AI works when the foundation is right 

The energy and utilities sector is investing heavily in AI. Business��leaders worldwide are embracing artificial intelligence to increase efficiency, unlock new business models, and prepare for the energy transition. A successful proof of concept is often the first milestone—but it marks only the beginning. The��real challenge��lies in scaling pilot projects across the entire��organization.��

In this context, the time and effort��required��for a full implementation��is��frequently��underestimated. Around six months are needed to build a robust data foundation. A further��12��months pass before initial results manifest in the form of a measurable return on investment. Large-scale rollout can take another three years. The reasons for this are manifold:��

• Unrealistic expectations: Many people use AI in their daily lives for simple tasks and expect similarly seamless effects in complex enterprise environments. 
• Legacy infrastructure: Historically grown system landscapes cannot be transformed overnight. 
• Regulatory complexity: In regulated industries such as electricity, gas, and water supply, compliance requirements are particularly high. They must be factored into every architectural decision from the very beginning. 
• Lack of AI-specific talent: What is needed are people who genuinely understand both the business and AI. This bridge between IT and the business side will become increasingly important in the future. 
• Organizational��change management:��Technology alone is not enough. Organizational transformation is and��remains��the decisive success factor.��

From AI hype to real value 

Building a new application is��only the first��step.��On the path to scaling, lifecycle management, identity and access management, security, compliance, and governance must all be consistently taken into account.��Release management, testing, and continuous improvement processes add further complexity.��“The��companies��that��invest in the right foundation today will benefit from AI to its full extent tomorrow,” says Andre Bechtold,��president and��head of �鶹ԭ�� Industries & Experiences.��

For companies, this means overcoming fragmented data silos and developing an integrated data strategy. Legacy systems must be integrated into a modern data and AI platform on which AI models can genuinely create value. Torsten Welte,��head of Energy & Natural Resources Industries��at �鶹ԭ��,��summarizes��it as follows:��“AI is fundamentally transforming the energy industry. The business must understand what is technologically possible. And IT must understand what the business needs.”��

��can��provide��the��essential foundation for this. AI is already natively embedded in the suite in the form of Joule. This��can open up��concrete use cases for the energy industry:��in the area of asset management and predictive maintenance, utilities��can��proactively manage assets and grids before disruptions occur. The Utilities Customer Self-Service Agent, in turn, enables 24/7 self-service for customers and can reduce service costs by up to 90%.��

Distributed energy requires intelligent networking 

The topic of��distributed��energy��resources (DER) remains of��central importance. In the past, energy flowed in only one direction: from the power plant to consumers. In the future, it will be bidirectional. Consumers��that��generate their own energy will actively feed it back into the grid.��

DER��describes precisely��this principle: the generation of electricity through millions of decentralized resources such as solar panels, EV chargers, heat pumps, and battery storage systems��by��consumers and so-called��prosumers. These assets generate vast amounts of data. Their orchestration��represents��one of the key challenges of the energy transition.��

The ��solution��provides a platform��for��a��single source��of truth: technical assets, commercial contracts, and customer data are brought together in a coherent data model. This helps create the foundation for new business models such as smart tariffs, dynamic pricing, energy sharing, and demand response.

�鶹ԭ�� consistently relies on a growing partner network built around its own data platform. Markus Bechmann,��global VP and��co-head��of��Industry Business Unit Utilities��at �鶹ԭ��, describes it this��way:��“Dynamic pricing and smart tariffs are no longer distant concepts.��They��are the business models��of��tomorrow. With �鶹ԭ��, energy providers already have the technological foundation today to seize these opportunities.”��

�鶹ԭ�� Experience Centers: experiencing AI, not just discussing it 

To make AI tangible, �鶹ԭ�� Experience Centers offer visitors the opportunity to experience AI in real-world scenarios beyond classic demo environments. One central example is the �鶹ԭ�� Energy Park in Walldorf. Using real infrastructure on the campus, �鶹ԭ�� demonstrates how the company itself is implementing the energy transition. This includes e-mobility, intelligent asset management, and energy communities. 

A new chapter for the energy industry 

The �鶹ԭ�� for Energy & Utilities Conference in Toulouse has once again demonstrated that AI in the energy industry is no longer a topic for the future. However, the path from pilot project to company-wide transformation requires more than technological enthusiasm. To meet the challenges of the energy transition, what is needed—alongside technological innovation—is a solid foundation of data, processes, and organization.

The objective of this collaboration is to digitalize procedures, improve efficiency and deliver better services to municipal employees and citizens in the areas of finance, revenue management and human resources.

The Madrid City Council has been working with �鶹ԭ�� software for two decades. It began in 2004 with the implementation of the first solutions in the areas of finance and HR, and in 2020 launched its public administration modernization project with the migration to the private cloud. This process is now advancing further with the adoption of the RISE with �鶹ԭ�� journey and �鶹ԭ�� Business Technology Platform (�鶹ԭ�� BTP). The former is a comprehensive journey that combines the elements needed to migrate to the private cloud under a single contract: �鶹ԭ�� S/4HANA, infrastructure and managed services. The latter is the platform for integration, extension and application development.

A New Public Management Model

The adoption of these technologies represents a true revolution in the way municipal procedures are managed, from budgeting, execution and control of revenues and expenditures to the comprehensive management of human resources. This approach makes it possible to move beyond traditional models based on fragmented systems toward unified management with real-time information and digitalized processes.

The transformation has a particularly significant impact in the tax domain, as part of the project includes the integration of tax and revenue management solutions from �鶹ԭ�� into the city’s financial platform. This enables municipal revenues to be managed as a natural extension of the financial system, eliminating isolated developments and facilitating an end-to-end view of the full cycle, from taxpayer registration and assessment to collection and inspection. As a result, operational efficiency is improved while strengthening financial control and budget planning capabilities.

Currently, two-thirds of the City Council’s tax revenues are already managed within this environment, including Property Tax (IBI), the Urban Waste Tax for Business Activities (TRUA), Capital Gains Tax (IIVTNU) and the Terrace Tax (T2 2023). The next step will be to incorporate the Motor Vehicle Tax (IVTM) and the Economic Activities Tax (IAE).

The project has been developed using a phased methodology. During the first year, the City Council carried out a cleansing and harmonization of master data from its previous management systems (GIIM and +TIL), cross-checking identities with police databases, tax addresses with the Spanish Tax Agency (AEAT) and addresses with the municipal street registry. This process generated taxpayer “Golden Records” and enabled, for example, an efficiency rate of 98.02% for Property Tax (IBI) in 2024. Data quality continues to be maintained for all new registrations.

According to Juan Corro, IT Manager of Madrid City Council (IAM), “�鶹ԭ�� technology offers us an extraordinary opportunity to accelerate our digital transformation and make the vision of a more efficient, innovative and citizen-centric local government a tangible reality. This project marks a paradigm shift: we are moving from managing paper files and isolated systems to managing information and processes in an integrated and intelligent way, with a 360-degree view. As a major capital city, Madrid has both the responsibility and the opportunity to position itself at the forefront of administrative modernization, serving as a benchmark for other municipalities.”

Carlos Lacerda, Senior Vice President and Managing Director of �鶹ԭ�� Southern Europe, stated: “�鶹ԭ�� remains firmly committed to the Spanish public sector, which we have supported in its modernization processes for decades. This project is a benchmark for advanced digital administration and demonstrates how technology can act as a strategic enabler to simplify processes, integrate information and strengthen real-time data-driven decision-making, laying the foundation for a more agile, innovative and service-oriented public administration.”

Benefits for the Administration and Citizens

The project is delivering benefits both in terms of internal efficiency and management, as well as citizen services:

• End-to-end process digitalization and a “paperless” administration: The “paperless” administration model has been consolidated, enabling the full digitalization of HR processes from start to finish. Requests are managed entirely through the municipal intranet. Internally, public employees can review and approve procedures with full traceability and in just a few steps, reducing processing times and errors caused by duplicate data. The result is a more agile, efficient and nearly 24/7 service that improves both the employee experience and citizen services.
• Operational efficiency and improved decision-making: Automation and AI capabilities integrated into the ERP system allow the City Council to significantly improve efficiency and productivity. Routine processes such as bank reconciliations and budget allocations are automated through rules and machine learning. In addition, the use of robotic process automation and services on �鶹ԭ�� BTP facilitates the automatic execution of repetitive tasks across systems. This reduces manual workload, minimizes errors and frees up time. Real-time analytics improve decision-making and, together with mobile and remote access to applications, enable more agile and flexible management.
• A more sustainable and efficient model: The implementation of RISE with �鶹ԭ�� enables the City Council to move toward a more sustainable and economically efficient IT model, based on subscription and pay-per-use principles. This approach reduces upfront investments, provides greater budget predictability and optimizes total cost of ownership. By scaling deployments according to municipal needs and paying only for required resources, the city improves responsible management of public funds while generating potential long-term savings.
• Greater adaptability and evolution: The City Council now has a flexible platform ready to evolve alongside technological, regulatory and social changes. The municipality will be able to align with national and European digital agendas, incorporate AI and advanced analytics capabilities, and evolve toward a smart administration model where data becomes a strategic enabler of better public policies.
• Continuous innovation: �鶹ԭ�� BTP is the innovation platform that integrates internal systems and third-party solutions, eliminating information silos. It also enables the rapid adoption of new technologies and responsiveness to changing needs and supports the City Council not only in modernizing processes but also in continuously evolving and launching innovative public administration initiatives.

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Media Contact:
Belén Martinez Millán, �鶹ԭ�� Spain, +34 91 4567220, belen.martinez@sap.com, CET
�鶹ԭ�� �鶹ԭ�� Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of �鶹ԭ��’s 2025 Annual Report on Form 20-F.
© 2026 �鶹ԭ�� SE. All rights reserved.
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That idea framed a , where Thomas Saueressig, chief customer officer and member of the Executive Board of �鶹ԭ�� SE, and Jan Gilg, global president of Customer Success & Americas and member of the Extended Board of �鶹ԭ�� SE, set out the company’s case for the Autonomous Enterprise.

Their message was clear: As AI moves from promise to practice, customers are no longer asking whether it matters; they are asking how to make it deliver measurable results across the business.

“Every day, billions of people wake up trusting that the world simply runs,” Saueressig said.

But making that happen is anything but simple. Saueressig pointed to the hidden complexity behind everyday routines — from power grids balancing supply and demand in real time to global supply chains moving goods across countries and continents. Enterprise operations, he argued, are the invisible backbone of modern life, even if most people never see them.

Gilg picked up that thread by focusing on the pressure customers now face as they try to translate AI ambition into business value. Excitement is high, he said, but so is urgency.

Customers want to scale AI across the enterprise and connect it to core processes where it can have tangible impact. But according to Gilg, the real obstacle is not the AI itself. It is the enterprise landscape around it.

“The elephant in the room: AI in the enterprise is complex,” he said, pointing to the disconnected applications and fragmented data many organizations still contend with.

That challenge led directly to �鶹ԭ��’s vision for the — one in which AI is embedded into business processes, connected through trusted data, and governed in a way that makes it reliable at scale.

The Autonomous Enterprise vision

“It’s this need for trusted, seamless integration that led us to our vision for the Autonomous Enterprise,” Gilg said.

He presented it not as a future concept, but as a practical operating model in which AI drives end-to-end execution within a trusted governance framework, with people remaining in control.

Saueressig cast �鶹ԭ��’s role as helping customers get there: “Our goal is to help you become an Autonomous Enterprise step-by-step. … We are making AI value real today.”

He linked that approach to RISE with �鶹ԭ��, �鶹ԭ��’s AI offerings, and the �鶹ԭ�� Services and Support Portfolio with its Ssuccess plans, which are designed to help customers put innovation to productive use. The emphasis, he said, is on creating value throughout the transformation journey

“When you are fully committed to RISE with �鶹ԭ��, we are committed to support you at every step,” Saueressig said. That commitment spans even the most complex and hybrid landscapes, he said, stressing that no customer will be left behind.

Lockheed Martin: Readiness over transformation in a high-stakes environment

That customer-first approach set up the next part of the keynote, where customers took the stage to share firsthand how they are transforming their businesses in the real world —  no theory, no abstraction, just practical experience.

Opening the customer round, Lockheed Martin positioned transformation not as an end goal, but to ensure constant readiness in one of the world’s most demanding environments.

“Transformation is not the goal. Readiness is for us,” said Maria Demaree, SVP and CIO of Lockheed Martin Corporation, stressing that the stakes are “human” when systems support national defense and allied missions. Readiness, she explained, means the ability to move “with speed, clarity, and confidence across the enterprise.”

Through its largest transformation investment in the company’s history, Lockheed Martin is redesigning processes end-to-end, connecting fragmented systems, and embedding AI into a model-based enterprise built on �鶹ԭ��.

Operating in a highly regulated environment with strict security and data requirements, the company is focused on reducing cycle times and improving responsiveness. Demaree emphasized that “transformation doesn’t start with technology. You must rethink your processes.” �鶹ԭ��’s role, she said, has evolved from vendor to trusted partner understanding Lockheed Martin’s business and the environment it works in.

Aeropuertos Argentina: From reactive winter operations to proactive AI-driven control

Aeropuertos Argentina made history by becoming the first Latin American customer to take the �鶹ԭ�� Sapphire keynote stage. The company used the spotlight to share a hands-on example rooted in operational urgency and showed how a clean core and focused innovation can quickly deliver results.

Managing 90% of Argentina’s commercial flights, they need to keep airport operations running during severe winter weather. This has historically relied on manual, fragmented processes — driving up costs, safety risks, and environmental impacts. To address this, the company developed an AI agent called Smart Network for Operative Winter (SNOW) to orchestrate weather data, runway sensors, maintenance processes, and operational procedures.

“We passed from a reactive to a proactive model,” said Gustavo Sabato, Chief Information Officer of Aeropuertos Argentina, highlighting expected benefits, including a 16% cost reduction and lower CO₂ emissions. Time to value was fast: from idea to operation in 12 weeks, with rollout starting at two airports and expanding to six more this upcoming winter.

A key enabler was upgrading from �鶹ԭ�� R/3 to �鶹ԭ�� S/4HANA in 2023 and building the solution on �鶹ԭ�� Business Technology Platform.  While integrating multiple non-standardized data sources was challenging, the result is now that the company operates with “only one version of the truth,” said Sabato, and requires minimal manual intervention. The company plans to scale the approach beyond Argentina and into processes at other airports they manage elsewhere, reinforcing that strong technical fundamentals are essential to turn AI into real operational outcomes.

