That idea framed a , where Thomas Saueressig, chief customer officer and member of the Executive Board of 麻豆原创 SE, and Jan Gilg, global president of Customer Success & Americas and member of the Extended Board of 麻豆原创 SE, set out the company鈥檚 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.

鈥淓very day, billions of people wake up trusting that the world simply runs,鈥� Saueressig said.

But making that happen is anything but simple. Saueressig pointed to the hidden complexity behind everyday routines 鈥� 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.

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

That challenge led directly to 麻豆原创鈥檚 vision for the 鈥� 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

鈥淚t鈥檚 this need for trusted, seamless integration that led us to our vision for the Autonomous Enterprise,鈥� 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 麻豆原创鈥檚 role as helping customers get there: 鈥淥ur goal is to help you become an Autonomous Enterprise step-by-step. … We are making AI value real today.鈥�

He linked that approach to RISE with 麻豆原创, 麻豆原创鈥檚 AI offerings, and the 麻豆原创 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

鈥淲hen you are fully committed to RISE with 麻豆原创, we are committed to support you at every step,鈥� 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 鈥�  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鈥檚 most demanding environments.

鈥淭ransformation is not the goal. Readiness is for us,鈥� said Maria Demaree, SVP and CIO of Lockheed Martin Corporation, stressing that the stakes are 鈥渉uman鈥� when systems support national defense and allied missions. Readiness, she explained, means the ability to move 鈥渨ith speed, clarity, and confidence across the enterprise.鈥�

Through its largest transformation investment in the company鈥檚 history, Lockheed Martin is redesigning processes end-to-end, connecting fragmented systems, and embedding AI into a model-based enterprise built on 麻豆原创.

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 鈥渢ransformation doesn鈥檛 start with technology. You must rethink your processes.鈥� 麻豆原创鈥檚 role, she said, has evolved from vendor to trusted partner understanding Lockheed Martin鈥檚 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 麻豆原创 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鈥檚 commercial flights, they need to keep airport operations running during severe winter weather. This has historically relied on manual, fragmented processes 鈥� 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.

鈥淲e passed from a reactive to a proactive model,鈥� said Gustavo Sabato, Chief Information Officer of Aeropuertos Argentina, highlighting expected benefits, including a 16% cost reduction and lower CO鈧� 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 麻豆原创 R/3 to 麻豆原创 S/4HANA in 2023 and building the solution on 麻豆原创 Business Technology Platform.  While integrating multiple non-standardized data sources was challenging, the result is now that the company operates with 鈥渙nly one version of the truth,鈥� 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. 鈥淥ur goal is not short-term optimization but long-term agility: standardizing on industry best practices, establishing a clean core, and becoming upgrade stable,鈥� he said.

He emphasized that both the transformation and the company鈥檚 AI ambitions depend on a strong foundation. 鈥淚f you can鈥檛 get this foundation right, you will continue to pay the price for it,鈥� 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 麻豆原创, standardizing processes and establishing a clean core.

That unified backbone now supports Levi鈥檚 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% 鈥� often submitted by smaller customers through handwritten notes, emails, or unstructured documents 鈥� previously took two to five days to process manually.

鈥淣ow, with the agents that we鈥檝e built on top of 麻豆原创, that process takes 20 to 30 minutes,鈥� 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. 

麻豆原创 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 鈥� from landscape analysis to custom-code assessment 鈥� can now be completed in a single weekend.

The world doesn鈥檛 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鈥檛 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鈥檚 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.

鈥淭he world doesn鈥檛 break because of change,鈥� he said. 鈥淚t breaks when change moves faster than resilience. And that鈥檚 where 麻豆原创 comes in.鈥� 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. 鈥淭he future isn鈥檛 written by AI.  It is written by us,鈥� he said.

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

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

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

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The business AI imperative

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

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

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

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

ERP as the foundation for business AI

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

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

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

麻豆原创 Business AI Platform

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

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

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

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

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

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

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

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

麻豆原创 Autonomous Suite

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

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

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

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

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

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

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

Industry AI: H&M and Sector-Specific Transformation

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

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

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

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

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

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

Closing: The Autonomous Enterprise

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

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

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

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

We explored how the Autonomous Enterprise is 麻豆原创鈥檚 new north star and vision. It鈥檚 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 麻豆原创 Sapphire, 麻豆原创 is reinventing itself for AI-native operations that move customers from point-solution AI to enterprise-wide autonomous operations.

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

AI isn鈥檛 technology for technology鈥檚 sake; it鈥檚 about driving outcomes, like real-time intelligence, automated end-to-end workflows, and continuous improvement鈥攁ll important aspects that AI can deliver.

麻豆原创 partners are 麻豆原创鈥檚 force multiplier to bring the Autonomous Enterprise to life, expanding reach, credibility, and adoption. To help 麻豆原创 partners evolve their practices to align with this vision, we also announced significant new investments in the partner ecosystem during the event.

麻豆原创 Business AI partner-led adoption program

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

At 麻豆原创 Sapphire, 麻豆原创 Executive Board Member and Chief Operating Officer Sebastian Steinhaeuser commented on our need to deepen our partner investments: 鈥溌槎乖� pledges 鈧�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 麻豆原创-delivered agents as well as by working with them to extend agents and build custom agents on our 麻豆原创 Business AI Platform.鈥�

The program has four packages:

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

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

麻豆原创 Business AI and data validated partner program

This new program distinguishes partners that demonstrate a holistic approach to 麻豆原创 Business AI and data along with deep expertise and close alignment with our 麻豆原创 Business AI and data strategy. Built on the foundation of the existing Competency Framework for the 麻豆原创 PartnerEdge program and enhanced by 麻豆原创 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 麻豆原创 Business AI Platform.

Partner agent race to 麻豆原创 TechEd

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

For the partner agent race to 麻豆原创 TechEd, agents must be:

• Developed with Joule Studio and deployed to 麻豆原创 Business AI Platform runtime
• Deployed on 麻豆原创 Business AI Platform using 麻豆原创 Cloud SDK for AI and AI Foundation

Extensions of 麻豆原创-delivered agents must also be created with Joule Studio, and agents that only integrate via direct APIs or integration services for 麻豆原创 BTP are out of scope for this project. 麻豆原创 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

麻豆原创 is introducing a structured enablement path that takes partners from awareness to action. 麻豆原创 has combined large-scale enablement and market recognition programs to scale the partner ecosystem for the Autonomous Enterprise and 麻豆原创 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 麻豆原创 Business AI Platform pages on听麻豆原创 Partner Portal provide all the information partners need for success, regardless of where they are in their AI journey.

麻豆原创 will deepen this enablement strategy with the upcoming听鈥淎I era powered by the Autonomous Enterprise鈥� learning, covering 麻豆原创 Business AI Platform, Joule Studio, and more for learners who want hands-on platform experience. 麻豆原创听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 麻豆原创 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 麻豆原创 Business AI Platform, accelerating ecosystem鈥憀ed growth in support of 麻豆原创鈥檚 AI鈥慺irst strategy. Our goal is ambitious: We want to see every 麻豆原创 customer enjoy an AI experience with 麻豆原创 in the next year. Let鈥檚 get them on the cloud and toward our vision.

Together, we鈥檒l 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 麻豆原创.

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 麻豆原创 Sapphire, we鈥檙e taking a giant step forward in making that mission a reality.

I鈥檓 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 麻豆原创 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 麻豆原创 landscape.

