻豆原创 SE.

.

As 麻豆原创 accelerates our strategy around applications, data, and AI, these certification enhancements will help ensure our growing ecosystem is aligned鈥攂oth technically and directionally鈥攚ith our clean core, cloud-forward, and AI-ready approach.听

A framework designed around partner and customer needs 

麻豆原创 is committed to delivering business innovations across applications, data, and AI. With this update, we have listened closely to partners and customers and introduced enhancements that make it easier for partners to听validate听their solutions while听maintaining听麻豆原创鈥檚听high standards:听

• Empowering customers to听leverage听data-driven business and enterprise AI鈥攕ecurely and at scale听
• Supporting intelligent apps, seamless cloud connectivity, and adoption of 麻豆原创 Business Technology Platform (麻豆原创 BTP)
• Adhering to 麻豆原创鈥檚 鈥渃lean core鈥� extensibility guidelines, ensuring future-ready, upgradable integrations

Integration certification and the new interoperability review 

Our refreshed framework offers听two clear paths for partners.

Integration certification (use-case based) 

• For partner solutions aligned with 麻豆原创 strategic priorities (麻豆原创 BTP-based, using 麻豆原创 Business AI, clean core, public cloud, and intelligent apps)
• Certification awarded for specific use cases that adhere to 麻豆原创听strategic priorities for听integration, data, and development guidelines
• Benefits include certified status, branding rights, and access to go-to-market support, with clear guidance and transparency throughout the process

Interoperability review (open and inclusive) 

We are especially excited to introduce the听interoperability review,听a new open program designed in response to partner and customer feedback.

• Open to all partner听and independent software vendor (ISV)听solutions, including those that may not be eligible for听integration听certification
• Showcase听technical compatibility with 麻豆原创 solutions through听compliance with听technical听integration听standards听
• Solutions listed as interoperable听on 麻豆原创 Notes and receive detailed听review听summery
• Helps partners听demonstrate听interoperability and 麻豆原创 compliance to customers.

This new interoperability听review听reflects our commitment to听listen to the 麻豆原创 ecosystem听and听enable more partners听and ISVs听to听participate, fostering innovation across our platform.听

How this benefits partners and customers听听

For partners:

• Easier access to 麻豆原创鈥檚 integration framework, even if formal certification听is not听applicable
• Clear pathways for strategic alignment and accelerated development of maintainable, future-ready solutions
• Co-marketing visibility for certified solutions

For customers: 

• Access to a broader set of partner solutions that are future-ready, upgradable, and compliant with 麻豆原创鈥檚 clean core standards
• Confidence in interoperability and technical quality across 麻豆原创鈥檚 business application landscape
• Faster adoption of data-rich solutions built on robust foundations

Looking forward 

The new framework,听planned to听launch in听Q3 2026, is designed to听empower partners, build trust with customers, and accelerate innovation across 麻豆原创鈥檚 platform.

Our Partner Ecosystem Success team will support this transition throughout the second half of 2026. Partners can preview the criteria for the integration certification and the interoperability review in the or reach out to your 麻豆原创 partner manager or the 麻豆原创 ICC team with questions. 

Karl Fahrbach is chief partner officer of 麻豆原创 SE.

Together, the companies plan to create the digital backbone for a sovereign, interoperable and AI-supported healthcare system. The solutions will combine the expertise of Fresenius, one of the world鈥檚 largest healthcare companies, with future-oriented 麻豆原创 technologies and meet high requirements for data sovereignty, security and regulatory compliance. The plan is to provide an open, integrated and data鈥慸riven digital health ecosystem that enables hospitals and medical facilities worldwide to use AI securely and to handle health data responsibly.

Digital sovereignty for healthcare

麻豆原创 and Fresenius plan to jointly build an individual, scalable healthcare platform that enables connected, data-driven healthcare processes. Based on this, the companies will develop joint, future-oriented and AI-supported healthcare solutions to sustainably increase quality, transparency and efficiency across the entire care chain and set new standards for digital innovation in the healthcare sector. The foundation will be proven 麻豆原创 technologies and products such as 麻豆原创 Business Suite, 麻豆原创 Business Data Cloud (麻豆原创 BDC), 麻豆原创 Business Technology Platform (麻豆原创 BTP) and 麻豆原创 Business AI. These core elements help create a unified, compliant, open and expandable base for the more-secure exchange and use of data as well as for operating AI models in a controlled environment.

Together, the companies also plan to build a sovereign, European solution for an integrated healthcare ecosystem that supports the integration of modern hospital information systems (HIS) based on 麻豆原创鈥檚 鈥淎nyEMR鈥� strategy. Interfaces based on open industry standards such as HL7 FHIR will enable the more-seamless connection of HIS, electronic medical records (EMRs) and other medical applications.

鈥淲ith 麻豆原创鈥檚 leading technology and Fresenius鈥� deep healthcare expertise, we aim to create a sovereign, interoperable healthcare platform for Fresenius worldwide. Together, we want to set new standards for data sovereignty, security and innovation in healthcare. Thanks to 麻豆原创, Fresenius can harness the full potential of digital and AI-supported processes and sustainably improve patient care,鈥� says Christian Klein, CEO and Member of the Executive Board of 麻豆原创 SE.