Exxon Mobil: Clean core and solid data foundation

ExxonMobil is rethinking how its operations will remain agile and nimble amid the rapid changes driven by the global shift toward new energy sources.

Bill Keillor, Vice President of ExxonMobil Global Services Company, said the energy giant launched a business-led transformation to simplify processes and unlock data that had become fragmented after decades of customization. “Our goal is not short-term optimization but long-term agility: standardizing on industry best practices, establishing a clean core, and becoming upgrade stable,” he said.

He emphasized that both the transformation and the company’s AI ambitions depend on a strong foundation. “If you can’t get this foundation right, you will continue to pay the price for it,” he said.

Keillor closed with three pieces of advice for any transformation: be crystal clear on strategy and align leadership behind it; put strong governance in place to enable fast, consistent decisions; and choose partners who challenge you and are in for the long run.

Levi Strauss: AI at scale

As Levi Strauss accelerated its shift toward a direct-to-consumer business, it recognized that greater speed and scale would require a lean technology landscape. Jason Gowans, Chief Digital and Technology Officer, said the company started by consolidating nine ERP systems into a single global foundation with RISE with �鶹ԭ��, standardizing processes and establishing a clean core.

That unified backbone now supports Levi’s ambitious AI strategy, with already more than 1,000 AI agents in production across the business. The impact is already visible; one example is wholesale order processing. While 80% of orders already flow through automatically, the remaining 20% — often submitted by smaller customers through handwritten notes, emails, or unstructured documents — previously took two to five days to process manually.

“Now, with the agents that we’ve built on top of �鶹ԭ��, that process takes 20 to 30 minutes,” Gowans said. For Levi Strauss, the lesson is clear: standardization does not limit agility; it makes it possible.

Migration powered by AI

These customer examples illustrated that transformation usually follows a shared path: modernizing the core, moving to the cloud, and unlocking innovation along the way. 

�鶹ԭ�� then showed how AI-powered agents can help customers accelerate that journey through a more integrated, AI-driven approach to transformation at scale. Migration and modernization assistants, , are designed to analyze systems, data, custom code, configuration, testing, and rollout as part of one connected process. By replacing fragmented manual work with coordinated automation, activities that once took weeks — from landscape analysis to custom-code assessment — can now be completed in a single weekend.

The world doesn’t break because of change

Gilg then widened the lens, arguing that every major technology wave brings uncertainty. But every one of these waves has in fact made the world better off by creating more jobs, new business models, and new revenue streams that people couldn’t imagine before. In the same way, he argued, enterprise software will become even more essential because of AI.

That is because the core needs of business remain the same: systems that work, people who care, and teams that collaborate. In Gilg’s framing, AI will not replace enterprise software. It will live inside it, embedded in the processes that keep companies running.

Saueressig brought the keynote back to its opening image: a world people trust to function. In a time of rapid change and unprecedented disruption, he asserted, resilience matters more than ever.

“The world doesn’t break because of change,” he said. “It breaks when change moves faster than resilience. And that’s where �鶹ԭ�� comes in.” Underscoring the importance of people in times of change, he emphasized that beyond technology and AI, transformation remains deeply human, shaped by the people who build and use it. “The future isn’t written by AI.  It is written by us,” he said.

Currently in beta, the agents help organizations deliver measurable results: a greater than 50% reduction in packaging compliance review hours, scenario simulation time cut from a day to 20 minutes, up to 80% reduction in manual GHS classification effort, and over 20% fewer packaging compliance errors.

The agents handle multi-step workflows that previously required hand-offs between teams and systems, including sustainability reporting preparation, packaging and product compliance assessments, carbon footprint simulation, and workplace safety documentation. They address mounting pressure across the enterprise: giving finance teams visibility into how carbon exposure affects forecasts; helping procurement teams manage regulatory risk without slowing down innovation; enabling supply chain teams to spot emission hotspots while maintaining service levels; and supporting operations in connecting safety observations to proactive, audit-ready actions.

New AI sustainability agents

The Sustainability Regulatory Readiness Agent helps organizations prepare for upcoming sustainability regulations such as the by translating materiality assessments into a defensible reporting scope and mapping the right data and metrics to each disclosure requirement. This enables sustainability teams to capture, validate, track, and ultimately disclose ESG information with far less manual effort.

For finance teams that need to manage carbon costs and disclosure risk while balancing the financial implications of sustainability performance, the agent automates financial-grade data mapping between material topics, regulatory requirements, and �鶹ԭ�� finance data, improving audit readiness and turning an existing materiality assessment into a clear, defensible reporting scope. Unlike a standalone sustainability point solution that only surfaces issues or a generic AI model that drafts narrative text, this agent works inside and the broader �鶹ԭ�� landscape to keep reporting scopes aligned to policy and keep underlying data structured and traceable.

The Footprint Optimization Agent brings together carbon, energy, and waste data from across Scope 1, 2, and 3 sources and pinpoints where emissions and other environmental impacts are highest across products, plants, and supply chains. It then runs side‑by‑side simulations of different reduction levers and turns the results into reports, supplier requests, and targeted initiatives that support decarbonization projects and ESG goal tracking. For operations, the agent makes it easy to test “what‑if” operational changes and see their projected impact on carbon and other environmental footprints. It reduces scenario simulation time from approximately one day to about 20 minutes, making operational decisions based on real impact projections available at workers’ fingertips. This directly addresses the financial implications of carbon exposure: with ESG data often derived from industry averages that can vary by 30 to 40% or more from actual values, the ability to simulate and act on granular, accurate data carries significant margin protection value.

The Packaging Compliance Agent reads and interprets evolving packaging regulations starting with the , maps supplier and product documentation to a structured data model, infers and flags missing information, and checks product designs for conformity at scale. It turns scattered, often unstructured packaging data into an auditable compliance record for each SKU, shipment, and product run, reducing manual review effort and error rates in the process.

Procurement and sourcing teams facing growing pressure to ensure supplier eligibility, material compliance, and traceability while managing cost and availability now have an agent that helps protect revenue by catching packaging issues before they block orders or trigger fines. This equates to a greater than 50% reduction in manual compliance review hours and over 20% reduction of packaging compliance assessment errors. As sustainability moves to the transaction level—compliance per SKU, per shipment, per product run—this kind of automated, embedded compliance capability becomes an operational necessity.

The GHS Classification and Labeling Agent collects the required input data, applies the relevant Globally Harmonized System (GHS) rules, and proposes classifications and label elements that can be used directly in downstream product compliance processes.

By automating these steps, it delivers up to an 80% reduction in manual efforts and a 60% reduction in GHS labeling and classification errors. For product and compliance teams that must keep launches on schedule and avoid shipment holds or market access denials, the agent embeds GHS product compliance into everyday workflows, turning a historically expert‑driven, error‑prone process into a consistent, auditable control point across the portfolio.

The Workplace Safety Agent supports workplace safety by analyzing reported observations and proposing follow-up tasks, risk assessments, and controls. It generates updated, approved safety instructions based on those observations to help organizations strengthen safety governance. With operations under increased pressure to ensure safe work environments without compromising service and speed of production, the agent delivers proactive, standardized safety management at scale, reducing the risk of incidents and unplanned downtime. At the same time, HR and EHS leaders can point to a clear trail of actions and updated instructions to demonstrate continuous improvement in safety culture to employees, regulators, and boards.

Only AI can deliver sustainability at scale

To ensure compliance and enhance strategic decision-making, sustainability data needs to become granular. It should move beyond a record of what happened and become a driver of future outcomes. To reach this level of insight, sustainability data needs to be analyzed at transaction level. Getting transaction-level data at scale is not something that can be done manually.

Granular sustainability data allows businesses to ensure compliance, control carbon and cost exposure, safeguard product marketability, and strengthen supply chain transparency and resilience. Perhaps most important is the ability to embed sustainability into business performance and across all business functions. This final point is the key to unlocking sustainable business autonomy.

In the sustainability context, becoming an Autonomous Enterprise means that sustainability policies are executed automatically inside enterprise workflows. This includes connecting financial and sustainability data for trusted steering, automating disclosure and performance insights, and blocking non-compliant shipments. Ultimately, sustainability becomes a governing factor in enterprise decisions, as opposed to a reporting or compliance activity.

Enterprise autonomy entails gradual AI maturation:

• Intelligence: Faster visibility into reporting and materials compliance risks across the enterprise
• Optimization: Data-driven decisions that balance cost, risk, and sustainability impact
• Autonomy: Actions executed directly within operational workflows, eliminating manual coordination

The choices enterprises make now—how data is structured, how decisions are supported, and how sustainability is integrated—will determine whether they can safely scale automation later or whether complexity and risk increase as systems evolve.

With the Autonomous Enterprise, leaders can deliver sustainable outcomes at scale.

Why �鶹ԭ��?

AI needs three things to successfully run autonomously: business and process context, data connection and integration, and a reliable governance structure.

Generic models can read data, but without business context they cannot reason how a business actually runs. They see tables, not operations, and provide recommendations that may be commercially or operationally unviable. Without data that is integrated and connected across all business departments, AI has to perform in siloes, unaware of how sustainability decisions might impact financial targets, or how procurement decisions affect supply chain risk. �鶹ԭ��’s rich ERP data foundation ensures that enterprise AI has the full business picture, not just fragments of it.

Finally, AI that lacks governance and cannot be audited or controlled can be more harmful than helpful to a business. �鶹ԭ��’s more than five decades of business process expertise anchored in governance, risk, and compliance, mean that AI for enterprise deployment can be managed safely and reliably. Sustainability agents operate within defined parameters, ensuring that automation scales without sacrificing control or compliance.

This is the foundation that makes everything possible. Without it, an enterprise has AI experiments. With it, it has an operating model.

Sophia Mendelsohn is chief sustainability and commercial officer at �鶹ԭ��.
Gunther Rothermel is chief product officer of �鶹ԭ�� Sustainability.

They are expected to manage risk, ensure compliance, and deliver strategic value, all while navigating talent shortages and increasing operational complexity. And most are doing it without the end-to-end visibility they need.

Workflows are disconnected, decision-making is reactive, and policies are inconsistently enforced. I have heard this from customers across every industry and, frankly, it is a problem that traditional approaches to procurement technology haven’t fully solved.

That’s what makes this moment different. At �鶹ԭ�� Sapphire, we introduced the Autonomous Enterprise, a fundamental shift in how businesses operate, with AI assistants and agents powering end-to-end execution at scale, with governance built in. Critically, this isn’t just about adding AI features to existing tools. It is about moving from AI in applications to AI on applications—intelligence that works across your entire landscape, not just inside individual products.

Autonomous Spend Management: From concept to reality

Autonomous Spend Management is a core pillar of the Autonomous Enterprise vision, designed to address the fragmentation that holds procurement and finance teams back. By applying agentic AI across procurement, travel, expenses, and external workforce processes, we’re creating continuity where disconnection exists today—intelligent systems that orchestrate activities, connect context, and surface the right insights at the right moment.

What this means for the people doing the work is equally significant. When AI handles routine execution, decision-makers get time and clarity back. They can intervene earlier, with better information, and focus on more strategic work that actually moves the needle.

To bring this to life, we are introducing a new set of Joule Assistants, AI-powered teammates designed to support procurement and spend management across the full life cycle:

• Category Management Assistant: Analyzes spend patterns, delivers market intelligence, and helps build sharper category strategies
• Sourcing Assistant: Manages the entire sourcing life cycle, from drafting RFPs and bids to recommending negotiation strategies
• Supplier Management Assistant: Provides comprehensive oversight of the supply base, from intelligent classification to continuous multi-dimensional risk monitoring
• Contract Assistant: Streamlines contract authoring, flags renewal opportunities, and connects supplier selection through to contract execution
• Requisition Assistant: Guides users to the right buying channel, auto-fills fields, and uses advanced trade-off analyses to help maximize volume discounts
• Buying Assistant:Helps professional buyers identify spend leakage, surface optimal suppliers, and automate order consolidation
• Receiving Assistant: Auto-creates goods receipts and service entry sheets and guides users through quality tracking so nothing falls through the cracks
• Invoicing Assistant: Handles invoice capture, duplicate detection, and payment proposals so finance teams can close faster with fewer errors
• Services Procurement Assistant: Manages the full SOW life cycle from creation through compliance tracking
• Travel Assistant: Simplifies trip planning with pre-spend estimates, streamlined approvals, and built-in compliance guidance
• Expense Management Assistant: Automates expense reporting, capturing details, flagging errors, and keeping everything compliant

The Autonomous Spend Management capabilities run across our cloud ERP application portfolio, including �鶹ԭ�� Cloud ERP Private, for end-to-end coverage across business processes and systems.

Why connected processes are critical

Connection is just as powerful as intelligence, and that conviction runs through everything we  announced this week. AI can only do so much if the underlying processes are still fragmented.

In next-gen �鶹ԭ�� Ariba Buying, new Joule Agents support purchasing and policy management through a more intuitive, persona-driven experience, guiding users toward compliant, contract-linked options while improving catalog management and document traceability. Deeper integration with �鶹ԭ�� S/4HANA Private Cloud Edition and �鶹ԭ�� ERP Central Component means these capabilities work with existing ERP investments, not around them.

�鶹ԭ�� Ariba Contracts now brings contract creation, approvals, and compliance tracking into a single unified workspace. AI-assisted drafting lets teams create contracts using natural language, while centralized visibility into terms, pricing, and key dates keeps data consistent and connected to downstream procurement processes.

We also introduced a new Joule Agent in �鶹ԭ�� Ariba Intake Management to automate how procurement requests are captured and routed across �鶹ԭ�� and non-�鶹ԭ�� systems. And expanded supplier evaluation capabilities in �鶹ԭ�� Ariba Supplier Lifecycle and Performance let teams segment performance data by geography, business unit, or category – with insights feeding directly into to inform sourcing and procurement decisions.

Expanding visibility into services spend and supporting adoption

Nowhere is the need for connected processes more apparent than in asset-intensive industries. In oil and gas, mining, and utilities, external workers can make up 40% of the workforce, yet most organizations are still managing them through manual processes and disconnected systems. The risks are real: expired certifications, overpayments, and poor visibility into work billed versus work actually done.

New �鶹ԭ�� Fieldglass capabilities address these challenges by bringing together the full contractor life cycle, from the moment a worker arrives on site through to final payment. Organizations can now automate time tracking, verify worker credentials and safety requirements before granting site access, maintain tighter controls over equipment, and dramatically reduce the manual effort involved in invoicing.