Let鈥檚 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鈥檝e 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鈥檚 request with 麻豆原创 Signavio Process Consultant Agent, 麻豆原创 Knowledge Graph, and 麻豆原创 Domain Models.
• Understands the customer landscape with 麻豆原创 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 麻豆原创-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鈥攁ll without sacrificing 麻豆原创鈥檚 enterprise-grade security and governance.

Vercel for blazing-fast, custom digital experiences

While 麻豆原创-oriented frameworks like UI5 and 麻豆原创 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 麻豆原创 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 麻豆原创 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 麻豆原创 systems, Joule Studio capabilities, and 麻豆原创-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, 麻豆原创 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 鈥� 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 麻豆原创 Business Transformation Management solutions like 麻豆原创 Signavio and 麻豆原创 LeanIX as well as 麻豆原创 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 麻豆原创 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: 麻豆原创 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, 麻豆原创 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 麻豆原创 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 麻豆原创 Knowledge Graph, 麻豆原创 Business Data Cloud, and 麻豆原创 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 麻豆原创 AI Agent Hub, fully managed Joule runtime, and solutions like 麻豆原创 Signavio and 麻豆原创 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 麻豆原创 live data, processes, and business semantics.

I am pleased to share that now through the end of 2026, 麻豆原创 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 麻豆原创 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 麻豆原创 Business Technology Platform and a member of the Extended Board of 麻豆原创 SE.

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

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

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

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

Introducing 麻豆原创 Business AI Platform

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

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

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

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

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

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

Designing the Autonomous User Experience

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

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

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

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

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

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

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

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

.

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About 麻豆原创

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

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

Unveiled today at 麻豆原创 Sapphire, Anthropic and 麻豆原创 will collaborate to embed Claude鈥檚 agentic capabilities into the newly announced 麻豆原创 Business AI Platform to advance 麻豆原创鈥檚 vision of the Autonomous Enterprise in the agentic AI era.

The collaboration builds on 麻豆原创鈥檚 more than 50-years of business application know-how across processes, data, and governance. This complements 麻豆原创鈥檚 open ecosystem approach to supporting any model and provides greater customer choice and flexibility to meet evolving AI requirements. 

Connecting directly to 麻豆原创 Business AI Platform, Claude will empower agents to carry 鈥媜ut tasks鈥攆rom closing the books at quarter-end and answering complex employee leave questions to rerouting supplier orders mid-shipment鈥攃oordinating across 麻豆原创 S/4HANA, 麻豆原创 SuccessFactors and 麻豆原创 Ariba solutions, and other systems via MCP.

鈥淥ur open platform means we鈥檙e tightly integrated with world-leading companies across our portfolio. Together with Anthropic, we鈥檙e building something uniquely valuable for our customers,” said Christian Klein, CEO of 麻豆原创 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 麻豆原创 Business AI Platform, that work happens inside the systems enterprises have already invested in, with the trust and governance 麻豆原创 customers rely on,” Daniela Amodei, co-founder and president of Anthropic, said.

Claude brings additional agentic capabilities and connectivity to Joule

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

With a deeper use of Claude and access to Anthropic鈥檚 frontier models, 麻豆原创 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 麻豆原创 customers, across finance, 鈥嬧�婬R, procurement, and supply chain. Agents leveraging Claude connect to 麻豆原创 Business AI Platform to understand business context grounded in 麻豆原创 data, make 鈥嬧�媘ore 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 麻豆原创鈥檚 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 麻豆原创 will work strategically to build custom agents and agentic workflows in 麻豆原创鈥攐ptimizing for key industries such as public sector, healthcare, education, life sciences and utilities. This combines 麻豆原创’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 麻豆原创 customer’s environment, it does so within the same controls that govern human decisions: the approvals, policies, and compliance frameworks already wired into 麻豆原创 solutions.

Together, Anthropic and 麻豆原创 plan on bringing this model to life by combining Claude with 麻豆原创鈥檚 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 麻豆原创 SE.

For 麻豆原创 customers, this shift promises step-change productivity. But it also raises a hard requirement: Enterprise AI agents must be safe, governable, and auditable by design.

This is the context for 麻豆原创鈥檚 deep technical collaboration on 麻豆原创 Business AI Platform with , an open source secure runtime for autonomous AI agents. This collaboration is not about 麻豆原创 鈥渁dopting鈥� a runtime. It is about 麻豆原创 actively shaping, hardening, and productizing the execution layer for enterprise agentic AI鈥攖ogether with NVIDIA.

Why this matters to 麻豆原创 customers

For 麻豆原创 customers, the value of this collaboration is concrete and practical. It enables:

• AI agents that operate inside 麻豆原创 processes without bypassing governance
• Security models aligned with enterprise IAM and compliance frameworks
• Clear audit trails for agent actions across systems
• Confidence to move from pilots to production

Most importantly, it avoids a false choice between innovation and control. Customers do not have to bolt security on later, or redesign their risk models to accommodate AI agents. Instead, security and governance are built into the execution model from the start.

The real enterprise challenge: Trusting agents that act

When AI systems move from generating responses to executing actions, the risk profile fundamentally changes. Agentic systems can touch systems of record, cross application and data boundaries, and operate without human review at every step.

In all enterprise environments, especially regulated ones, this makes execution safety and governance the defining challenge. Traditional chatbot-era controls are insufficient once agents can access shells, files, networks, credentials, and APIs.

麻豆原创 customers know this reality well. Business AI is only valuable if it can be:

• Inspected and audited
• Constrained by policy
• Trusted by security and compliance teams

Solving this problem requires more than infrastructure primitives or application-level rules alone.

NVIDIA OpenShell: The foundation

NVIDIA OpenShell addresses a critical layer of the problem: secure, sandboxed execution of autonomous agents.

As an open source runtime, OpenShell introduces strong capabilities, including:

• Isolated execution environments
• Policy enforcement for filesystem and network access
• Runtime-level containment that limits blast radius even when agent logic fails

These capabilities form a foundational layer for autonomous agents to execute safely. In practice, enterprises need that execution layer aligned with business context and governance.

Enterprises expect clarity on questions such as:

• Which business role authorizes an action?
• Which process context applies?
• How actions map to enterprise policies and audit trails?

This is where 麻豆原创鈥檚 contribution becomes decisive.

What 麻豆原创 brings: Enterprise semantics, governance, and scale

麻豆原创 is co-developing and contributing to OpenShell based on enterprise reality.

1. Enterprise-driven runtime requirements

麻豆原创 operates at a level of scale and responsibility that few software providers do: mission-critical processes, regulated industries, and millions of transactions per hour.

By bringing real 麻豆原创 agentic workloads into the collaboration, 麻豆原创 provides the operational proving ground that OpenShell needs to mature from a powerful runtime into an enterprise-hardened one.

This includes shaping requirements around:

• Isolation boundaries that match enterprise risk models
• Policy enforcement aligned with real business constraints
• Auditability that stands up to customer and regulatory scrutiny

2. Co-development of OpenShell capabilities

麻豆原创 is committing engineering capacity to the OpenShell open-source code base, with a focus on areas that matter specifically to enterprises: runtime hardening, policy modeling, enterprise identity integration, and auditing and governance hooks.

麻豆原创 is helping define how secure agent execution must work for enterprises; not just theoretically, but in production.