鈥淭ogether with 麻豆原创, we can accelerate the digital transformation of the German and European healthcare systems and enable a sovereign European solution that is so important in today鈥檚 global landscape. We are making data and AI everyday companions that are secure, simple and scalable for doctors and hospital teams. This creates more room for what truly matters: caring for patients,鈥� adds Michael Sen, CEO of Fresenius.

As part of the joint transformation project, both companies plan to invest a mid three-digit million euro amount in the medium term to consistently drive the digital transformation of the German and European healthcare system through the use of digital and AI-supported solutions.

The partnership is implemented through various forms of collaboration. These include joint investments in startups and scaleups, joint technological developments and close cooperation within coordinated governance structures between the two companies.

Visit the . Get 麻豆原创 news via  and .

Media contact:
Dana Roesiger, +49 62277 7 63900, dana.roesiger@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.听 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.

As companies and governments face challenges around sovereignty, security and competitiveness, they need to embrace approaches that initially appear contradictory: investing boldly despite limited resources, sharing data while protecting it and competing while collaborating. These are not contradictions 鈥� this is the new operating model.

Against this backdrop, it becomes clear that organizations must adopt a three-pillar approach to navigate this new normal of paradoxes.

First, they must ground themselves in flexible digital foundations; second, embed AI deeply and responsibly into their operations; and third, view collaboration as a strategic advantage rather than a compromise.

These principles form the backbone of a sustainable way of working in the Intelligent Age, where progress depends on navigating paradoxes with agility and shared purpose.

Laying the foundation for flexibility

Progress is moving at breakneck speed. Technologies that seemed futuristic yesterday are mainstream today and by tomorrow, they could even be obsolete. To keep pace, organizations need a foundation that is rigid but adaptable 鈥� a platform that can evolve as quickly as the world around it.

That foundation is the cloud. A cloud migration is more than an IT project: it is the digital foundation for a thorough modernization of the entire enterprise, for moving from 鈥済ood 鈥渢o 鈥済reat.鈥�

Modern cloud infrastructure enables data, applications and AI to interoperate seamlessly, creating an environment where innovation can flourish. It accelerates the deployment of software updates and new applications, reduces complexity and provides the scalability needed to respond to shifting demands.

True flexibility, however, goes beyond technology. Organizations must foster a mindset that embraces change, encourages experimentation and prioritizes resilience over perfection. This means empowering teams to adapt quickly, learn continuously and view change as an opportunity rather than a threat.

Drive AI innovation on your terms

As AI rapidly reshapes how we live, study and work, no organization can afford to ignore it, yet many still have questions about how to apply it.

In the business-to-business realm, AI cannot be treated as a standalone technology. To unleash its full potential, AI must be deeply embedded in business processes. This requires three pillars:

• Modern cloud software
• Advanced data management
• A consistent stack of AI technologies

Companies that move from legacy on-premises software to integrated cloud applications unlock AI鈥檚 ability to access, understand and facilitate transactions across the enterprise. This enables AI agents to function as digital coworkers, capable of executing complex workflows spanning the business.

The power AI offers is undeniable and in today鈥檚 volatile world, this often leads to questions around digital sovereignty. True digital sovereignty is about maintaining control over critical data and assets while leveraging the best technologies available in line with national interests.

Data protection and compliance are non-negotiable. Companies and governments must ensure that sensitive information remains under appropriate jurisdictional control.

Internationally aligned sovereignty standards 鈥� such as ISO (鈥嬧�婭nternational Organization for Standardization) and IEC (International Electrotechnical Commission) 鈥� would enable secure, compliant scaling across borders, unlocking the full potential of AI without compromising trust.

Not all data requires the same level of protection. Information essential to national security or public safety requires the highest levels of control. At the same time, less sensitive data can be managed in trusted cloud environments that comply with recognized cybersecurity standards.

This nuanced approach allows organizations to balance innovation with responsibility.

Compete with collaboration

The paradox of competition and collaboration is perhaps the most striking of all. In a hyperconnected world, no company or government can tackle today鈥檚 challenges alone. Cybersecurity threats, climate change and economic inequality are global issues that demand collective solutions.

The competitive advantage now lies in partnerships 鈥� across industries, sectors and borders. Public-private collaboration is essential to co-create AI use cases, build open ecosystems and invest in digital education. Such partnerships are strategic imperatives that strengthen our society and our economy for long-term growth.

Collaboration also extends to governance. Establishing shared frameworks for ethical AI, data privacy and sustainability will require dialogue among stakeholders with competing interests. Yet, this dialogue is the cornerstone of progress.

Dialogue: the operating principle

While the opportunities AI provides are immense, they are by no means guaranteed. The determining factor will be our ability to engage in meaningful dialogue 鈥� as companies and governments, technology experts and policy-makers, innovators and citizens.

In the Intelligent Age, the question is not whether we will face paradoxes, but how we face them. Dialogue must be our operating principle 鈥� the means through which we reconcile paradoxes, build trust and chart a course toward shared prosperity. The future will belong to those who embrace complexity, act with courage and collaborate across divides.

Christian Klein is CEO and member of the Executive Board of 麻豆原创 SE.

.

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.

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