We’re also using AI to accelerate SOW creation by automatically recommending worker roles based on the SOW description and historical buyer data, which reduces manual setup and improves consistency from the start. And to support adoption, WalkMe Premium is now integrated with �鶹ԭ�� Fieldglass and �鶹ԭ�� Ariba, providing in-app guidance for tasks such as creating statements of work, approving timesheets, and hiring candidates.

The future of spend management

Autonomous Spend Management marks a fundamental shift from managing processes to delivering business outcomes. From chasing cost savings to actively shaping resilience, margin, and growth. From reacting to events to anticipating them.

The real strategic implication is this: Spend does not happen in isolation. Every contract and invoice has a downstream effect on financial performance. When those decisions are made in context—with AI connecting procurement, supply chain, and finance—the enterprise doesn’t just run more efficiently, it runs as one system.

That’s what we are building, and what we announced this week marks a significant step forward.

For more details on this week’s announcements, see the . For more details on the latest updates in travel and expense, please refer to the

Etosha Thurman is co-business lead and chief marketing officer for �鶹ԭ�� Finance & Spend Management.

While expectations for reliable, on-time delivery remain high, organizations are navigating faster‑changing demand, more complex global networks, and increasing pressure on cost and working capital. And they’re looking for ways to turn insight into action more quickly and consistently across the supply chain.

�鶹ԭ�� has been helping organizations build more connected and intelligent supply chains for over 50 years. At �鶹ԭ�� Connect in October, we introduced �鶹ԭ�� Supply Chain Orchestration, establishing a foundation for detecting issues, coordinating responses, and connecting execution across complex supply networks.

The innovations announced this week at �鶹ԭ�� Sapphire extend that vision further. By introducing a new set of AI-driven assistants and agents, we’re moving orchestration toward an autonomous operating model, where planning, manufacturing, logistics, and asset operations increasingly anticipate, coordinate, and resolve without manual intervention at every step.

AI grounded in real operations

AI delivers lasting value in supply chain management only when it is embedded where work actually happens. Autonomous agents do not operate independently of enterprise applications; they rely on deeply integrated processes and trusted data. Precision, compliance, and resilience depend on this foundation. Without it, AI does not scale or earn trust.

At �鶹ԭ��, the Autonomous Enterprise represents a vision for how organizations will run their businesses in the future: with insight, decision-making, and execution increasingly connected, while people remain firmly in control. Autonomous Supply Chain Management is a practical step toward that vision.

Autonomous Supply Chain Management reflects an evolution in how planning, execution, and operations work together. People define goals and priorities, assistants orchestrate activity across domains, and agents execute the work—all within governed, end‑to‑end processes.

At �鶹ԭ�� Sapphire, we’re introducing , enabled by new Joule Assistants and Industry AI scenarios that apply this model to daily operations across planning, manufacturing, logistics, engineering, and asset management. General availability will be phased throughout 2026, starting now.

Joule Assistants across the supply chain

Rather than disconnected AI tools, the following assistants will be embedded directly into core �鶹ԭ�� supply chain applications, where deep process knowledge, semantically rich business data, and enterprise‑grade governance already exist.

Each will support a distinct area of responsibility while sharing context, data, and outcomes across the supply chain:

• Asset and Service Assistant: Changes how work gets detected and dispatched, turning signals and anomalies into action rather than queue items
• Business Network Assistant: Extends this coordination outward across suppliers, logistics providers, and service partners so execution doesn’t stall at the edges of the enterprise
• Logistics Assistant: Keeps warehouse and transportation execution moving as conditions change, coordinating agents rather than waiting for human handoffs at every step
• Manufacturing Assistant: Connects shop floor signals with broader operational context so teams can act on disruptions faster
• Planning Assistant: Helps planners stay ahead of exceptions and constraints without having to manually piece together signals from across the network
• Product Design Assistant: Helps engineering and manufacturing teams stay aligned as products evolve, surfacing the downstream implications of changes before they create rework or delays

From assistants to autonomous agents

In addition to these assistants, �鶹ԭ�� is delivering more than 60 purpose‑built agents across supply chain processes. These agents are designed to sense events, analyze impact, and take guided action within defined business guardrails, helping coordinate execution while keeping people firmly in control.

In manufacturing, agents such as the Production Excellence Agent and Production Master Data Readiness Agent continuously monitor production, quality, and machine signals to detect issues early and keep routings and work instructions aligned with enterprise plans. In asset and service operations, the Asset Performance Alert Processing Agent and Technician Briefing Agent are designed to assess asset conditions, prioritize work, and increase first time fix rates, helping reduce downtime and improve responsiveness.

Beyond supply chain-specific scenarios, these assistants and agents will also extend into �鶹ԭ��’s cloud ERP environment, including , supporting �鶹ԭ��’s broader Autonomous Enterprise strategy. General availability will be phased through 2026, starting now.

Building on this foundation, �鶹ԭ�� Industry AI adds industry-specific intelligence that complements the core assistants. Rather than standalone features, Industry AI brings together purpose-built agents, process expertise, and business data to drive measurable outcomes. This value-led approach helps organizations apply AI in ways that reflect regulated requirements, complex production models, and asset-intensive operations – accelerating information across entire industry value chains.

People remain responsible for strategy, oversight, and the decisions that require judgement. What changes is how consistently high-volume, time-sensitive coordination happens across the supply chain.

Where this shows up in practice

The Autonomous Enterprise is our vision, and the innovations we’ve announced at �鶹ԭ�� Sapphire are concrete steps that customers can build on within current �鶹ԭ�� environments. They are focused on addressing value leakage caused by fragmented handoffs, delayed decisions, and manual work.

In planning, new capabilities will connect commercial decisions directly with supply planning, linking promotion and pricing plans to inventory and replenishment to reduce stockouts, minimize write-offs, and improve planning consistently. New capabilities include vendor-managed inventory, transportation load building, deployment optimization, and co- and by-product planning.

In manufacturing and engineering, updates to will strengthen compliance and traceability in regulated environments. AI capabilities in the engineering-to-manufacturing handover will help teams understand the downstream impact of design changes before they reach the shop floor, surfacing implications for bills of materials, routings, lead times, and costs directly in context.

In , new Joule Agents will support execution-level decisions across warehouse and transportation operations, validating inbound receipts, aligning labor with real workload, and helping organizations respond faster to shifting constraints. Predictive labor planning in will allow operations teams to anticipate workforce needs rather than react to gaps.

In asset and service management, a new �鶹ԭ�� Field Service and Asset Management solution will bring planning, scheduling, dispatching, and field execution together in a single experience, connected to so work execution, parts usage, and costs stay aligned across service, operations, and finance.

These capabilities will become available in phases through 2026, aligning with customers’ existing �鶹ԭ�� landscapes. Together, they represent incremental but meaningful progress toward more connected, automated, and resilient supply chain operations.

The path forward

Supply chains don’t become autonomous overnight. This evolution happens workflow by workflow, expanding automation where it delivers real value, while keeping people firmly in control. As AI becomes embedded in execution, supply chain teams spend less time monitoring and firefighting, and more time shaping decisions, managing trade-offs, and building resilience.

This shift is bigger than any single organization. In a new white paper,��, we explore how leading organizations are moving beyond isolated AI pilots toward AI embedded across end-to-end supply chain processes, and what it takes to get there. This article draws on multiple sources, including analytical support from McKinsey & Company.

That’s the direction we are moving, from reacting toward supply chains that anticipate, absorb, and adapt. What we’re introducing at �鶹ԭ�� Sapphire reflects that commitment.For more details on all announcements made this week, please refer to the .

Dominik Metzger is president and chief product officer of �鶹ԭ�� Supply Chain Management.

Market volatility, liquidity pressures, and currency fluctuations are exposing the limits of traditional planning models built around fixed timelines and after-the-fact analysis. To keep pace, finance teams need the ability to continuously sense change, understand its impact, and steer performance with confidence.

The challenge is that many organizations are still planning with processes designed for a different era. Siloed data, manual workflows, and episodic planning cycles make real-time decision-making difficult, limiting visibility across the entire business. reinforces the urgency: 72% of organizations still find financial planning, budgeting, and forecasting too time-consuming.* In a volatile environment, that lag translates directly into slower responses to risk, missed opportunities, and diminished confidence in the decisions that shape performance.

This is why finance needs a new operating model, one that moves beyond periodic exercises and toward continuous steering. At �鶹ԭ�� Sapphire, we are introducing �鶹ԭ�� Enterprise Planning, a new flagship offering designed to close the gap between insight and action, enabling planning to continuously drive business performance.

The shift from periodic planning to continuous steering

Traditional financial planning has always provided structure, but too often that structure comes at the expense of agility. Planning occurs in fixed windows. Teams work from historical snapshots, static assumptions, and fragmented inputs. By the time a variance is understood or a scenario is modeled, the business may already be operating in a fundamentally different environment.

�鶹ԭ�� Enterprise Planning is designed to move organizations beyond these constraints through a continuous approach to planning and execution built on speed, confidence, and control. Finance teams gain the ability to detect signals as they emerge, evaluate constraints in real time, and connect plans directly to execution.

This Sense-Reason-Act model represents a fundamental shift in how planning operates. Rather than waiting for a planning cycle to surface issues, agents continuously monitor for material changes and respond through guided, explainable decisions embedded in everyday processes. At the same time, �鶹ԭ�� Analytics Cloud continues to support the iterative Plan-Do-Check-Act cycles that finance teams rely on for strategic and tactical planning across mid- to long-term horizons, including model creation, forecasting, variance analysis, and scenario simulation. Together, these two approaches create a planning ecosystem that is both responsive in the moment and disciplined over time.

The solution embeds Joule Agents directly into the planning process, helping connect strategy to operations in real time. Agents can interpret internal and external data signals, model their impact on KPIs, simulate scenarios, recommend actions, and orchestrate planning workflows with built-in governance and explainability. Planning shifts from a single point in time to continuous workflows. When decisions are made, Joule Agents can update plans to support downstream execution. General availability is planned for Q3 2026.

Built on �鶹ԭ�� Analytics Cloud and �鶹ԭ�� Business Data Cloud, these capabilities form a more connected, intelligent planning ecosystem that enables organizations to act decisively and with full transparency.

Why governed data and connected planning matter

Continuous planning is only as reliable as the data it is built on. Without a unified data foundation, even the most advanced analytics cannot produce trustworthy outcomes. As automation increases, this challenge becomes more acute: decisions execute faster, but errors can scale just as quickly.

That is why our approach is not AI in isolation. �鶹ԭ�� Enterprise Planning is built using �鶹ԭ�� Business Data Cloud data products and the �鶹ԭ�� Analytics Cloud solution. �鶹ԭ�� Analytics Cloud remains the foundation for strategic and tactical planning cycles, while �鶹ԭ�� Business Data Cloud provides the governed data foundation underpinning the entire ecosystem. This helps ensure compliance, auditability, and enterprise-wide trust, which becomes even more critical as AI-driven automation expands.

Continuous planning in practice

What makes this vision tangible is how it shows up in real financial workflows. By continuously monitoring market signals and financial positions, these solutions help organizations reduce the lag between insight and action, improving both speed and decision quality. This is the Sense-Reason-Act model at work: sensing shifts in currency markets, reasoning through the impact on cash positions, and acting through guided decisions that keep the business aligned with its financial objectives.

More broadly, the Autonomous Finance domain brings together Joule Assistants and Joule Agents to provide CFOs and finance organizations with more insight, control, and support across their operations. Beyond planning, specialized Joule Assistants coordinate multiple agents to support key finance processes including financial closing, billing, governance, and tax and compliance. The result is a finance function where intelligence is embedded across the full operational scope, not confined to a single workflow.

Because these agents are delivered within �鶹ԭ��’s planning and finance solutions, they carry a native understanding of enterprise data, planning semantics, and mission-critical business processes. The goal is not to replace finance expertise, but to augment it. This gives teams the foresight needed to navigate complexity with greater confidence.

The Autonomous Finance capabilities run across our cloud ERP application portfolio, including �鶹ԭ�� Cloud ERP Private, for end-to-end coverage across business processes and systems.

The future of finance is continuous

The future of finance will be defined by the ability to connect data, processes, and decisions across the enterprise in a continuous loop. Organizations that can sense change as it happens, reason through its impact using trusted and governed data, and act by connecting plans back to execution will be best positioned to navigate volatility with the agility and discipline that modern finance demands.

With �鶹ԭ�� Enterprise Planning, organizations can move beyond static planning cycles and toward a more intelligent, continuous approach to steering performance.

For more details, refer to the and the .

Lawrence Martin is chief product officer and head of Public Cloud Engineering at �鶹ԭ��.
David Imbert is head of Finance Product Marketing at �鶹ԭ��.

*IDC Spotlight, sponsored by �鶹ԭ��, The Rise of Dynamic Planning in the Agentic AI Era, #US54493826, April 2026

The conversation has moved beyond what AI can do into how it should be applied, placing HR at the center of decisions that will shape people, culture, and business outcomes for years to come.

While we have often talked about the “future of work,” the simple fact is that future is already here. The question is whether organizations are ready to operate differently.

AI requires a fundamental rethinking of how work gets done, grounded in the data, systems, and processes that run today’s organizations. And getting it right starts with one clear principle: humans must remain firmly at the center—not as operators of process, but as leaders of judgement, strategy, and change.

What Autonomous HCM means for HR leaders

At �鶹ԭ��, this is the foundation of our vision for the Autonomous Enterprise, announced at in Orlando, where AI assistants can run core HR processes end-to-end, so people are empowered to focus on their most meaningful work while staying firmly in control of outcomes.

brings together agentic AI, HR applications, and real business context—grounded in deep process expertise and enterprise-grade governance—to help organizations anticipate workforce needs and respond with greater precision as business priorities change.

With the new HCM innovations announced at �鶹ԭ�� Sapphire, we are building on the existing breadth and depth of �鶹ԭ�� SuccessFactors with new AI-native functionality that amplifies how HR can help shape the business and elevate what employees are capable of.

Automate work with Joule Assistants

The first shift is automation; not as task replacement, but as a new way of working. A new generation of , delivered through Joule as �鶹ԭ��’s AI engagement layer, bring this to life by orchestrating agents to execute work end-to-end and support decisions in real-time.