3. Joule Studio runtime: From runtime safety to enterprise control

Where OpenShell secures execution, Joule Studio runtime provides the enterprise harness that makes agents usable and governable in business systems:

• Business-aware policy semantics like roles, skills, life cycle
• Enterprise identity and access control
• Observability and auditability across agent behavior
• Deployment and operational governance across landscapes

This ensures that agent autonomy is always framed by business intent and accountability, not just technical permissions.

OpenShell answers: 鈥淐an this action safely execute?鈥�; Joule Studio runtime answers: 鈥淪hould this action happen at all?鈥�

Raising the bar for enterprise agentic AI

This collaboration represents more than an integration. It reflects a shared intent to define what 鈥渆nterprise-grade鈥� actually means for autonomous AI systems.

By combining NVIDIA鈥檚 runtime and security innovation and 麻豆原创鈥檚 enterprise productization, governance expertise, and operational scale, 麻豆原创 and NVIDIA are working toward an integrated solution for trusted agent execution鈥攐ne that enterprises can inspect, govern, and rely on.

For 麻豆原创 customers, this means AI agents that are not just powerful, but designed to earn trust in the environments where trust matters most.

Andre Lamego is senior vice president and chief product officer of 麻豆原创 BTP Fabric

Building on their long-standing partnership, AWS and 麻豆原创 are making it easier for customers to access mission-critical 麻豆原创 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鈥攚ithout waiting for IT teams to replicate, prepare, and provision 麻豆原创 data. 

鈥淭he next era of business will be defined by how well organizations turn intelligence into action at scale,鈥� said Muhammad Alam, member of the Executive Board of 麻豆原创 SE, 麻豆原创 Product & Engineering. 鈥淏y bringing together 麻豆原创 Business Data Cloud and widely adopted AWS AI and analytics capabilities, customers can unlock the true potential of data and AI.鈥� 

Enabled by 麻豆原创 BDC Connect, the integration delivers near real-time, zero-copy access to semantically rich 麻豆原创 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.

“麻豆原创 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 麻豆原创 Business Data Cloud with the AWSsecure, global infrastructure and advanced AI services, organizations can unlock mission-critical 麻豆原创 data and act on it at the speed and scale their business demands.” 

With 麻豆原创 BDC Connect for Amazon Athena customers can: 

• Create a single, trusted foundation for all their business data, 麻豆原创 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

麻豆原创 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 (S茫o Paulo), Asia Pacific (Seoul), Asia Pacific (Singapore) Regions, and the AWS European Sovereign Cloud. 

Partnership opens new pathways for enterprise data migration with 麻豆原创 AI-supported tooling complemented by Palantir鈥檚 AIP for data migration scenarios to simplify an expedite digital transformation for 麻豆原创 customers, with Accenture as a co-innovation partner for joint customers

This year at 麻豆原创 Sapphire, 麻豆原创 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 麻豆原创鈥檚 vision of the Autonomous Enterprise.

The enhanced partnership is designed to facilitate joint customers鈥� 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 麻豆原创鈥檚 broader agentic migration strategy, uniting 麻豆原创鈥檚 deep expertise in enterprise applications and 麻豆原创 Business AI with Palantir鈥檚 AIP to deliver AI-driven data migration capabilities that accelerate timelines, secure cost efficiencies, and fundamentally transform how organizations operate. 麻豆原创 customers can now leverage Palantir鈥檚 AIP for data migration scenarios alongside the agent-led toolchain from 麻豆原创, which includes business transformation tools and the new migration and modernization assistants to accelerate their transformations to 麻豆原创 Cloud ERP.

鈥淭o 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,鈥� said Christian Klein, CEO of 麻豆原创 SE. 鈥淭ogether with Palantir, we are enabling customers to move to the cloud with speed and confidence through complementary capabilities that accelerate innovation across the enterprise.鈥� 

鈥淲e are proud to partner with 麻豆原创 and Accenture to bring the power of advanced AI and data migration to the world鈥檚 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,鈥� 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, 麻豆原创, Palantir, and Accenture can help joint customers identify acceleration opportunities across 麻豆原创 and non-麻豆原创 systems sooner, achieve faster time-to-value, and drive continuous innovation by fundamentally redefining the approach to 麻豆原创 Cloud ERP migrations.

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

鈥淚n today鈥檚 world, speed to value is critical for our clients,鈥� said Julie Sweet, chair and CEO of Accenture. 鈥淲e are excited to co-innovate with 麻豆原创 and Palantir to help our clients accelerate their journey to ERP modernization with 麻豆原创, which is the foundation for reinventing core operations and using AI to achieve new performance frontiers.鈥� 

New 麻豆原创-validated deployment options

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

Together, are redefining 麻豆原创 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 麻豆原创 Endorsed App on the 麻豆原创 Store. The 麻豆原创 Solution Extension is planned to be generally available to 麻豆原创 customers in Q3 2026.

Jan Gilg is a member of the Extended Board of 麻豆原创 SE.

In 2026, we will more than double the number of customers allowed into the program, marking an important milestone in our mission to provide RISE with 麻豆原创 on Azure customers extraordinary support and expertise throughout their experience. Thousands of enterprise customers are already transforming their businesses with RISE with 麻豆原创 on Azure, including , and

First publicly , this initiative brings together the best technical teams from 麻豆原创 and Microsoft to enable a more seamless, high-touch migration and onboarding experience for the customer with no additional cost for an accelerated path to business transformation and faster cloud innovation.

A collaborative approach to success

The program is a joint customer experience that complements and enhances the RISE with 麻豆原创 customer journey, providing

• Designated resources: Access to a global team of 麻豆原创-skilled Microsoft product engineers, cloud solution architects, and support experts
• Proactive services: Recommendations based on proven best practices from years of close cooperation between Microsoft and 麻豆原创 engineering teams, delivered via Microsoft Engineering and Customer Success subject matter experts
• Access to Cloud Accelerate Factory: For all customers in the program, access to , which delivers hands-on support to help customers streamline modernization on Azure
• Enhanced support: Streamlined escalation paths across 麻豆原创 and Microsoft to ensure aligned oversight and guidance at every step
• Zero cost: Program offered free of charge to approved customers

鈥淩ISE with 麻豆原创 on Microsoft Azure ensures customers experience the best of both worlds: 麻豆原创鈥檚 business process leadership and Microsoft鈥檚 trusted cloud platform,” 麻豆原创 Chief Partner Officer Karl Fahrbach said. “Together, we鈥檙e helping organizations move faster, reduce risk, and innovate with confidence as they embrace the future of the intelligent enterprise.”

鈥淭his program reflects our deep commitment to helping customers modernize mission-critical 麻豆原创 workloads on Azure with confidence,” said Sandy Gupta, vice president of Global ISV Ecosystem at Microsoft. “By combining Microsoft鈥檚 cloud innovation with 麻豆原创鈥檚 business expertise, we鈥檙e delivering a secure, predictable, and AI-ready journey that accelerates time to value and unlocks new opportunities for transformation.”

Joint value: Why this matters for customers

The RISE with 麻豆原创 on Microsoft Azure initiative is more than just a technical offering; it鈥檚 a strategic investment in customer success, delivered jointly by Microsoft and 麻豆原创.

Key benefits of the initiative for customers include:

• Frictionless go-lives:听 The program helps reduce technical downtime, risk, and post-processing cutover delays
• Enhanced reliability: Proactive health checks, architecture reviews (Azure environment), and direct communications paths to Microsoft Customer Success and Engineering
• Go-live readiness support: Azure health checks and engagement at key project milestones

Accelerating your digital transformation

Whether your organization is just beginning its RISE with 麻豆原创 journey or looking to accelerate an ongoing migration, this program ensures you have the expertise, visibility, and partnership needed to succeed.