These assistants are not just automating tasks; they are guided by employees to reduce manual effort and support a growing range of HR scenarios:

• Payroll becomes proactive, not reactive: The coordinates multiple to prepare payroll runs, identify issues early, and guide administrators to faster resolution, shifting payroll from reactive process to proactive execution. Working alongside the Core HR Assistant and , it helps organizations manage employee data, track time and attendance, and pay employees with greater accuracy and less manual work.
• Talent acquisition flows more seamlessly end-to-end: The helps keep hiring moving from intelligent matching to interview coordination, providing real-time guidance to recruiters and hiring managers. Once a candidate accepts, the takes over to support a smooth transition for new employees. These new Joule Assistants connect talent acquisition processes between and the broader �鶹ԭ�� SuccessFactors HCM suite.
• HR services become faster and more intuitive: The helps administrators resolve common HR questions instantly, directing employees to the right next step and reducing service center volume while improving the overall employee experience.

Reimagine the workforce with AI-driven planning

As AI becomes part of how work gets done, organizations must rethink workforce planning as a continuous leadership discipline, not a periodic exercise. Today, 62% of C‑suite executives say they are dissatisfied with how well people data connects to business performance, according to , making it harder to turn strategy into action. The new workforce planning capability within �鶹ԭ�� Enterprise Planning supports a shift toward strategic work redesign, inclusive of both agents and people, by helping leaders link workforce decisions directly to HR, business, and financial needs.

This workforce planning capability connects data from , , and �鶹ԭ�� SuccessFactors, creating a unified foundation for workforce decision‑making across employees and contingent labor. Together, this moves workforce planning beyond static models. Leaders gain clear scenario insight and the ability to combine human judgment with AI to align workforce and investment decisions.

At a more granular level, constant change means business and HR leaders are often dealing with organizational changes. The new AI‑enabled organizational modeling for replaces slow, disconnected modeling approaches with an integrated experience that supports scenario planning and impact analysis, enabling leaders to evaluate organizational choices with greater accuracy and alignment. With this approach, leaders can quickly explore alternative organizational structures and understand implications before changes are implemented. Whether adjusting roles, teams, or reporting lines, organizational modeling becomes a practical leadership tool, supporting thoughtful change while maintaining data integrity and minimizing disruption. The result is a clearer, more proactive approach that helps organizations make smarter workforce decisions in a constantly evolving business landscape.

Elevate people through continuous upskilling

When it comes to skills, the rise of generative AI has once again accelerated the pace of change. New jobs are emerging, new skills are required, and processes that have worked for decades are being completely reimagined.  The new Workforce Upskilling Assistant delivers personalized, AI-driven learning directly where work happens, in collaboration tools, mobile, desktop and �鶹ԭ�� SuccessFactors—helping organizations keep skills aligned with where the business is headed. By orchestrating multiple Joule Agents, it supports content creation and generation, adaptive micro-learning, and reinforcement, enabling leaders and managers to identify critical skill gaps and accelerate upskilling, particularly in fast-moving areas such as AI.

By delivering learning in the tools and channels employees already use, the Workforce Upskilling Assistant turns workforce and business data into timely, bite‑sized learning moments. Rather than relying on scheduled courses or standalone systems, HR learning teams can quickly convert existing content to deliver learning to the right person at the right time.

A new standard for human-centered Autonomous HCM

�鶹ԭ��’s Autonomous Enterprise vision sets a new standard for how HR leads in an AI-driven world, one where AI assistants and agents take on the work of coordination, so people can focus on leading and shaping outcomes. As AI becomes embedded into how work runs, HR is uniquely positioned to guide what matters most, moving from coordinating processes to guiding decisions, building resilient teams, strengthening trust, and ensuring the workforce is ready for what’s ahead.

That is the promise of an Autonomous HCM platform: human expertise elevated by AI, delivering meaningful impact for both people and the business.

Learn more about how �鶹ԭ�� is delivering Autonomous HCM by catching the replay of the HCM Innovation .

Dan Beck is general manager and chief product officer for �鶹ԭ�� SuccessFactors.

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

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

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

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

Aligning experience and execution

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

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

At �鶹ԭ�� Sapphire, we highlighted assistants that make this real across the portfolio:

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

AI-driven discovery and engagement grounded in business reality

�鶹ԭ��’s collaboration with Google follows the same principle: connect AI-driven discovery and engagement to business execution.

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

By combining �鶹ԭ��’s governed business data with Google’s AI capabilities, assistants and agents can connect customer intent from storefronts, search, and AI-driven channels to �鶹ԭ�� commerce and order processes. This ensures that what customers see reflects what the business can fulfill.

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

�鶹ԭ�� Commerce Cloud innovations

�鶹ԭ�� continues to be recognized in analyst evaluations, including the Gartner® Magic Quadrant™ for Digital Commerce, where �鶹ԭ�� has been positioned as a Leader for 11 consecutive times.

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

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

�鶹ԭ�� is also expanding its ecosystem with Vercel to accelerate storefront development and deployment with optimized performance, scalability, and composable front-end experiences.

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

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

Sales execution turns insight into action

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

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

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

Scaling trusted autonomous service

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

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

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

Industry AI in action

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

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

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

The next phase of customer engagement

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

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

Balaji Balasubramanian is president and chief product officer of �鶹ԭ�� Customer Experience.

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

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

“Today I’m super proud to launch our new �鶹ԭ�� Business AI Platform, which forms the basis for our vision of the future of business: the Autonomous Enterprise, where agents run the business and you can focus on what truly matters,” Klein said.

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

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The business AI imperative

Across industries, organizations are investing heavily in artificial intelligence, yet many still struggle to translate that investment into meaningful business value. At �鶹ԭ�� Sapphire, the message was clear: This isn’t a technology problem; it’s a context and execution problem.

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

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

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

ERP as the foundation for business AI

�鶹ԭ��’s answer to this challenge begins with what Klein described as “the brain of every company: its ERP system.” For over 50 years, �鶹ԭ�� has had solutions with incredibly deep process and data domain know-how alongside the governance requirements, compliance controls, and company-specific configurations that define how businesses actually run.

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

“We’re bringing together LLMs with 50 years of business know-how stored in our ERP. But to do this, we had to do nothing less than completely reinvent our company,” he told the audience. “Today we are very excited to show you the new �鶹ԭ�� and our vision for the Autonomous Enterprise.”

�鶹ԭ�� Business AI Platform

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

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

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

Echoing Klein, �鶹ԭ�� CTO Philipp Herzig, who presented the platform in detail, said it has been designed to close the agent adoption gap in the enterprise by delivering outcome, speed, enterprise-readiness, and context. “It’s the place where you build, contextualize, reason, and govern AI,” he said.

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

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

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

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

�鶹ԭ�� Autonomous Suite

Building on the platform, �鶹ԭ�� Executive Board Member Muhammad Alam, �鶹ԭ�� Product & Engineering, announced the transformation of �鶹ԭ��’s SaaS application portfolio into the �鶹ԭ�� Autonomous Suite, described as the most significant evolution of �鶹ԭ��’s applications business in the company’s history.

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

“�鶹ԭ�� Autonomous Suite brings together the depth of our process expertise, semantically rich data, and built-in governance and compliance,” said Alam. “These agents are designed with outcomes as a core objective. Each assistant has a defined set of ROI KPIs that you can expect it to deliver.” 

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

Turning to Joule itself, Muhammad said �鶹ԭ�� is fundamentally reimagining how users will interact with �鶹ԭ�� applications in the future.

“We call this Joule spaces and along with the familiar Joule conversations experience and Joule Studio 2.0, it is now part of what we call Joule Work,” he explained.

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

Industry AI: H&M and Sector-Specific Transformation

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

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

RISE with �鶹ԭ�� and �鶹ԭ�� GROW: Path to the Autonomous Enterprise

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

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

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

Closing: The Autonomous Enterprise

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

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

“We’ve been reinventing how businesses run for over 50 years, and now by infusing �鶹ԭ��’s ERP brain into the new �鶹ԭ�� Business AI Platform, we’re solving one of the biggest challenges businesses are facing today: how to turn AI into business value,” he said. “It’s the end of long negotiations, supply chain disruptions, financial blind spots, and the beginning of better: Welcome to the Autonomous Enterprise.”

During our event keynote, I took time to preview this exciting new venture, which was formally announced at �鶹ԭ�� Sapphire, alongside our CEO and chairman of the Executive Board, Christian Klein.

We explored how the Autonomous Enterprise is �鶹ԭ��’s new north star and vision. It’s the future of business where AI transforms how people work and processes run.

Building on the Suite-as-a-Service foundation established last year at �鶹ԭ�� Sapphire, �鶹ԭ�� is reinventing itself for AI-native operations that move customers from point-solution AI to enterprise-wide autonomous operations.

With this launch, we’re also re-framing some of the misconceptions and hesitations that we know our customers have about AI.

AI isn’t technology for technology’s sake; it’s about driving outcomes, like real-time intelligence, automated end-to-end workflows, and continuous improvement—all important aspects that AI can deliver.

�鶹ԭ�� partners are �鶹ԭ��’s force multiplier to bring the Autonomous Enterprise to life, expanding reach, credibility, and adoption. To help �鶹ԭ�� partners evolve their practices to align with this vision, we also announced significant new investments in the partner ecosystem during the event.

�鶹ԭ�� Business AI partner-led adoption program

The Partner Summit at �鶹ԭ�� Sapphire in Orlando included the launch of a new offer that funds��partners who��activate, extend, build, and deploy �鶹ԭ�� Business AI for customers. The �鶹ԭ�� Business AI partner-led adoption program is a significant opportunity for partners to guide their clients to unlock the potential of �鶹ԭ�� Business AI Platform.

At �鶹ԭ�� Sapphire, �鶹ԭ�� Executive Board Member and Chief Operating Officer Sebastian Steinhaeuser commented on our need to deepen our partner investments: “�鶹ԭ�� pledges €100M to our partner ecosystem today to fast forward AI adoption and accelerate our customers path to the Autonomous Enterprise. Partners are able to tap into this fund when they support our customers in the adoption and consumption of �鶹ԭ��-delivered agents as well as by working with them to extend agents and build custom agents on our �鶹ԭ�� Business AI Platform.”

The program has four packages:

• Adoption: AI Assistant activated and deployed
• Launch: Joule Studio partner-built custom agent or��workflow/pro-code application
• Performance: Joule Studio partner-built custom agent and��workflow/pro-code application
• Enterprise: Minimum of three Joule Studio partner-built custom agents and��workflow/pro-code application

�鶹ԭ�� will actively nominate customers with potential for this program. Partners can also reach out to �鶹ԭ�� with their suggestions. If the customer qualifies, �鶹ԭ�� will approve the proposed services, and the �鶹ԭ�� partner will execute a statement of work with the customer and share the required documentation with �鶹ԭ�� for funding.

�鶹ԭ�� Business AI and data validated partner program

This new program distinguishes partners that demonstrate a holistic approach to �鶹ԭ�� Business AI and data along with deep expertise and close alignment with our �鶹ԭ�� Business AI and data strategy. Built on the foundation of the existing Competency Framework for the �鶹ԭ�� PartnerEdge program and enhanced by �鶹ԭ�� Business AI and data requirements, this designation signals to customers that these partners are capable and genuinely invested in delivering the full promise of the Autonomous Enterprise, including guidance with autonomous domain blueprint adoption and building agentic scenarios on �鶹ԭ�� Business AI Platform.

Partner agent race to �鶹ԭ�� TechEd

Building on the strong momentum of the partner agent race to �鶹ԭ�� Sapphire, in which partners submitted more than 680 agents, �鶹ԭ�� is inviting partners to join the next chapter of the program. Partner agent race to �鶹ԭ�� TechEd spotlights enterprise-grade, secure, scalable, production‑deployed AI agents in live environments, built on �鶹ԭ�� Business AI Platform.

For the partner agent race to �鶹ԭ�� TechEd, agents must be:

• Developed with Joule Studio and deployed to �鶹ԭ�� Business AI Platform runtime
• Deployed on �鶹ԭ�� Business AI Platform using �鶹ԭ�� Cloud SDK for AI and AI Foundation

Extensions of �鶹ԭ��-delivered agents must also be created with Joule Studio, and agents that only integrate via direct APIs or integration services for �鶹ԭ�� BTP are out of scope for this project. �鶹ԭ�� encourages partners to begin preparing eligible agents as soon as the timeline, evaluation criteria, and other details are released in the coming weeks.

End-to-end partner enablement strategy

�鶹ԭ�� is introducing a structured enablement path that takes partners from awareness to action. �鶹ԭ�� has combined large-scale enablement and market recognition programs to scale the partner ecosystem for the Autonomous Enterprise and �鶹ԭ�� Business AI Platform.

The enablement plan includes a deep-dive curriculum for sales, presales, consultants, and developers. Partners can take advantage of hands-on workshops, regional innovation days in priority markets, and Hack2Build sprints focused on agent-based use cases. Dedicated Autonomous Enterprise and �鶹ԭ�� Business AI Platform pages on���鶹ԭ�� Partner Portal provide all the information partners need for success, regardless of where they are in their AI journey.

�鶹ԭ�� will deepen this enablement strategy with the upcoming��“AI era powered by the Autonomous Enterprise” learning, covering �鶹ԭ�� Business AI Platform, Joule Studio, and more for learners who want hands-on platform experience. �鶹ԭ����will also host live webinars connecting partners directly to the Autonomous Enterprise narrative, platform strategy, and key commercial updates. Partners can find additional curated learning and enablement content on the .

A soundtrack for the future, a symphony of success

Closing out our keynote for Partner Summit at �鶹ԭ�� Sapphire in Orlando, we underscored how critical our partners are to this moment.

Our focus is to enable partners to adopt and extend the Autonomous Enterprise and �鶹ԭ�� Business AI Platform, accelerating ecosystem‑led growth in support of �鶹ԭ��’s AI‑first strategy. Our goal is ambitious: We want to see every �鶹ԭ�� customer enjoy an AI experience with �鶹ԭ�� in the next year. Let’s get them on the cloud and toward our vision.

Together, we’ll keep pushing the tempo, layering innovation, and building the soundtrack for the Autonomous Enterprise, ultimately creating a symphony of success for our customers.

Karl Fahrbach is chief partner officer of �鶹ԭ��.

The autonomous enterprise reflects a fundamental shift in how organizations operate using real‑time intelligence to guide decisions, orchestrate processes end to end, and continuously adapt as conditions change. AI becomes embedded into the fabric of the enterprise, helping every function operate with greater speed, resilience, and confidence.

The foundation of the autonomous enterprise is the �鶹ԭ�� Business AI Platform, which infuses AI with the process knowledge, data, and governance organizations depend on. 

Business Transformation Management solutions from �鶹ԭ�� help power the �鶹ԭ�� Business AI Platform by bringing together insights and enterprise knowledge that have long been fragmented and isolated in silos.

Business Transformation Management solutions from �鶹ԭ�� help deliver the promise of the autonomous suite. Here’s how.

�鶹ԭ�� Agent Hub: Command center for agentic governance

Now available, the helps organizations discover, inventory, govern, and evaluate AI agents across the enterprise landscape. In fact, it’s already being used by 150 companies with over 100, 000 agents under management. �鶹ԭ�� AI Agent Hub acts a system of records for all AI agents, large language models (LLMs), and Model Context Protocols (MCP) servers.

In the context of �鶹ԭ�� Business AI platform, �鶹ԭ�� AI Agent Hub underpins the governance pillar, ensuring organizations can deploy and manage AI agents safely and at scale.

In addition to the enterprise architecture context that �鶹ԭ�� LeanIX provides, along with an giving agents access to architecture data, �鶹ԭ�� AI Agent Hub enables enterprise architects to apply proven governance practices, such as mapping to business capabilities, to the entire agentic landscape. The addition of agent mining capabilities supported by �鶹ԭ�� Signavio provides visibility into the behavior of AI agents, their conformance with policies, and their business impact.

From the standpoint of the Autonomous Enterprise, the insight the hub provides is not only necessary, it’s critical.

New AI capabilities

The new Enterprise Architecture Assistant from �鶹ԭ�� LeanIX is supported by several new agents, including two highlighted here. The Enterprise Content Research Agent draws on internal business content to enrich architecture data, while the Enterprise Architecture Web Research Agent scans the web for relevant vendor and application information.

These enhancements are part of a broader set of AI capabilities in �鶹ԭ�� LeanIX. The solution now makes it easier to create surveys, automate tasks, perform calculations, and plan target architectures. In addition, significantly improved semantic search enables Claude, AI co‑pilots, and other agents to seamlessly access and work with enterprise architecture data.

In �鶹ԭ�� Signavio Process Transformation Suite, we redesigned �鶹ԭ�� Signavio Process Modeler with an AI-first architecture, modernized user experience and deeper integration with �鶹ԭ�� Autonomous Suite. �鶹ԭ�� Signavio also introduced the Process Transformation Assistant to enable business users to conduct sophisticated process analysis through natural language prompts. The assistant can identify high-impact opportunities for agent deployment, accelerating the time from question to decision and providing context-aware process insights to anyone.

Looking ahead to a new paradigm

Despite the rapid pace of change brought about by agentic AI, we are still in the early days of this technological revolution. To succeed and continue to ride the wave of innovation, companies need to aggregate and organize their procedural knowledge about how they operate.  This knowledge is often fragmented across many structured and unstructured sources—such as process models, application logic, documents, and chats—to create a coherent view of how the business s runs.

This foundation enables agents to understand and act within the business context. In turn, agents will continuously contribute back, enriching and evolving this knowledge repository over time.

At �鶹ԭ�� Signavio we call this storehouse “company memory.” Company memory, comprised in part of process atoms, captures all the knowledge of operational practices, business rules, preferences, and more so that it can be accessed by agents as needed to check conformance and change behavior.

To enable the Autonomous Enterprise, you need to capture the tribal wisdom and unstructured knowledge your company depends on to operate today. That is what process atoms and a centralized company memory, accessed and updated by agents, do for you. In the future, it’s hard to imagine how any enterprise will succeed without the context, learning, and guidance that company memory delivers.

Business transformation never stops

As our research has shown, . That’s why you need a capability in place that allows for planning, managing, and realizing value from every transformation you undertake.

This year at �鶹ԭ�� Sapphire , we talked about all the ways our solutions support this capability as well as all the ways our solutions continue to evolve in the era of the autonomous enterprise, allowing you to adapt, innovate, and thrive into the future.

Get started today

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Andre Wenz is chief product officer of �鶹ԭ�� Signavio.
Dominik Rose is chief product officer of �鶹ԭ�� LeanIX.

�鶹ԭ�� Business Data Cloud (�鶹ԭ�� BDC) is the data foundation of that platform, the business data fabric that anchors universal business context, serving as the trusted knowledge core��for every enterprise application and agent.��

The future of agentic organizations will be driven by AI with the deepest organizational knowledge. That future doesn’t start with AI models; it starts with whether your data foundation can give agents the business context they need to act autonomously. 

Today, we are introducing innovations that move organizations closer to becoming an autonomous enterprise.

Turn all your data into business outcomes 

A business data fabric architecture ensures every agent, application, and decision draws from the same trusted business context. And today, we are introducing new business data fabric capabilities that bring multi-model, unified master data, and embedded governance to your agentic foundation. 

• �鶹ԭ�� HANA Cloud natively available in �鶹ԭ�� Business Data Cloud:���鶹ԭ�� HANA Cloud��is��now a��core��component of �鶹ԭ�� Business Data Cloud.��As the AI database��for �鶹ԭ�� BDC,���鶹ԭ����HANA Cloud provides a��unified��in-memory engine��for agents to reason across transactional, analytical, and multi-model workloads��such as spatial, graph, and vector.��In practice, this means agents can navigate relationships across customers and suppliers, analyze geographic dependencies, or perform semantic search in real time.��And because every workload runs on a single in-memory engine with native workload management, inference time drops dramatically, lowering TCO and improving the predictability of AI��costs.��With �鶹ԭ�� HANA Cloud, �鶹ԭ�� Databricks, and �鶹ԭ�� Snowflake, �鶹ԭ�� Business Data Cloud delivers��intelligent compute for��every data and AI workload.
• Reltio in �鶹ԭ�� Business Data Cloud: With the completed acquisition of Reltio, �鶹ԭ�� is bringing multi-domain master data management capabilities directly into �鶹ԭ�� Business Data Cloud, helping customers unify, cleanse, and harmonize data across �鶹ԭ�� and third-party��sources. Reltio’s AI-based entity resolution identifies and merges related records��into a single, consistent view of business entities.��Low-latency delivery and Model Context Protocol support enable real-time, multi-agent workflows across��your data landscape: a procurement agent, for example, can assess supplier risk and trigger action almost instantly using trusted, real-time data. Together, this becomes a golden record system of context that Joule Agents use to deliver faster time-to-value for business AI.
• �鶹ԭ�� Master Data Governance natively available��in���鶹ԭ�� Business Data Cloud:��Unified master data is only as valuable as the governance applied to it. To ensure data is AI-ready, governance must��shift��from regulator to value accelerator. �鶹ԭ�� Master Data Governance is now a core component of �鶹ԭ�� Business Data Cloud, governing master data and policies across��your��business data fabric.��This results in��embedded��AI governance that accelerates agent deployment, ensuring every agent operates on data��products��that��are��verified��and aligned to your business policies.��
• �鶹ԭ�� AI Core integration with �鶹ԭ�� Business Data Cloud: �鶹ԭ�� is introducing deeper integration between �鶹ԭ�� Business Data Cloud and �鶹ԭ�� AI Core, enabling AI models to be grounded directly in trusted business data, semantics, and governance. Batch inference can now be embedded into business-ready data products, continuously enriching the data that powers Joule with predictions, classification, and��AI��outputs.����

“This is where �鶹ԭ�� Business Data Cloud fits into the vision: not as a centralized system, but as an enabler of cultural change through its unique capabilities. These capabilities allow teams to preserve mission-critical business context across financial and non-financial data.”

Jannie Affeld, VP Finance Systems and ERP, Google 

Transform outcomes with Joule Agents 

�鶹ԭ�� is bringing agentic AI directly into the business data fabric through Joule Agents, introducing new capabilities that streamline data management, analytics, and planning through a conversational experience: 

• Data product search and creation: Joule Agents simplify how users discover and create data products. With natural language prompts, users can identify relevant �鶹ԭ�� and third-party data sources, perform joins and transformations automatically, and apply business context and governance policies.  
• Automated planning and analytical modeling: Joule Agents enable data modelers and planning teams to generate analytical and planning models using AI. By defining dimensions, granularity, and data sources, users can automatically create models aligned with best practices. Teams can also initiate planning cycles, manage versions, and apply calculations without deep technical expertise. 
• Easily��surface business��insights:��Business users��can��ask complex analytical questions in natural language and receive context-aware insights across lines of business. Powered by governed data products��in �鶹ԭ�� Business Data Cloud and �鶹ԭ�� Knowledge Graph,��Joule��understands relationships, processes, and business logic��to deliver��more accurate and complete answers without requiring manual exploration.
• �鶹ԭ�� Analytics Cloud story generation: Joule accelerates �鶹ԭ�� Analytics Cloud story creation by transforming data models, queries, and business context into dashboards and visualizations automatically. Users can continue the conversation, drilling into KPIs, identifying drivers, and exploring trends in a single workflow. 

Extend context across your open data ecosystem

Last year, we introduced �鶹ԭ�� BDC Connect, a capability to share data and metadata with zero copies, preserving meaning across every cloud and platform. We are excited to announce �鶹ԭ�� BDC Connect for Amazon Athena, continuing our promise of openness and choice.

This enables �鶹ԭ�� data products to be discovered and consumed directly within AWS without replication or loss of context. As a result, teams can build analytics, applications, and AI agents faster while ensuring they operate on trusted, governed business data.

Together with existing partners across Snowflake, Databricks, Google BigQuery, and Microsoft Fabric, �鶹ԭ�� Business Data Cloud delivers a connected, open data ecosystem so organizations can extend business context across their entire landscape with zero copies. 

General availability is planned for H2 2026.

“Compute can happen anywhere, data can stay at the source when needed, but business context is managed once, centrally, in �鶹ԭ�� Business Data Cloud.”

Malin Persson, CIO at Ericsson

Get started today 

Build your trusted foundation for agentic AI with �鶹ԭ�� Business Data Cloud.  

Irfan Khan is president and chief product officer of �鶹ԭ�� Data & Analytics.

From application development to automation, integration, and now agentic AI, we have pushed forward so organizations can move faster, solve bigger challenges, and create with confidence.

At �鶹ԭ�� Sapphire, we’re taking a giant step forward in making that mission a reality.

I’m thrilled to announce Joule Studio, a bold new, fully managed offering that empowers enterprises to build and manage the full life cycle of AI agents, applications, and workflows. Joule Studio brings �鶹ԭ�� Business AI Platform to life, empowering organizations to build agents that are natively grounded in live business data, end-to-end processes, and rich business semantics that already exist across your �鶹ԭ�� landscape.

Let’s look at what users can accomplish with Joule Studio.

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Build faster with intent-based development

To connect business needs and technical execution, we’ve placed intent-based development capabilities at the heart of the Joule Studio experience. Users can simply describe their goals in natural language, enabling anyone in the business to quickly create an automated solution or digital assistant.

When triggered, Joule Studio:

• Sets the business context for user’s request with �鶹ԭ�� Signavio Process Consultant Agent, �鶹ԭ�� Knowledge Graph, and �鶹ԭ�� Domain Models.
• Understands the customer landscape with �鶹ԭ�� LeanIX, including third-party solutions.
• Generates a complete, structured flow of artifacts, including a product requirements document that captures the business outcome, technical specifications with implementation-ready details, code scaffolding, test artifacts, and a live working preview.
• Creates a highly traceable flow from idea to implementation, ensuring a direct, seamless handoff from business users to developers. It fundamentally shifts enterprise agentic development from a slow, manual translation of requirements into a rapid, structured, and �鶹ԭ��-aligned workflow.

“Joule Studio generated an end-to-end solution in 10 to 15 minutes, replacing three to four days of manual development and coordination.”

Vanitha Ponnusamy, Sony

Develop agentic solutions your preferred way

Joule Studio pairs the simplicity of intent-based capabilities with unprecedented openness, providing developers with the freedom to create agentic solutions their way, using their preferred frameworks and tools without being locked into a single approach.

For example, developers can deepen and adapt Joule Studio-generated solutions using the tools and agentic IDEs they already know and love, such as Visual Studio Code, Cursor, and others. Additionally, Joule Studio offers new pro-code capabilities that support frameworks such as LangChain, Pydantic AI, and LlamaIndex, as well as an embedded n8n environment for visual multi-agent orchestration.

Harness best-in-class partnerships: n8n and Vercel

To build truly transformative AI solutions, developers need the freedom to use the tools they already love. That is why we are thrilled to announce new embedded partnerships with Vercel and n8n, giving Joule Studio users the ultimate flexibility to orchestrate complex workflows and build stunning user experiences—all without sacrificing �鶹ԭ��’s enterprise-grade security and governance.

Vercel for blazing-fast, custom digital experiences

While �鶹ԭ��-oriented frameworks like UI5 and �鶹ԭ�� Fiori remain the gold standard for enterprise consistency, our new partnership with Vercel gives developers unparalleled choice for custom frontend design. By leveraging Vercel within the �鶹ԭ�� ecosystem, developers can rapidly build highly flexible, custom web interfaces for their AI agents using popular frameworks like Next.js. This enables teams to deliver lightning-fast, consumer-grade digital experiences that prioritize speed and custom design, while securely preserving �鶹ԭ�� enterprise controls.

n8n for visual workflow orchestration at enterprise scale

Creating intelligent agents is just the beginning; integrating them into end-to-end business processes is where the real value is unlocked. We are bringing an embedded, fully managed n8n environment directly into Joule Studio. By using n8n within Joule Studio, teams can visually orchestrate multi-agent systems and bring AI right into the process flows they are designed to support, ensuring agents act with perfect timing and context. Developers get the beloved n8n experience they already know, complemented by seamless access to �鶹ԭ�� systems, Joule Studio capabilities, and �鶹ԭ��-managed services for identity and operations. It is the ultimate combination for delivering powerful, enterprise-ready automations faster than ever.

Deploy enterprise-ready agents securely

Building powerful agents is only half the equation; realizing their full value comes from running them securely and reliably at enterprise scale. To help our customers do this, �鶹ԭ�� is introducing a managed Joule Studio runtime service that enables organizations to deploy agents, applications, and workflows in a secure, production-ready environment with zero infrastructure management required.