To learn more or nominate your organization, contact your 麻豆原创 or Microsoft account representative.

As one of the , TSG Hoffenheim is working closely with 麻豆原创 in a co鈥慽nnovation setup to pioneer and test new AI capabilities within . The focus is on assessing how AI can support football鈥憇pecific processes such as scouting and video analysis. 

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Transforming scouting with generative AI 

Scouting is crucial to TSG Hoffenheim and one of the most data-intensive areas in football. Talent evaluations often include dozens of detailed reports, observations, and assessments that must be synthesized into a clear player profile. 

As part of the ongoing co鈥慽nnovation, TSG Hoffenheim and 麻豆原创 are currently experimenting with AI鈥�supported scouting summaries in 麻豆原创 Sports One. Early versions explore how 麻豆原创 Joule can be used to ask natural language questions and receive AI鈥慻enerated responses that help condense extensive, unstructured text into more concise overviews, including recurring strengths, weaknesses, and performance tendencies. 

Scouts can ask, for example, questions such as: 

• 鈥淗ow good is player X at creating chances?鈥�  
• 鈥淪ummarize the most relevant observations from the scouting reports of player X from 2026.鈥� 
• 鈥淲hat are the strengths and weaknesses for Player X?鈥� 

These capabilities are being evaluated for their potential to reduce manual consolidation effort and support consistency in player assessments. Together, these benefits aim to enable more informed decision鈥憁aking across both youth and professional scouting. TSG Hoffenheim actively contributes to shaping this capability as 麻豆原创 evolves it, ensuring it reflects the operational realities of modern scouting organizations. 

AI-assisted scene finder: accelerating video analysis 

Video analysis remains one of the most resource-intensive workflows in professional football. 
Working together with 麻豆原创 and AWS Professional Services, TSG Hoffenheim is co鈥慽nnovating and testing an AI鈥�assisted scene finder concept. This capability explores how natural language input can support analysts in identifying relevant match situations more efficiently. 

Instead of sifting through video material, analysts can describe the scenario they are looking for: 鈥淪how counterattacks after ball recovery that resulted in a shot on target.鈥� Within seconds, the system can retrieve matching clips. 

For clubs like TSG Hoffenheim, this capability has great potential to reduce time spent on manual video search, support more targeted tactical preparation, and improve collaboration between analysts and coaching staff as the solution continues to mature.

Shared commitment to innovation 

鈥淥ur partnership with 麻豆原创 goes far beyond simply implementing new technology,鈥� Timo Gross, head of Football Intelligence at TSG Hoffenheim, said. 鈥淚t鈥檚 a true co鈥慽nnovation relationship that combines our practical on鈥慺ield football expertise with 麻豆原创鈥檚 leadership in enterprise AI and cloud鈥慸riven sports technology. By sharing real鈥憌orld insights from our daily work and validating new ideas early on, we play an active role in shaping the next generation of AI capabilities within 麻豆原创 Sports One.鈥� 

As AI becomes an integral part of , 麻豆原创 and TSG Hoffenheim will continue to collaborate on solutions that elevate performance, streamline operations, and unlock new strategic advantages. 

With intelligent scouting, natural language insights as well as automated video discovery, the future of football analysis is rapidly evolving, and TSG Hoffenheim stands at the forefront of that transformation. 

Isabelle Schuhmacher is communications lead for 麻豆原创 Global Sponsorships.

Top image 漏 TSG Hoffenheim

As a global player in the software and technology industry, 麻豆原创 is a key enabler of digital sovereignty in Germany and across Europe. With the introduction of the BSI鈥檚 new C3A criteria and the growing importance of resilient cloud infrastructures, digital sovereignty is now entering a phase of practical implementation.

I spoke with Thomas Caspers, vice president of the BSI, about these developments and the role of the technology partnership with 麻豆原创.

Q: Digital sovereignty is currently one of the central themes in German and European digital policy. Why is this topic gaining such strong momentum right now?

A: The debate is clearly driven by geopolitical factors. For us, the key issue is ensuring that Europe remains capable of taking action. That is precisely what digital sovereignty is about and, by the way, what cybersecurity in general is about as well: being prepared rather than reacting only when a crisis occurs.

The question is not limited to where data is stored. We take a systemic view of the overall picture: Will critical data centers remain operational? Is qualified personnel available? Are supply chains secured? Can services continue to be used even if the underlying conditions change suddenly? This ability to act is at the heart of the debate.

With the C3A, we are now consolidating the criteria that, from our perspective, enable the self-determined and secure use of cloud services, not only in public administration but far beyond that.

Q: With the C3A criteria catalogue, the BSI is now making its requirements for autonomous and self鈥慸etermined cloud usage public. What is new or distinctive about this?

A: Much of this is not fundamentally new for cooperation partners such as 麻豆原创, with whom we have worked closely for many years. We have been applying these criteria in practice for a long time and continuously refining them as technology evolves. What is new is that we have now systematically documented them and made them publicly available as a guiding framework.

The C3A do not have direct regulatory effect, but for the first time they create a high level of transparency for the market. It becomes clear which requirements cloud providers must meet if cloud customers or public authorities want to use cloud services in a self鈥慸etermined and secure manner. These requirements include technical, operational, and now also legal criteria. This comprehensive, systematic perspective is what is new and particularly important.

Q: What role does cooperation with technology providers such as 麻豆原创 play when translating these requirements into concrete architectures and operating models?

A: A very important one. 麻豆原创 was one of the first partners with whom we intensified cooperation in this context. Of course, there are formal rules and defined exchange formats for this collaboration. But in practice it quickly became clear that we are in almost continuous dialogue.

In developing the C3A, we also drew on experience gained from projects such as Delos Cloud and 麻豆原创 Cloud Infrastructure. This kind of direct cooperation is essential, especially as technology, security requirements, and sovereignty considerations are evolving so dynamically.

For us, it is crucial to work with companies where implementation can happen closely, trustfully, and quickly. This applies equally to established cloud topics and to new technologies. If we want innovation to be usable in a secure and controlled way and if Germany is to remain competitive in digitalization, this kind of early and reliable coordination between supervisory authorities and industry is indispensable.

Q: From your perspective, what demonstrates that digital sovereignty is more than just a political concept and can actually be implemented in practice?

A: For me, this is evident wherever requirements are not only defined, but actually tested and implemented in practice and where the resulting products and services then succeed in the market. This applies, for example, to the question of how cloud infrastructures can be brought to a level where they are suitable even for particularly critical environments.

It must be absolutely clear which criteria apply and how they are fulfilled technically, organizationally, and not least physically.

A concrete example is Delos Cloud as a sovereign cloud for public authorities in Germany. In cooperation with 麻豆原创, the BSI is working to transfer Microsoft cloud technology into a model that can be operated securely and self鈥慸eterminedly under German requirements. This clearly demonstrates that digital sovereignty is not merely claimed, but must and can be implemented architecturally, organizationally, and regulatorily.

That is where the value of cooperation lies. When requirements are clear, we can work together with companies on architectures, operating models, and security measures.

Q: Resilience is a key topic in the current debate. What must a sovereign cloud model be capable of in the event of geopolitical disruptions or failures?