Joule Studio runtime does the heavy lifting for our customers by managing all the complex operational capabilities needed for enterprise scale; runtime configuration, cluster management, storage, and model access are delivered seamlessly out-of-the-box. Underpinning this runtime is also the NVIDIA OpenShell, which places each agent inside an isolated, sandboxed environment with configurable policies and guardrails — ensuring agents can operate autonomously while staying within defined boundaries and preventing unchecked access to sensitive enterprise systems.

This governed foundation provides IT teams with built-in observability and lifecycle management. With controlled deployments, standardized schema validation, and deep integration with �鶹ԭ�� Business Transformation Management solutions like �鶹ԭ�� Signavio and �鶹ԭ�� LeanIX as well as �鶹ԭ�� Cloud Application Lifecycle Management allow teams to monitor agent usage, costs, and business impact over time. It creates an always-on cycle of continuous improvement, where AI monitors performance, surfaces insights, and proposes the next round of fixes.

Agents deployed on Joule Studio runtime will be equipped with persistent, long-term memory powered by �鶹ԭ�� HANA Cloud, enabling them to retrieve user preferences and context across multiple sessions.

Bring agents into the flow of everyday work

Ultimately, the value of agentic AI is realized when people can effortlessly interact with it. With the new Joule Work engagement layer, we are bringing the apps, agents, and workflows your teams build directly into the flow of everyday work, providing a personalized, intent-based workspace that reduces context switching and accelerates task completion.

“Across 48 diverse scenarios, Joule Studio consistently delivered high-quality code, with only a handful of instances requiring minor refinements to reach full functionality.”

Suraj Gahalyan, Accenture

Joule Studio: �鶹ԭ�� Business AI Platform in action

Joule Studio is more than just a powerful development environment; it is the ultimate expression of the unified coming together. While the broader market struggles with disconnected point solutions that lack business context and keep AI stuck in endless pilot modes, �鶹ԭ�� Business AI Platform bridges every system, process, and decision to deliver true enterprise-wide value.

Joule Studio acts as the engine that brings the three foundational pillars of the �鶹ԭ�� Business AI Platform to life in one seamless workflow:

• Build: We are taking organizations from idea to enterprise impact by providing a unified workspace that enables the seamless creation of agents, applications, and workflows. Whether leveraging intent-based development or our embedded partnerships with n8n and Vercel, teams can turn ideas into solutions without operational overhead.
• Contextualize and reason: An agent is only as smart as the data it understands. Through deep integration with the �鶹ԭ�� Knowledge Graph, �鶹ԭ�� Business Data Cloud, and �鶹ԭ�� Domain Models, every solution built in Joule Studio is natively anchored in universal business context. This means agents reason over real, semantically rich business data, understanding relationships and process logic, for reliable performance from day one.
• Govern: Speed and control are no longer a tradeoff. By tapping into �鶹ԭ�� AI Agent Hub, fully managed Joule runtime, and solutions like �鶹ԭ�� Signavio and �鶹ԭ�� LeanIX, Joule Studio embeds enterprise-grade governance, observability, and lifecycle management directly into the development process.

By unifying these capabilities, Joule Studio allows your best people to do their best work. It eliminates integration complexity and fragmented security, empowering your organization to transition from isolated AI experiments into a secure, autonomous enterprise.

Get started today

Joule Studio is ushering in a new era of enterprise-grade agentic development. While the rest of the market struggles to bridge the gap between basic LLMs and real-world business execution, Joule Studio delivers a definitive advantage: agents, applications, and workflows that are natively grounded in �鶹ԭ�� live data, processes, and business semantics.

I am pleased to share that now through the end of 2026, �鶹ԭ�� customers and partners can receive free design-time access, including AI-assisted development capabilities under fair-use limits. This is your opportunity to redefine how your business operates and turn your existing �鶹ԭ�� landscape into an unparalleled AI engine. Equip your teams to build with speed and confidence today.

• Learn more at

We cannot wait to see the incredible agentic solutions your teams will bring to life!

Michael Ameling is president of �鶹ԭ�� Business Technology Platform and a member of the Extended Board of �鶹ԭ�� SE.

Employees at , a global fashion retailer with tens of thousands of employees, had to navigate multiple systems to piece together data across sales and procurement. Answering a single question could take up to 10 minutes.

Today, they just ask Joule. What used to take 10 minutes now takes about three seconds, driving a 70% increase in operational efficiency and a 50% reduction in manual errors.

Using capabilities in , LC Waikiki partnered with �鶹ԭ�� and to build a custom AI-driven experience that dynamically interprets user requests, applies role-based context, performs the necessary queries, and connects data across systems to present a complete view in one place. It then links people directly to the relevant transaction.

At �鶹ԭ��, stories like these inspire our vision for the enterprise in which AI transforms how people and processes work—one where people set the direction and AI executes. We call it the the Autonomous Enterprise.

In the Autonomous Enterprise, decisions are grounded in real-time intelligence, workflows are automated end-to-end, and AI proactively improves every function while empowering people to do their best work.

The Autonomous Enterprise also provides fully governed AI you can trust, so you can achieve more. Making this a reality for companies is critical because AI is now essential to how all work gets done. It is increasingly involved in decisions that carry financial, operational, and regulatory consequences.

Joule: One place to direct the entire business

In the Autonomous Enterprise, Joule Work, announced at �鶹ԭ�� Sapphire, is the next step in the evolution of how people engage with and execute end-to-end business processes. Joule Work is a dynamic workspace that adapts to intent, keeps people focused on outcomes, and delegates execution to AI.

Through Joule Work, you can say goodbye to manually coordinating work across multiple applications and interfaces. Instead, tell Joule what you want to accomplish. Joule Assistants with role and process context will coordinate teams of Joule Agents to surface the right insights and automate routine work across departments and systems. Rather than static, disjointed systems, you get workspaces that pull together information and menus from various systems that fit your specific needs, in real time.

Joule Work is available now to customers in the �鶹ԭ�� Early Adopter Care program. �鶹ԭ�� Early Adopter Care program for the Joule Work desktop app is planned for Q2 2026; general availability for both is planned for H2 2026. The Joule Work mobile app is generally available now.

We also announced that Joule’s bi-directional Agent-to-Agent (A2A) capabilities will be generally available in Q4, enabling third-party agents to securely call on Joule Agents and act within enterprise processes, extending interoperability in both directions across �鶹ԭ�� and non-�鶹ԭ�� environments. Agents built in Joule Studio will natively support A2A protocols, enabling interoperability and scalability for multi-agent execution.

�鶹ԭ�� Autonomous Suite: The operational core of the modern enterprise

While Joule Work empowers every individual to do their best work and expand their impact, the �鶹ԭ�� Autonomous Suite transforms how entire business functions, or “autonomous domains,” work.

�鶹ԭ�� Autonomous Suite spans five domains: finance, spend, supply chain, human capital management, and customer experience. These domains will operate as a single system, so workflows and agents run across functions without fragmenting into separate tools, separate data, or separate decisions. This approach allows AI recommendations to reflect your full operating reality.

With �鶹ԭ��’s integrated suite of business applications and industry-leading business data, AI in the Autonomous Enterprise is grounded in the specifics of how key business functions actually work. This foundational context for transformative AI outcomes is where �鶹ԭ��’s unique experience comes in. For decades, we have been trusted to run our customers’ most important functions. �鶹ԭ�� Autonomous Suite infuses our deep knowledge of business processes into your AI, along with the data context and operational guardrails it needs to be truly effective and reliable at enterprise scale.

Each organization is also unique. Over time, your business has defined how your work gets done. These are the rules, workflows, and how systems respond when something unexpected happens, like a failed transaction, so processes don’t break. In the Autonomous Enterprise, AI delivers its greatest value by respecting these boundaries, turning your unique ways of working into a true advantage.

At �鶹ԭ�� Sapphire, we announced new Joule Assistants and Joule Agents, spanning the domains of the Autonomous Enterprise, to help organizations move from managing work to directing outcomes. These new assistants and agents will roll out through the end of this year.

�鶹ԭ�� Business AI Platform: The foundation of the Autonomous Enterprise

The �鶹ԭ�� Business AI Platform turns the vision of human-led, AI-driven business operations into something enterprises can build and run. It enables them to move from AI experimentation to execution by grounding agents and applications in real business context that governs it all at enterprise scale.

At the center is , a fully managed environment that empowers enterprises to build and manage the full lifecycle of AI agents, applications, extensions, and workflows. Intent-based development capabilities allow people to describe what they need in natural language. A Joule Agent then generates structured requirements, specifications, code, and test artifacts grounded in �鶹ԭ�� process and data context.

Developers can work within the tools they already use, including VS Code and MCP-enabled toolchains, and choose their preferred agent frameworks, such as , , and .

Through deep integration with the , —and the new �鶹ԭ�� Domain Models trained on �鶹ԭ�� code, customer data, metadata, and business processes—Joule Agents reason over real, semantically rich enterprise data rather than generic knowledge. �鶹ԭ�� Domain Models are available through the �鶹ԭ�� Early Adopter Care program, with general availability planned for Q3 2026.

Speed and governance, no longer a tradeoff, are built into the �鶹ԭ�� Business AI Platform. At �鶹ԭ��, we believe that corporate governance—including approval flows, compliance processes, identity management, and the ability to audit decision-making—must carry into how AI is deployed, updated, and scaled. Joule Studio runtime provides a secure, production-ready, fully managed environment for deploying agents, helping organizations meet compliance standards while reducing infrastructure complexity.

An enhanced �鶹ԭ�� AI Agent Hub also provides a vendor-agnostic command center to discover, inventory, and govern �鶹ԭ�� and non-�鶹ԭ�� AI agents and MCP servers across the enterprise. Integration with and further embeds governance and architecture transparency into the development process.

The �鶹ԭ�� AI Agent Hub leverages enterprise-wide process intelligence to continuously track where AI agents are creating value and can proactively surface where they can deliver even more, because we believe AI needs to remain accountable for outcomes in addition to uptime. �鶹ԭ�� AI Agent Hub is generally available, with additional capabilities rolling out through 2026. See release timelines in the .

Empowering everyone to solve business challenges with AI

We are making the Autonomous Enterprise a reality because at �鶹ԭ��, we believe that companies of all sizes need far more than marginally better AI models or the latest bolt-on solutions. They deserve AI-driven outcomes that increase innovation, revenue, and margins.

The Autonomous Enterprise is what brings our vision to life: AI grounded in your data, connected across your most important processes, and governed to fit how your business runs.

Brenda Bown is chief marketing officer for �鶹ԭ�� Business AI.

The company introduces a unified �鶹ԭ�� Business AI Platform, deepening partnerships with Anthropic, Amazon Web Services, Google Cloud, Microsoft, NVIDIA and Palantir

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

“For the mission-critical processes of our customers, ‘almost right’ just isn’t good enough,” said Christian Klein, CEO of �鶹ԭ�� SE. “By uniting �鶹ԭ�� Business AI Platform with �鶹ԭ�� Autonomous Suite, we anchor AI agents in the business processes, data and governance so they can deliver accurate, compliant and secure outcomes, unlocking new sources of revenue and meaningful cost savings.”

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

Introducing �鶹ԭ�� Business AI Platform

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

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

Deploying �鶹ԭ�� Autonomous Suite Across Every Business Function and Industry

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

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

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

Designing the Autonomous User Experience

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

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

Accelerating the Customer Journey Toward Autonomy with €100 Million Infusion

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

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

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

Lastly, �鶹ԭ�� announced a full slate of strategic partnerships across each category:

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

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About �鶹ԭ��

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

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�鶹ԭ�� and Anthropic today announced plans to expand their collaboration to deliver advanced AI solutions to enterprise customers, making Claude, Anthropic’s AI model, a primary reasoning and agentic capability embedded across �鶹ԭ��’s AI-enabled solution portfolio, powered by Joule and Joule agents.  

Unveiled today at �鶹ԭ�� Sapphire, Anthropic and �鶹ԭ�� will collaborate to embed Claude’s agentic capabilities into the newly announced �鶹ԭ�� Business AI Platform to advance �鶹ԭ��’s vision of the Autonomous Enterprise in the agentic AI era.

The collaboration builds on �鶹ԭ��’s more than 50-years of business application know-how across processes, data, and governance. This complements �鶹ԭ��’s open ecosystem approach to supporting any model and provides greater customer choice and flexibility to meet evolving AI requirements. 

Connecting directly to �鶹ԭ�� Business AI Platform, Claude will empower agents to carry ​out tasks—from closing the books at quarter-end and answering complex employee leave questions to rerouting supplier orders mid-shipment—coordinating across �鶹ԭ�� S/4HANA, �鶹ԭ�� SuccessFactors and �鶹ԭ�� Ariba solutions, and other systems via MCP.

“Our open platform means we’re tightly integrated with world-leading companies across our portfolio. Together with Anthropic, we’re building something uniquely valuable for our customers,” said Christian Klein, CEO of �鶹ԭ�� SE. “The Autonomous Enterprise requires AI that understands business context and acts within the controls organizations depend on, and our partnership with Claude plays a key role in this.”

“We built Claude to support the work that helps businesses run: closing the books, rerouting delayed orders, or approving expenses, to name a few. With Claude on �鶹ԭ�� Business AI Platform, that work happens inside the systems enterprises have already invested in, with the trust and governance �鶹ԭ�� customers rely on,” Daniela Amodei, co-founder and president of Anthropic, said.

Claude brings additional agentic capabilities and connectivity to Joule

Joule from �鶹ԭ�� is an AI-enabled business assistant that helps teams make faster, smarter decisions by embedding contextual, more secure AI directly into �鶹ԭ�� and non-�鶹ԭ�� business workflows. Now, �鶹ԭ�� is expanding Claude’s capabilities to Joule with plans to integrate Anthropic’s advanced agentic AI capabilities across the newly announced �鶹ԭ�� Business AI Platform.

With a deeper use of Claude and access to Anthropic’s frontier models, �鶹ԭ�� customers can expect additional capabilities, such as:

• Better reasoning on complex business tasks: Claude will empower agents to take real action for hundreds of thousands of �鶹ԭ�� customers, across finance, ​​HR, procurement, and supply chain. Agents leveraging Claude connect to �鶹ԭ�� Business AI Platform to understand business context grounded in �鶹ԭ�� data, make ​​more accurate decisions, and operate safely within defined processes. For example, a Treasury Manager can ask Joule to prepare a CFO briefing for a bank meeting, and within minutes receive a completed presentation populated with live data and analysis as well as flagged financial risks. Work that previously took hours of manual effort now takes minutes. 
• Agentic AI that understands business context: Claude works with business context from across �鶹ԭ��’s enterprise systems and other tools connected through MCP. It takes action step by step: looking up data, making updates, triggering approvals, moving a task forward. Anthropic and �鶹ԭ�� will work strategically to build custom agents and agentic workflows in �鶹ԭ��—optimizing for key industries such as public sector, healthcare, education, life sciences and utilities. This combines �鶹ԭ��’s expertise in enterprise applications and AI with Claude’s reasoning and agentic capabilities.

Bringing AI into the systems enterprises already trust

As AI moves from advising to acting, trust is critical, especially in the enterprise and in regulated industries. Anthropic is bringing safe, reliable AI into processes that enterprises already trust. When AI adjusts an order, triggers a workflow, or makes a recommendation inside an �鶹ԭ�� customer’s environment, it does so within the same controls that govern human decisions: the approvals, policies, and compliance frameworks already wired into �鶹ԭ�� solutions.

Together, Anthropic and �鶹ԭ�� plan on bringing this model to life by combining Claude with �鶹ԭ��’s depth and scale, helping organizations move from experimentation into the core of how their organizations operate.

Philipp Herzig is CTO and a member of the Extended Board of �鶹ԭ�� SE.

Building on their long-standing partnership, AWS and �鶹ԭ�� are making it easier for customers to access mission-critical �鶹ԭ�� data products across AWS services, including Amazon Bedrock, Amazon Quick, and Amazon SageMaker. This will allow teams to deliver self-service analytics and build AI agents across all lines of business—without waiting for IT teams to replicate, prepare, and provision �鶹ԭ�� data. 

“The next era of business will be defined by how well organizations turn intelligence into action at scale,” said Muhammad Alam, member of the Executive Board of �鶹ԭ�� SE, �鶹ԭ�� Product & Engineering. “By bringing together �鶹ԭ�� Business Data Cloud and widely adopted AWS AI and analytics capabilities, customers can unlock the true potential of data and AI.” 

Enabled by �鶹ԭ�� BDC Connect, the integration delivers near real-time, zero-copy access to semantically rich �鶹ԭ�� data products directly through Amazon Athena, keeping data in place, preserving its original business context, and eliminating replication delays. Customers can query and analyze this data immediately, or choose to store and transform it for use across the broader AWS environment. This gives teams a governed, secure environment within AWS to easily build reports, dashboards, and AI agents.

“�鶹ԭ�� and AWS share a commitment to helping customers put their most valuable data to work,” said Ruba Borno, vice president of Global Specialists and Partners at AWS. “By combining �鶹ԭ�� Business Data Cloud with the AWSsecure, global infrastructure and advanced AI services, organizations can unlock mission-critical �鶹ԭ�� data and act on it at the speed and scale their business demands.” 

With �鶹ԭ�� BDC Connect for Amazon Athena customers can: 

• Create a single, trusted foundation for all their business data, �鶹ԭ�� and beyond 
• Get AI up and running faster with business data that is ready to use 
• Build intelligent applications and agents powered by the business data that matters most 
• Fast-track insights and innovation with self-service analytics that reduce time-to-insight from weeks to hours 

General availability

�鶹ԭ�� Business Data Cloud is already available on AWS in the U.S. East (N. Virginia), Europe (Frankfurt), Asia Pacific (Tokyo), Canada (Central), Asia Pacific (Sydney), South America (São Paulo), Asia Pacific (Seoul), Asia Pacific (Singapore) Regions, and the AWS European Sovereign Cloud. 

Partnership opens new pathways for enterprise data migration with �鶹ԭ�� AI-supported tooling complemented by Palantir’s AIP for data migration scenarios to simplify an expedite digital transformation for �鶹ԭ�� customers, with Accenture as a co-innovation partner for joint customers

This year at �鶹ԭ�� Sapphire, �鶹ԭ�� and Palantir announced an expansion of their strategic partnership focused on delivering new data migration capabilities designed to help enterprise customers succeed in the AI era and realize �鶹ԭ��’s vision of the Autonomous Enterprise.

The enhanced partnership is designed to facilitate joint customers’ cloud migrations, with the most complex data migration scenarios moving quickly, securely, and confidently through their business transformation journeys.

AI embedded across the migration life cycle

The expanded partnership builds on �鶹ԭ��’s broader agentic migration strategy, uniting �鶹ԭ��’s deep expertise in enterprise applications and �鶹ԭ�� Business AI with Palantir’s AIP to deliver AI-driven data migration capabilities that accelerate timelines, secure cost efficiencies, and fundamentally transform how organizations operate. �鶹ԭ�� customers can now leverage Palantir’s AIP for data migration scenarios alongside the agent-led toolchain from �鶹ԭ��, which includes business transformation tools and the new migration and modernization assistants to accelerate their transformations to �鶹ԭ�� Cloud ERP.

“To turn the vision of the Autonomous Enterprise into reality, organizations need trusted partners to help them transform their core operations and unlock the power of business data and AI,” said Christian Klein, CEO of �鶹ԭ�� SE. “Together with Palantir, we are enabling customers to move to the cloud with speed and confidence through complementary capabilities that accelerate innovation across the enterprise.” 

“We are proud to partner with �鶹ԭ�� and Accenture to bring the power of advanced AI and data migration to the world’s most important operations. This partnership is designed to help customers realize the full value of their data, accelerate cloud migrations and AI adoption, and build more resilient and efficient operations,” said Alex Karp, co-founder and CEO of Palantir Technologies. 

Accenture as global strategic services partner

Accenture plays a key role in bringing this joint effort to life as the first global strategic services partner for this initiative, helping their clients translate these capabilities into large-scale business-led programs. Together, �鶹ԭ��, Palantir, and Accenture can help joint customers identify acceleration opportunities across �鶹ԭ�� and non-�鶹ԭ�� systems sooner, achieve faster time-to-value, and drive continuous innovation by fundamentally redefining the approach to �鶹ԭ�� Cloud ERP migrations.

By embracing AI from day one, organizations can automate migration analysis, planning, remediation, testing, and impact assessment—moving from tracking project timelines to creating measurable business value at every stage. 

“In today’s world, speed to value is critical for our clients,” said Julie Sweet, chair and CEO of Accenture. “We are excited to co-innovate with �鶹ԭ�� and Palantir to help our clients accelerate their journey to ERP modernization with �鶹ԭ��, which is the foundation for reinventing core operations and using AI to achieve new performance frontiers.” 

New �鶹ԭ��-validated deployment options

�鶹ԭ�� is making Palantir AIP for data migrations scenarios available as an �鶹ԭ�� Endorsed App on the �鶹ԭ�� Store, and soon as an �鶹ԭ�� Solution Extension, establishing a trusted, �鶹ԭ��-validated path for accelerating complex data migrations, including migrations to �鶹ԭ�� Cloud ERP. The new �鶹ԭ�� Solution Extension unites �鶹ԭ��’s deep expertise in mission-critical business processes and semantically rich data with Palantir AIP to securely accelerate data migrations for �鶹ԭ�� customers. With the new offering, customers can gain faster insights and more intelligent, data-driven business outcomes.

Together, are redefining �鶹ԭ�� data migrations, including ERP modernization through complementary solutions, transforming a traditionally complex migration process into an effort that enables faster value realization. 

Availability 

Palantir AIP for data migration scenarios is now available as an �鶹ԭ�� Endorsed App on the �鶹ԭ�� Store. The �鶹ԭ�� Solution Extension is planned to be generally available to �鶹ԭ�� customers in Q3 2026.

Jan Gilg is a member of the Extended Board of �鶹ԭ�� SE.

Held from April 20–24, Hannover Messe is the world’s leading industrial trade fair.

On day one, Christian Klein, CEO of �鶹ԭ�� SE, stopped by the �鶹ԭ�� booth before joining German Chancellor Friedrich Merz and other industrial leaders on the center stage to discuss the importance of moving from AI ambition to real-world execution.

And visitors to the �鶹ԭ�� booth experienced that shift firsthand, following the production of the ginger shot.

Packaged in a neat blue box, the ginger shot was refreshing but that wasn’t the only takeaway. The real takeaway was how �鶹ԭ��’s new set of AI-powered manufacturing and supply chain innovations can deliver connected .

Supply chain orchestration

From AI and data and then using �鶹ԭ��’s agentic AI, visitors saw what supply chain orchestration looks like in practice. �鶹ԭ�� uses , trusted data, and applications to help manufacturers��sense, analyze, and act in real time.

At the booth, visitors saw human operators interact with an ANYbotics robot through Joule using natural language to run live, remote field service inspections; Uhlmann’s high-tech glass-fronted packing machine, PacXplorer, in action opposite the CNC machine from DMG MORI that was creating spare parts for the PacXplorer; and, at end of the production cycle, AIMBO’s robot handling the picking and packing of the ginger shot. Both AIMBO and ANYbotics are part of �鶹ԭ��’s growing network of physical AI partnerships.

In addition to many tours held in German and English, day one also saw tours in Japanese, Chinese, and Portuguese—Brazil was the partner country at Hannover Messe 2026.

Equipped with headphones to block out the noise of the crowds at the booth, visitors heard how �鶹ԭ��’s AI can deliver trusted orchestration and smarter execution for and .

Live AI use cases demonstrate functions and benefits

Operations and insights use case

Here, visitors experienced �鶹ԭ��’s vision of supply chain orchestration. In this vision, supply chain orchestration acts as the nerve center of the enterprise. It uses external alerts such as natural disasters, port congestions, or supplier routes to optimize enterprise logistics and planning using agents.

Benefits can include faster response times with AI-assisted monitoring and automated alerts; improved decision-making with data-driven, operational decisions powered by integrated business AI capabilities; and seamless integration with end-to-end connectivity from supply chain planning through to manufacturing execution and quality control.

Top AI functions

• can assist with order release and real-time monitoring.
• A physical AI robot inspects hazards, analyzes inspection data, and identifies root causes.
• Supply optimization analysis helps summarize insights, analyze, and explain the time-series optimization planning run.

Smart production use case

DMG MORI demonstrated production at its CNC machine—as part of an end-to-end process—from engineering to planning to production.

As the white robotic arm of the CNC machine silently moved the pusher spare part��after the milling process, visitors learned about the benefits of integration, from design to tool management, CNC programs to as part of a seamless, integrated process. The production operator dashboard offers the operator on the machine AI capabilities and insights to operational and maintenance information.

The process then continues through to logistics execution with �鶹ԭ�� Logistics Management, which helps combine warehousing and transportation capabilities for smaller warehouses.�� This��features an AI-powered logistics assistant that can cut through the noise, automatically gathering, summarizing, and prioritizing critical shipment information. It can also provide real-time shipping prices, bringing to life trusted orchestration and smarter execution.

Top AI functions

• uses natural language to help streamline warehouse and transportation operations.
• can provide manufacturing information and support decision-making throughout the workflow.

Intelligent packaging use case

Uhlmann’s PacXplorer and �鶹ԭ�� highlighted a fully integrated, high-speed packaging line from �鶹ԭ�� S/4HANA, to �鶹ԭ�� Digital Manufacturing, down to Uhlmann’s automation layer to produce the packaged ginger shot. The ginger shots were moved away from the line by a mobile autonomous robot from Symovo. This use case showed visitors how �鶹ԭ�� supports regulated industries such as pharma and life sciences. ��

Highlighted benefits include increased operational speed with higher throughput thanks to decreased order processing time, built-in regulatory compliance, reduced manual intervention, inventory transparency, and data integrity across the entire production chain.

Top AI functions

• Condition monitoring-led services can enhance asset uptime and service efficiency by combining AI-driven insights and seamless collaboration across the service ecosystem.
• AI-empowered flow analysis enables quick process modeling and engineering optimization.
• Intelligent exception handling is embedded in agent-driven processes.
• Joule’s integrated AI agents can support decision-making throughout the workflow.
• Joule can help power order and line insights.

Humanoid use case

At the final stop before getting their ginger shots, visitors watched an intelligent humanoid robot perform physical tasks at the end of the packaging line, bridging the gap between digital planning and physical execution, highlighting �鶹ԭ��’s Project Embodied AI.

Benefits of humanoids include increased operational speed with higher throughput due to a decreased order processing time; increased business uptime and cost efficiency especially in areas dangerous or difficult for humans; inventory transparency with real-time data integrity across the warehouse; and physical-digital alignment eliminating misalignment between planning and execution.

Top AI functions

• Joule and Joule Studio can enable robots to understand the physical world, make autonomous decisions, and learn from their environment for smarter operations.

More than a quick refuel

At the end of their visit, visitors got so much more than a quick refuel to slake their thirst. Following the creation of the ginger shot from recipe development and planning to production with mixing, filling, and packing, visitors came away with a clear understanding of how �鶹ԭ�� is connecting insight to execution with trusted orchestration and smarter execution. And, it is this trusted orchestration and smarter execution that is building the resilience every manufacturer needs in today’s world.

To succeed, manufacturers need more than incremental improvements or siloed optimizations. They need to orchestrate their operations end to end with connected processes and trusted data, so they can respond faster to change, operate more efficiently, remain compliant, and continue to grow—even as disruption is constant.

At Hannover Messe 2026, the world’s leading stage for industrial transformation, �鶹ԭ�� will introduce a new set of AI‑powered manufacturing and supply chain innovations. These innovations help companies ensure business continuity by orchestrating people, processes, and technology across their extended enterprise, turning volatility into an opportunity for resilience, efficiency, and customer impact.

From AI insight to AI in execution

For years, manufacturers have invested in analytics and dashboards to improve visibility. But visibility alone does not prevent disruption. What’s required now is AI embedded directly into core business processes, where intelligence can analyze alerts, reason over business impact, and provide real-time solutions to resolve issues. With agentic AI, companies are now able to go a step further: automating the right actions for the best outcomes, with humans remaining in the loop wherever critical decisions are required.

�鶹ԭ�� is operationalizing AI at industrial scale by embedding AI agents directly into supply chain and manufacturing workflows and contextualizing them with trusted enterprise and network data. Built on harmonized industrial, transactional, and network data, these agents can move beyond analysis to real‑time prediction and execution, working to deliver resilience, regulatory readiness, and measurable customer impact from day one. Creating tangible ROI is what matters most—whether by reducing unplanned downtimes, scrap, and rework, or by increasing quality and ultimately production output.

Orchestrating the supply chain end to end with AI

At the center of �鶹ԭ��’s focus at Hannover Messe is .