A: It must remain operational. For us, resilience means having options and being prepared for difficult scenarios so that operations can be maintained in the event of a crisis. In our current scenarios, we assume that a minimum level of operation must be ensured over an extended period.

This explicitly includes situations in which original providers or supply chains are no longer available in their existing form at short notice.

In other words, we must consider not only normal operations, but also exceptional circumstances. Anyone who takes digital sovereignty seriously must also be prepared for scenarios that no one hopes to see. That is precisely why issues such as continuity of operations, availability of personnel, and supply鈥慶hain resilience play such a central role in the C3A.

Q: How important is the interaction of national standards such as between Germany鈥檚 BSI and France鈥檚 ANSSI for a shared European understanding of digital sovereignty?

A: This interaction is essential. Germany and France play a special role in the European debate because both countries are working very concretely on criteria, standards, and implementation models and are putting them into practice.

What we learn in Germany feeds into the European discussion, and of course we also benefit from exchanges with our partners in France and other European countries. If Europe is to make progress on digital sovereignty, it needs national innovative strength, reliable partnerships, and at the same time a shared strategic direction. This is also crucial for creating a scalable market for European companies such as 麻豆原创 one that encourages investment in innovation.

Q: What should public authorities, companies, and cloud providers prepare for in the coming years?

A: The requirements will become more concrete, more verifiable, and more systemic. The first question is what is technologically possible, but this must be followed by the question of how robust, transparent, and controllable an offering actually is. This applies to technical aspects as well as operational and legal ones. We have to consider the entire stack.

If we are able to make technologies usable in a secure and sovereign manner, then we should do so. That means clear standards, a holistic approach, and the ability to bring new technologies into use in a controlled way across the full stack.

Martin Merz is president of 麻豆原创 Sovereign Cloud.

Customers can deploy Joule Agents in 麻豆原创 CX Solutions to build, launch, and optimize marketing campaigns

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

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

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

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

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

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

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

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

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

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

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

For more information about Gemini Enterprise, visit .

Visit the . Get 麻豆原创 news via  and .

About Google Cloud

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

About 麻豆原创

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

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

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

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

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

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The marketer鈥檚 reality: ambition outpacing execution

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

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

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

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

AI accelerating the engagement divide 

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

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

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

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

New model for engagement built on trusted enterprise data

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

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

At the heart of this partnership:

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

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

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

Kevin Ichhpurani, President, Global Partner Ecosystem at Google Cloud

From prompt to performance: how agents work together for marketing

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

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

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

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

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

For example, a marketer can prompt:

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

And from there:

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

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

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

Clear business outcomes for marketing teams

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

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

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

Beyond campaigns: continuous engagement at enterprise scale

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

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

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

A great way to break through that roadblock is to listen to leaders who jumped in early to use AI to transform outcomes. , a managing director of Finance in the Global IT division at Accenture, is one of those people.

The professional solutions and services company employs nearly 780,000 employees across 52 countries, who work with 350 partners to serve over 9,000 clients. The idea of transformation at Accenture鈥檚 scale might be intimidating to some, but not Lambert. He鈥檚 leading an听ongoing transformation听of Accenture鈥檚 finance function, which he calls 鈥渢he heartbeat鈥� of the company.

The results he鈥檚 achieved鈥� including saving the finance team a combined 57,000 hours annually by having AI generate narrative summaries for reporting鈥攕hine a spotlight on what鈥檚 possible. And he鈥檚 just getting started.

I had a chance to speak with him about how he became a leader in AI-driven transformation, and what others can learn from his achievements. This is a lightly edited version of our conversation

Q: As you know, innovating with AI is about reshaping how a business delivers value. But not every business leader is leading the charge. Some are watching and waiting. Why did you roll up your sleeves and decide to be on the forefront?

A: Taking a leadership position on AI is important to keep moving forward and shaping new services and capabilities. For example, across a company our size, even though we鈥檙e hyper focused on emerging technologies, we can find small problems across our technology landscape. There are processes and data living in different places and silos develop over time. Most large companies have this challenge. But those are valuable processes, and the business data we have is especially valuable. AI opens up new opportunities to bridge those gaps and deliver more end-to-end outcomes, so that our finance function can meet the growing business expectations of our stakeholders.

For many companies, the key to getting impactful results from business AI is to start with one function that鈥檚 central to business performance. Why was finance the right place for you to begin, and what did you want to achieve?

I always say finance is the heartbeat of our organization. I heard one of our global IT leaders use that phrase, and while it was inspirational, it also made me think, 鈥淟et鈥檚 not accidentally cause a heart attack for the organization.鈥�

Jokes aside; he was right. Your transactional and operational data flows through finance, and management decisions sit on top of it. Starting there gave us the ability to make end-to-end impact across processes that touch procurement, liquidity, forecasting, receivables, and more. And 麻豆原创 gives us a digital core where all that transactional data is harmonized.

The bottom line is that finance is the natural starting point if you want to move from reactive reporting toward more proactive, AI-driven insights that you can use to help move the business forward. So, we set out to unify data and transform finance processes in a way that scales across the whole value chain.

Cash and liquidity are so important in the finance function, and to an entire company. But managing it requires bringing together data, forecasting, and decision-making across many teams. How did AI help?

If finance is the heartbeat of a company, cash and liquidity are the lifeblood of your systems. Here鈥檚 a great example: Accenture engages in a lot of acquisitions, and we run operational cash in 50-plus countries, so it鈥檚 easy for decisions to default to historical, manual reviews. That鈥檚 what was happening at Accenture before a forward-thinking leader stopped by and asked if we could apply machine learning to the problem. Great leaders often ask great questions, and that one really got us thinking.

[AI] freed up 20% of our idle cash, which we could then move into global operations to fund acquisitions and strategic growth.

Eli Lambert

We took inspiration from retail: how stores treat inventory based on discounts and sales. If you treat cash like stock, you can apply those same learning models to figure out how much you really need to hold onto at any point in time. That鈥檚 how we built what we call 鈥淚ntelligent Cash.鈥� It brings all the business data together into a single data mart, a repository for structured data for a specific department or line of business, and uses machine learning to generate recommendations that our teams can act on.

AI is so good at this, and here鈥檚 what鈥檚 incredible: It freed up 20% of our idle cash, which we could then move into global operations to fund acquisitions and strategic growth. Now what used to take months, or even more than a year to build, we can now do it in days or weeks because 麻豆原创鈥檚 data cloud brings [麻豆原创] Datasphere, Databricks, and our machine-learning workloads into one place. The result is faster decision-making, better visibility, and much more accurate forecasting.

I love hearing about how you were able to use gains, delivered through strategic AI innovation, and then channel those gains into a high-value activity for the organization.听 I know you also worked on receivables, something that impacts cash flow and customer relationships. What pain points did you face, and how did automation and machine learning transform the process?

Receivables were highly manual compared to payables. Clearing was inconsistent, and reconciliation took a lot of time because payments often come incomplete or with partial data. Anyone who works in or near finance knows exactly what I鈥檓 talking about. So, we co-developed on the 麻豆原创 platform a machine-learning-based receivables solution. It more than doubled the automation rate for receivables processing and tripled automatic reconciliation, about a 300% improvement.

As part of that, we introduced high-confidence, one-click matching recommendations that reduce errors and cut down the manual work. We saw a seven percent uplift in auto-clearing with a cash application scheduler built on the 麻豆原创 platform that delivers matches about 77% faster. All of that adds up to a more efficient receivables process, improved cash-flow visibility, and better productivity for the team.