�鶹ԭ�� helps manufacturers connect processes and data not only across internal teams, but also across company boundaries—with suppliers, logistics partners, and service providers. By using AI agents to connect design, planning, procurement, manufacturing, logistics, service, and asset management—and by integrating seamlessly with ERP and line-of-business systems—�鶹ԭ�� helps break down silos that slow decision-making and increase operational risk.

This new agentic orchestration is powered and governed by a portfolio of intelligent applications that act, not just analyze, enabling faster, more coordinated responses without sacrificing quality, control, or growth.

New AI agents redefining planning, service, and operations

At Hannover Messe 2026, �鶹ԭ�� will showcase AI agents that help manufacturers and operators reduce time to value, stabilize operations, and improve service levels amid ongoing disruption. As a precursor to broader announcements planned for �鶹ԭ�� Sapphire, these agents demonstrate how agentic AI delivers practical benefits across all supply chain domains. Here are a few examples:

Manufacturing

• Production Master Data Agent helps automate and optimize the creation and maintenance of production master data. By leveraging the bill of materials, the agent can generate production routings—including operations and work centers—and help ensure components are correctly assigned across the production process. This helps reduce manual effort, accelerate production setup, and keep production data accurate as requirements change. General availability is planned for Q2 2026.
• Production Planning and Operations Agent enables planners to release production orders using natural language while automatically validating material availability, capacity, and scheduling constraints. Joule provides recommendations—such as alternative components or rescheduling options—that planners can review and approve, reducing manual work and keeping production aligned with real‑world conditions. General availability is planned for Q2 2026.

Assets & services

• Field Service Dispatcher Agent can improve service responsiveness and asset uptime by dispatching the right technician based on skills, location, asset condition, and priority—driving faster resolution and better workforce utilization. General availability is planned for Q2 2026.
• Alert Processing Agent can enrich operational alerts using past incidents, resolutions, and contextual signals and recommend clear, data‑driven actions to help teams resolve issues faster and improve operational reliability. General availability is planned for Q3 2026.
• Asset Health Agent analyzes time‑series health indicators to assess and summarize the current and projected health of individual and multiple technical objects. By forecasting when assets are likely to become critical and alerting users in real time, the agent supports condition‑based maintenance and helps minimize downtime while ensuring asset availability. General availability is planned for Q3 2026.

AI agents advancing logistics execution

• Material Reservation Agent helps ensure materials are available when and where needed by automating reservation creation and maintenance based on business rules—reducing delays, improving inventory accuracy, and optimizing working capital. General availability is planned for Q2 2026.
• Outbound Task Orchestration Agent can protect customer service levels by detecting and resolving picking and packing issues in real time, orchestrating corrective actions to support on‑time, accurate delivery. General availability is planned for Q2 2026.

Aligning workforce, logistics, and assets in real time

Operational resilience also depends on synchronizing people with all other resources as conditions change.

With , skills, certifications, availability, and labor rules are aligned with real-time operational demand so workforce plans can adjust automatically as production changes.

In logistics, , together with the new solution, helps organizations reduce transportation costs, accelerate warehouse execution, and improve delivery performance. Using conversational interaction with Joule, order managers can prioritize fulfillment while automatically accounting for availability and scheduling constraints.

Asset and quality operations also benefit from embedded intelligence. AI-assisted anomaly detection and alert processing in helps teams identify risks earlier, prioritize actions, and reduce unplanned downtime. In parallel, �鶹ԭ�� Document AI can automate the , improving throughput, data quality, and compliance at scale.

Regulatory readiness and what’s next

As regulatory requirements tighten, �鶹ԭ�� is expanding support for Digital Product Passports as part of , aligned with the EU’s Ecodesign for Sustainable Products Regulation (ESPR). These capabilities help manufacturers create ESPR‑ready product records capturing environmental impact, material composition, repairability, and recyclability data. General availability is planned for Q2 2026.

Expanded �鶹ԭ�� Business Network capabilities also deliver built‑in e‑invoicing compliance and data-residency support, enabling secure partner collaboration, synchronized logistics, and improved delivery performance across global networks.

See it live at Hannover Messe 2026

Taken together, these innovations reflect a shift from reactive management to intelligent execution—where AI is embedded directly into the processes that keep manufacturing and supply chains running today while laying the foundation for the next wave of innovation that will be unveiled at �鶹ԭ�� Sapphire.

Visit �鶹ԭ�� at booth F08 in Hall 15 at Hannover Messe 2026, April 20–24, to see how AI-infused orchestration, embedded AI agents, and end‑to‑end supply chain applications are redefining manufacturing.

Dominik Metzger is president and chief product officer for �鶹ԭ�� Supply Chain Management.

The announcement was made at HANNOVER MESSE 2026, where they showcased PacXplorer, a high-tech packaging machine from Uhlmann that serves as both an industrial demonstrator and a development platform.

PacXplorer: Connected Production in Industrial Practice

Developed through collaboration within Factory‑X, the PacXplorer brings together digital twins, condition monitoring, smart services and interoperable production solutions within a collaborative data ecosystem. Factory‑X is a lighthouse project funded by the German Federal Ministry for Economic Affairs and Energy as part of the Manufacturing‑X initiative. Its objective is to establish a decentralized data space for the capital goods industry, enabling secure and interoperable data exchange across companies and industries for equipment manufacturers and operators alike.

The machine is integrated into �鶹ԭ�� system landscapes and operated live. It demonstrates how industrial data can be used in a sovereign, interoperable and cross‑company manner not as a theoretical model, but in real production operations. This creates transparency regarding asset condition, utilization and performance while laying the foundation for new data‑driven services.

Service as a Key to Resilience

The value of this approach becomes particularly clear in service operations. Where production, data and operations are tightly interconnected, service plays a decisive role in ensuring asset availability, productivity and stable customer relationships. One often underestimated lever is spare parts service: delays lead directly to downtime and economic losses, especially in volatile market and supply situations. At the same time, these processes remain heavily manual in many industrial companies.

�鶹ԭ�� and Uhlmann are deliberately advancing the further development of this area. An AI‑supported process assists throughout the entire workflow from handling incoming inquiries and clarifying missing information to identifying the correct spare part and generating quotations. The approach integrates into existing �鶹ԭ�� service and sales processes and is closely aligned with real‑world business operations. The objective is fast, reliable and scalable customer service.

“Today, industry is less concerned with cost optimization than with decision‑making under uncertainty,” says Dominik Metzger, President and Chief Product Officer, �鶹ԭ�� Supply Chain Management, �鶹ԭ�� SE. “With �鶹ԭ�� Business AI and integrated production and service solutions, we move decision‑making directly into business processes. This allows companies to identify risks early, respond with greater flexibility and remain operational even under unstable conditions.”

Rethinking Value Creation Together

The collaboration between �鶹ԭ�� and Uhlmann illustrates a fundamental shift in industry: resilience is not achieved through additional buffers, but through better, faster and more-connected decisions across the entire value chain. Companies that manage their production and service processes in a data‑driven way can respond more flexibly to change and secure their competitiveness over the long term.

Beyond HANNOVER MESSE, �鶹ԭ�� and Uhlmann will continue their innovation partnership. Following the event, the PacXplorer will be operated at the S.Factory in �鶹ԭ�� Experience Center Walldorf, serving as a platform for customers, partners and co‑innovation to continuously advancing industrial transformation.

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Media Contact:
Dana Roesiger, +49 6227 7 63900, dana.roesiger@sap.com, CET
�鶹ԭ�� �鶹ԭ�� Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.  Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of �鶹ԭ��’s 2025 Annual Report on Form 20-F.
© 2026 �鶹ԭ�� SE. All rights reserved.
�鶹ԭ�� and other �鶹ԭ�� products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of �鶹ԭ�� SE in Germany and other countries. Please see for additional trademark information and notices.

Image copyright: ©Uhlmann Group

�鶹ԭ�� is expanding the Joule solution across �鶹ԭ�� 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 �鶹ԭ�� 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 �鶹ԭ�� 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 �鶹ԭ�� Concur and Amex GBT, Concur Travel and Concur Expense solutions.
• The �鶹ԭ�� Sales Cloud solution now integrates with Booking Agent to streamline workflows and enhance productivity for sales teams.

�鶹ԭ�� 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 �鶹ԭ�� 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® Corporate and Business customers using Concur Expense with availability for all such customers planned for Q3 2026.

�鶹ԭ�� 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 �鶹ԭ�� Early Adopter Care in Q3 2026. �鶹ԭ�� Concur solutions will now support RTN from all major credit card networks.

Additionally, �鶹ԭ�� 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 these or join the . 

Visit the . Get �鶹ԭ�� news via  and .

Media Contact:
Kelly Sheldon Murray, +1 (978) 708-6821, 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 �鶹ԭ��’s 2025 Annual Report on Form 20-F.
© 2026 �鶹ԭ�� SE. All rights reserved.
�鶹ԭ�� and other �鶹ԭ�� products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of �鶹ԭ�� SE in Germany and other countries. Please see for additional trademark information and notices.

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 “Silicon Valley” for defense innovation, and featured customers, partners, academics, government officials, and representatives from �鶹ԭ��. 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, �鶹ԭ�� 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’ 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 �鶹ԭ��’s 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 �鶹ԭ�� Industries & Experiences.

Photography courtesy of Norbert Steinhauser.

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Sovereignty is becoming a defining factor for organizations in the public sector and regulated industries. It is the foundation for adopting AI in a trusted, responsible way — and for driving meaningful digital transformation.

At the World Economic Forum Annual Meeting 2026 in Davos, �鶹ԭ�� executives Christian Klein and Thomas Saueressig, Chairman of the Supervisory Board of �鶹ԭ�� SE Pekka Ala-Pietila, along with global business leaders Dr. Ferri Abolhassan and Taha Bawa all share insights on how full-stack sovereignty empowers organizations and how trust and data control fuel responsible AI adoption.

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—this while many brands are still optimizing for search engines and are quietly disappearing from the models driving the next generation of product discovery.

“Agentic commerce—shopping powered by AI agents acting on our behalf—represents a seismic shift in the marketplace,” McKinsey, the strategic management consultancy, noted in a . “It 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.”

This, as speakers and panelists at the NRF conference acknowledged, isn’t just an evolution of e-commerce; it’s 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, �鶹ԭ�� 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.

�鶹ԭ�� 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 �鶹ԭ�� Business Data Cloud that leverages data from across �鶹ԭ�� software and third-party systems to help provide accurate demand planning, improved forecast accuracy, and lower inventory costs to drive more seamless omnichannel engagements.

�鶹ԭ�� Customer Experience has also unveiled a recently that can be combined with the��, 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, �鶹ԭ�� 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 , “while most retail merchandising teams have invested in automation tools��and experimented with AI, 71% of merchants say that AI merchandising tools have had limited to no effect on their business so far.”

“The challenge,” McKinsey said, “often lies less in the technology than in how it’s 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’t at all or is only slightly prepared to scale AI across merchandising.”

Onstage at NRF, Andre Bechtold, president for �鶹ԭ�� 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.

“Retailers are operating in an environment defined by volatility—tariffs, margin pressure, supply chain disruption, and customers that expect real-time, hyper-personalized experiences everywhere,” Bechtold said during a discussion with Gymshark, the workout apparel retailer. “At the same time, boards and investors are asking a tougher question than ever before: what outcomes are we actually getting?”

“The challenge,” he said, “isn’t a lack of innovation. In fact, most retailers have plenty of tools, pilots, and point solutions. The real issue is that disconnected technology doesn’t translate into resilient growth. That’s why the conversation is shifting. It’s no longer about isolated AI use cases or shiny new features. It’s about whether AI and data are embedded across the business—connecting supply chains, finance, merchandising, and customer engagement—in ways leaders can trust.”

Echoing the same point, Thomas Saueressig, member of the Executive Board of �鶹ԭ�� 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. ��“As long as AI runs alongside the core business as an isolated project, the effects remain limited,” he said.

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AI is transforming how work gets done, but only when humans remain at the center.

�鶹ԭ�� takes an AI‑first, suite‑first approach, embedding AI directly into business processes to help drive productivity, profitability, and growth.

�鶹ԭ�� executives Christian Klein, Gina Vargiu-Breuer, and Dominik Asam, along with Snowflake CEO Sridhar Ramaswamy and Goodwall CEO Taha Bawa, share their insights on the importance of AI in business transformation during the World Economic Forum Annual Meeting 2026��in Davos.

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, �鶹ԭ��’s focus is firmly grounded in helping retailers take practical steps today. This isn’t about flashy demos of a distant future—it’s 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’s 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—often before a shopper ever visits a retailer’s site.

Like marketplaces before them, AI agents introduce a new layer between brands and customers. The difference is speed and autonomy. Agents don’t just surface options; they reason, decide, and act.

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

At NRF, �鶹ԭ�� expanded its agentic commerce vision with the announcement of the storefront MCP server for �鶹ԭ�� 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—whether embedded in a retailer’s 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’s the first of many steps �鶹ԭ�� 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—it’s 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 �鶹ԭ�� Commerce Cloud—working to give retailers agility without sacrificing control or scalability.

Returns become a strategic intelligence engine

Returns are one of retail’s 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 “keep, reject, or return” 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. �鶹ԭ�� can deliver this through native integration between �鶹ԭ�� ERP and �鶹ԭ�� 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%–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—turning 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—reviews, 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—whether 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. �鶹ԭ�� 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—where 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—but only for those who build the right foundations today.

To learn more about how �鶹ԭ�� Commerce Cloud is powering AI-driven commerce, visit .

Kollen Glynn is global head of �鶹ԭ�� Commerce Cloud for �鶹ԭ�� Customer Experience.

NEW YORK — (NYSE: �鶹ԭ��) today announced a new generation of AI-enhanced retail innovations at NRF 2026: Retail’s Big Show.

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

“Retailers face a landscape where AI is no longer optional,” said Balaji Balasubramanian, President and Chief Product Officer for Customer Experience and Consumer Industries, �鶹ԭ�� SE. “�鶹ԭ�� provides one closed-loop, AI-enhanced retail operating system that ties planning, execution and engagement together. We put data and AI at the heart of retail, delivering speed, personalization and growth across every channel and segment.”

AI that turns retail data into actionable intelligence

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

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

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

AI that streamlines modern retail operations

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

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

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

AI that drives better customer engagement

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

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

AI that builds customer loyalty

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

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

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

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Media contact:
Mallory Kuno, +1 (425) 239-9362,��mallory.kuno@sap.com, ET
�鶹ԭ�� �鶹ԭ�� Room; press@sap.com

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