In a global organization like Accenture, reconciling financial data and surfacing meaningful insights can be a huge amount of work. You turned to generative AI to help, which is really smart. What led you to that approach, and how is it changing your team鈥檚 day-to-day experiences?

We were dealing with balance sheet reconciliations across 50-plus countries, and the process was decentralized. I know a lot of companies face this problem. So, first, we moved everything online. Then we brought in machine learning and generative AI to analyze cost categories, summarize data, and surface important shifts.

[Our] Intelligent Financial Advisor, built on the 麻豆原创 platform, can generate narrative commentaries that are so accurate that over 90% are simply approved with little or no revision. That鈥檚 saved about 57,000 hours globally. Our teams can focus on higher-value analysis instead of manual reconciliation.

Eli Lambert

We then deployed an Intelligent Financial Advisor built on the 麻豆原创 platform that can generate narrative commentaries that are so accurate that over 90% are simply approved with little or no revision. That鈥檚 saved about 57,000 hours globally, just in controllership work, and helped us move to a three-day global close instead of five. The insights come faster and clearer, and the teams can focus on higher-value analysis instead of manual reconciliation. It鈥檚 also helping create more consistent roll-ups across regions and letting us use our talent more strategically.

I鈥檓 hearing this theme of not only measurable business gains from outputs, but the ability to better allocate time from manual, rote tasks to ones that deliver far more value for the business. That also applies to planning and forecasting. How did you bring AI into that part of the finance function?

Our planning work had grown too complex. Remember, we鈥檙e a large-scale, multifaceted global business. So, we replaced old models with 麻豆原创 Analytics Cloud, which gives us multi-year planning models enhanced by AI.

We applied it first to merger and acquisition modeling, where accuracy really matters. It lets us model very complex data sets and helps our finance team collaborate more easily across the business. The results have been more accurate forecasts, reduced risk of errors, and much better collaboration between executives and practitioners. Early results were strong, and that encouraged us to expand AI use in planning more broadly.

What advice do you have for leaders who are not as far along in using AI to supercharge business results?

First, start with a high-impact function tied to real outcomes. Then focus early on data quality and harmonization; it鈥檚 the foundation for everything that comes after. Then get your cadence right and your team working together. Hone in on the use cases that really matter to you鈥攖he best vendors can help you identify those鈥攁nd make sure to get the help you need from those vendors and their partners.

Use AI to spur growth. At Accenture, we鈥檝e been able to use AI to save significant cash in one area, which we then invest in another, high-growth process鈥攁cquisitions in our case. That鈥檚 how you use AI to really rethink your business and move it to the next level.

Eli Lambert, on advice to other enterprises

As you go, take a crawl-walk-run approach: start slow then increase the pace of scale and adoption over time. Be sure to invest in change management and upskilling as you go to spur learning and adoption. And partner closely with technology providers and system integrators who鈥檝e been there before. That accelerates everything.

The final suggestion I have is to use AI to spur growth. At Accenture, we鈥檝e been able to use AI to save significant cash in one area, which we then invest in another, high-growth process鈥攁cquisitions in our case. That鈥檚 how you use AI to really rethink your business and move it to the next level. And that鈥檚 possible today in ways that were not, even five years ago. Seize that opportunity.

I couldn鈥檛 agree more with Lambert. AI really does provide an opportunity to re-imagine entire business processes for greater impact.

To keep exploring what鈥檚 possible, at Accenture. Then see more AI use cases in and across all your , including procurement, supply chain, manufacturing, and more.

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

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

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

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

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

Inspection robotics is about data

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

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

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

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

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

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

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

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

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

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

Treating robots as part of the workforce

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

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

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

Project Embodied AI in practice

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

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

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

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

Scaling safely and responsibly

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

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

A glimpse into the future

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

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

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

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

Top image courtesy of ANYbotics

SafetyGuard was created as part of a program at UTUM鈥檚 Digital Product School鈥攚here teams of selected students work on real-world challenges鈥攊n just 12 weeks by a student team, 鈥淢IDAS,鈥� and 麻豆原创 Research & Innovation. This project illustrates just how effective cross-location collaboration with the ecosystem can be in rapidly creating prototypes as a foundation for product development at 麻豆原创.

Embodied AI: a joint focus of innovation

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

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

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

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

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

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

Programs with impact

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

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

Co-innovation gets results鈥攆aster

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

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

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

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

麻豆原创 has restructured the award recognition to provide more meaningful distinction, reflect our partners鈥� essential contributions, and ensure all award categories align with the Partner Ecosystem Success strategy. The newly created 麻豆原创 Partner Awards replace previous recognition programs, including 麻豆原创 Pinnacle Awards, 麻豆原创 Global LoB Partner Excellence Awards, and 麻豆原创 Regional Partner Excellence Awards.

In-region winners are announced at local kick-off events and regional partner summits in Q1. These partners have proven success in transforming customer business by harnessing cloud and AI technologies aligned with 麻豆原创鈥檚 business strategy. To encourage continued innovation, these partners are recognized for the value they deliver in fostering exceptional customer impact.

Recipients of these prestigious awards are a part of 麻豆原创鈥檚 wide-ranging partner base. Selections are made using system-generated data on key performance indicators and weighted metrics aligned with 麻豆原创鈥檚 communicated business strategies. A steering committee of designated regional representatives review and rank achievements accordingly.

Congratulations to the 2026 winners for this esteemed recognition!

2026 麻豆原创 Partner Awards 鈥� Regional

Recipients by region

Middle and Eastern Europe (MEE)

• Business Transformation Management, Excellence: NTT DATA Business Solutions
• Customer Transformation, Large Enterprise: Deloitte
• Innovative Solution, 麻豆原创 Store: Qualtrics
• Innovative Solution, Solution Extensions: Tricentis
• Managed Service Provider, Top Performance: T-Systems International
• RISE with 麻豆原创 Methodology: Accenture
• 麻豆原创 Business AI, Partner Innovation 鈥� Customer AI Use Case: PwC

Latin America and Caribbean (LAC)

• Customer Transformation, Partner-Led Territories: Seidor
• Customer Transformation, Corporate: Seidor
• Customer Transformation, Large Enterprise: Accenture
• Small Enterprise Growth: Heinsohn
• Delivery Quality: Globant
• Customer Success Management: ADP
• 麻豆原创 Cloud ERP, New Customer Acquisition: Seidor
• 麻豆原创 Cloud ERP, Installed Base Transformation: Seidor
• Rising Star: Kyndryll
• 麻豆原创 Business Data Cloud Success: Solveplan
• 麻豆原创 Business AI, Customer Adoption: Seidor
• Business Transformation Management, Excellence: NumenIT
• 麻豆原创 Business Suite Success: Seidor
• Innovative Solution, 麻豆原创 Store: Fioneer
• Innovative Solution, Solution Extensions: Tricentis
• Procurement Transformation Sales Excellence: Team Eight
• Finance Transformation Sales Excellence: Seidor
• Customer Experience Sales Excellence: Seidor
• Supply Chain Management Sales Excellence: NTT DATA Business Solutions 
• Human Capital Management Sales Excellence: ITGES
• The Best Partner of the Year: Seidor

North America (NA)

• Customer Transformation, Partner-Led Territories: Syntax
• Customer Transformation, Corporate: NTT DATA Business Solutions
• Customer Transformation, Large Enterprise: Accenture
• Small Enterprise Growth: Vision 33
• Delivery Quality: Deloitte
• Customer Success Management: NTT DATA Business Solutions
• 麻豆原创 Cloud ERP, New Customer Acquisition: VistaVu Solutions
• Rising Star: KPMG
• 麻豆原创 Business Data Cloud Success: The Hackett Group
• 麻豆原创 Business AI, Customer Adoption: Accenture
• Business Transformation Management, Excellence: Impriva
• 麻豆原创 Business Suite Success: Cognitus
• 麻豆原创 Store: Redwood
• Innovative Solution, 麻豆原创 Store: Laidon Group
• Partner Solution Success: OpenText
• Innovative Solution, Solution Extensions: Vistex
• Partner Learning and Skills Growth: Deloitte
• RISE with 麻豆原创 Methodology: Accenture

Europe, Middle East, and Africa (EMEA)

• Customer Transformation, Large Enterprise: Accenture
• Delivery Quality: Deloitte
• Partner Learning and Skills Growth: EY
• RISE with 麻豆原创 Methodology: IBM
• 麻豆原创 Business Data Cloud Success: Accenture
• 麻豆原创 Business AI, Customer Adoption: Deloitte
• 麻豆原创 Business Suite Success: Accenture
• 麻豆原创 Business AI, Customer Use Cases: PwC
• 麻豆原创 BTP Extensibility: Capgemini
• Customer Transformation, Corporate: Seidor
• Customer Transformation, Partner-Led Territories: Tano Digital Solutions
• Rising Star: KPMG
• 麻豆原创 Store: Planon
• Partner Solution Success 鈥� Best Solutions Extensions Performance: OpenText
• Innovative Solution Extension 鈥� Growth: BlackLine
• Corporate Social Responsibility: Seidor

Asia Pacific (APAC)

• Customer Transformation, Corporate: PwC
• Customer Transformation, Large Enterprise: Accenture
• Customer Transformation, Partner-Led Territories: NTT DATA Business Solutions
• Delivery Quality: Abeam Consulting
• Partner Learning and Skills Growth: Infosys
• RISE with 麻豆原创 Methodology: Deloitte
• 麻豆原创 Cloud ERP, New Customer Acquisition: Citek Technology Joint Stock Company
• 麻豆原创 Cloud ERP, Installed Base Transformation: PwC
• Rising Star: KPMG
• 麻豆原创 BTP Extensibility with 麻豆原创 Build and Clean Core: Accenture
• 麻豆原创 Business Data Cloud Success: Accenture
• 麻豆原创 Business AI, Partner Innovation 鈥� AI Cloud Application: Deloitte
• 麻豆原创 Business AI, Partner Innovation 鈥� Customer AI Use Case: ASPN CO, LTD.
• 麻豆原创 Business AI, Customer Adoption: EY
• 麻豆原创 Store: Qualtrics
• Business Transformation Management, Excellence: DyFlex Pty Ltd
• 麻豆原创 Business Suite Success: PwC
• Partner Solution Success: OpenText
• Sustainability: Deloitte
• Managed Service Provider, Top Performance: Accenture
• Procurement Transformation Sales Excellence: ABeam Consulting
• Finance Transformation Sales Excellence: PwC
• Customer Experience Sales Excellence: PT Eclectic Consulting
• Supply Chain Management Sales Excellence: PwC
• Human Capital Management Sales Excellence: Deloitte
• Regional Strategic Services Partner: ABeam Consulting

Dina Blasi is a global partner marketing director, leading partner awards and recognition at 麻豆原创.

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

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

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

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

Building the foundation for enterprise-grade AI

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

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

Modernizing the business logic that runs the enterprise

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

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

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

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

Connecting AI to business operations

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

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

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

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

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

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

Experience agentic AI at NVIDIA GTC

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

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

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

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

.

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

麻豆原创 has restructured the award recognition to provide more meaningful distinction, reflect our partners鈥� essential contributions, and ensure all award categories align to the Partner Ecosystem Success strategy. The newly created 麻豆原创 Partner Awards replace previous recognition programs, including the 麻豆原创 Pinnacle Awards, the 麻豆原创 Global LoB Partner Excellence Awards, and the 麻豆原创 Regional Partner Excellence Awards.

麻豆原创 partners are an essential extension of our team, driving success throughout the Customer Value Journey and helping our customers bring out their best. We rely on our partners鈥� unique industry expertise, implementation methodologies, and complementary solutions to meet the specific needs of customers, especially as they transition to the cloud and embed artificial intelligence (AI) into their business practices.

To exemplify our ongoing commitment to partners, our new awards framework continues the tradition of rewarding outstanding achievements and excellence. These awards recognize significant partner contributions in market units, regionally, and, most prestigiously, at the global level.

We are pleased to announce the . Only 23 partners are recipients of this esteemed award. These influential partners have illustrated the ability to help customers thrive through innovative services, products, and solutions.

The 2026 麻豆原创 Partner Awards recognize 50 categories globally and are based on performance from January 1, 2025 to December 31, 2025. As in previous years, selections were determined using system-generated data on core weighted metrics and key performance indicators. A steering committee of global 麻豆原创 representatives then viewed, vetted, and ranked the achievements according to internal criteria aligned with 麻豆原创鈥檚 communicated business strategies.

Recipients will be celebrated during and and will be invited to exclusive networking opportunities with peers and 麻豆原创 leadership. These partners will also receive a communication package to help promote their success. To further amplify this achievement, 麻豆原创 will list winners on its website for a year and through its communication channels to maximize global exposure to prospects and customers.

Congratulations to the 2026 . We look forward to applauding your success at and .

Karl Fahrbach is chief partner officer at 麻豆原创.

For the opening, Andre Bechtold, president, 麻豆原创 Industries & Experiences, addressed the network partners with a warm welcome and underlined the strategic value of partners for 麻豆原创 and its global customer base. These partners are front-runners of the human-centered approach to innovation, exploring and designing solutions with and for customers built with latest 麻豆原创 technologies such as 麻豆原创 Business AI.

It鈥檚 all about openness, collaboration, and storytelling

During a fireside chat, Dennis Kecskemeti, head of 麻豆原创 Innovation Experience, Paul Saunders, head of 麻豆原创 Customer Outcomes & Advocacy, and Andreas Wendel, head of Innovation Experience Services, answered questions asked by moderator and head of Customer Engagement Services MEE, EMEA, and APAC Kathrin Tarnai-Sindl.

All three guests had brought a personal object with a special connection to 麻豆原创 AppHaus. Interestingly, two brought their mobile phones, but for very different reasons: for one it was the device to listen to audio stories when traveling or commuting, for the other it was a multifunctional gadget to do private calls when traveling, listen to music, and much more. The third guest brought a handball to remind everyone that all good things only work out when teams work together and collaborate. So, their central describing words for 麻豆原创 AppHaus were storytelling, openness, creativity, multifunctionality, and collaboration.

With the new integrated approach, the closer interplay of 麻豆原创 AppHaus, 麻豆原创 Experience Centers, and co-innovation services will provide one continuous experience journey in an end-to-end context. 麻豆原创 AppHaus is where problems are framed and ambition is created in a human-centered, exploratory, and strategic way. 麻豆原创 Experience Centers translate that ambition into tangible value narratives, showcasing what鈥檚 possible with 麻豆原创, 麻豆原创 Business AI, and 麻豆原创 Business Suite. Co-innovation services turn inspiration into execution by piloting, validating, and scaling real solutions with customers and partners. Together, all three form a closed loop from challenge, vision, and experience to solution and impact.

“Each service within 麻豆原创鈥檚 innovation experience is strong on its own. But their real power emerges through connection and collaboration. By bringing 麻豆原创 AppHaus, 麻豆原创 Experience Centers, and co-innovation together, we are shaping a new way for customers and partners to work with 麻豆原创, turning ambition into confidence and inspiration into lasting impact.”

Andreas Wendel, Head of 麻豆原创 Innovation Experience Services

麻豆原创 AppHaus Network members came together in Walldorf

The event agenda offered different working sessions and formats for strategic alignment, exchange on experiences in customer projects, joint marketing efforts, mergers and acquisitions, enablement, and feedback rounds on . On top of that, there was room for networking and excursions. After hours of exchange in discussions, work groups, and sessions, the group of about 30 partner representatives visited the S.Factory, S.Mart, and 麻豆原创 Experience Center. A fun bowling competition, a scavenger hunt across the Walldorf campus, and a quick glimpse at the construction site of the future 麻豆原创 AppHaus Walldorf rounded out the event experience and left the partners with a comprehensive update on all things 麻豆原创 related.

“During this year鈥檚 麻豆原创 AppHaus Network meet-up we focused on shaping our collaboration model for the future, on further improving our co-innovation methods together, and on learning about our different strategic needs and priorities. It is so valuable to meet the 麻豆原创 AppHaus members鈥� representatives in person and have this lively exchange! And let鈥檚 not forget, this year it is about building bridges between our new sister teams within 麻豆原创鈥檚 innovation experience and the global 麻豆原创 AppHaus Network partners.”

Svenja Mueller, Customer Engagements MEE, EMEA, APAC, and Co-Lead of the 麻豆原创 AppHaus Network

About 麻豆原创 AppHaus Network听

For more than a decade, 麻豆原创 AppHaus has collaborated closely with a growing network of more than 20 partners around the world. They have established their own 麻豆原创 AppHaus locations and are fully trained in 麻豆原创鈥檚 human-centered approach to鈥痠nnovation. Together, all members work to drive co-innovation projects with customers, using cutting-edge 麻豆原创 technologies such as 麻豆原创 Business AI, Joule, agentic AI, and many more. It is about very timely enablement of all members in train-the-trainer formats to explore and design business use cases in customer workshops. Latest examples include the 麻豆原创 Learning Journey and other formats, tools, and methods offered in the specialized .鈥�

This allows all 麻豆原创 AppHaus Network members to act as agile front-runners and co-innovation experts. They support customers regardless of their digital maturity, guiding them to unlock tangible business value around the world along鈥�.

Imke Vierjahn is communications lead for 麻豆原创 AppHaus.

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

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

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

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

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

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

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

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

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

Photography courtesy of Norbert Steinhauser.

Updated March 2, 2026

Usually in the cloud, 麻豆原创 partners provide implementation and operations services that complement 麻豆原创 cloud services. In such scenarios, partners utilize support services from 麻豆原创 on behalf of the joint customer. Typical scenarios include, for instance, requesting support for a technical issue by creating a support case with 麻豆原创 or leveraging 麻豆原创 Cloud ALM in an implementation project.

As partners regularly request support, 麻豆原创 closely collaborates with its partner ecosystem along all dimensions of support and equips partners with the tools, insights, and self-services they need to deliver consistent, high鈥憊alue services alongside 麻豆原创. This includes:

• Best practices for partners to self-sufficiently handle common consulting and 鈥渉ow-to鈥� questions from customers
• Data insights and dashboards, such as the customer insights dashboards and Support Collaboration Analytics (for partners) in 麻豆原创 for Me, to help monitor performance, identify trends, and proactively realize quality improvements
• Best practice guidance embedded in 麻豆原创 Cloud ALM with the opportunity for partners to enhance process content and methodologies represented in the solution
• Support Accreditation training that can guide partners to efficiently engage 麻豆原创 for support
• Enabling transparency on partner action on customer鈥檚 behalf through dedicated partner S-users

Partner selection based on trusted support expertise

Customers can now receive higher value from partners with trusted support expertise. Partners that have built strong capabilities for an effective support collaboration can accelerate project execution and reduce risks. For example:

• Partners that self-sufficiently address customers鈥� consulting and 鈥渉ow-to鈥� questions can resolve inquiries much faster, as it avoids involving 麻豆原创 in the process.
• Partners that use 麻豆原创 self-services or automatic responses to support inquiries as the default without creating redundant cases can minimize delays and disruptions.
• Partners that effectively follow 麻豆原创鈥檚 best practices, for example in 麻豆原创 Cloud ALM and the 麻豆原创 Activate methodology, can be better equipped to help mitigate project risks and escalations.

Customers are therefore encouraged to review partners鈥� support capabilities when selecting and working with partners. Effective partners apply 麻豆原创 support best practices to help resolve issues and self-sufficiently handle customers鈥� consulting and 鈥渉ow-to鈥� inquiries. As a target for showing trusted support expertise, no more than 30% of partner-created support cases should fall into these categories. High-performing partners will establish standard operating procedures and continuously optimize service delivery by leveraging 麻豆原创鈥檚 data-driven support insights. Such partners also engage more efficiently with customers and 麻豆原创 by speaking the same language because consultants are qualified on support offerings, channels, and best practices through the Support Accreditation training. They can also deliver best practice-based implementations by applying 麻豆原创 guidance available through 麻豆原创 Cloud ALM.

To simplify partner selection, also based on their trusted support expertise, 麻豆原创 will show such qualified partners in 麻豆原创 Partner Finder from March 2026 onwards.

As a prerequisite for showing such trusted support expertise, customers need to ensure their partners are working with partner S-users.

Customer action recommendations to realize incremental value when engaging partners

When seeking a partner, select those with trusted support expertise, visible from March 2026 onward in through a support proficiency designation.

When working with your partner, enable transparency by authorizing partner S-users for support case handling via the and leverage the in 麻豆原创 for Me for transparency on partner support collaboration effectiveness.

Jens Bernotat is head of Strategy, Portfolio, and Ecosystem Management for Global Customer Support at 麻豆原创.
Marcus Blaesi is head of Global Ecosystem Programs for Global Customer Support at 麻豆原创.

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

A framework designed around partner and customer needs 

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

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

Integration certification and the new interoperability review 

Our refreshed framework offers听two clear paths for partners.

Integration certification (use-case based) 

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

Interoperability review (open and inclusive) 

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

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

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

How this benefits partners and customers听听

For partners:

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

For customers: 

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

Looking forward 

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

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

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

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

Digital sovereignty for healthcare

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

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

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

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

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

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

Visit the . Get 麻豆原创 news via  and .

Media contact:
Dana Roesiger, +49 62277 7 63900, dana.roesiger@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com

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

The partnership will embed artificial intelligence at the core of Syngenta鈥檚 enterprise, modernizing operations and enabling accelerated innovation through advanced data analytics across the business 鈥� from manufacturing and supply chain to grower-facing products and services.

The agricultural industry continues to navigate challenges driven by climate variability, supply chain complexity and global uncertainty. By deploying AI-assisted tools enterprise wide, this partnership positions Syngenta to meet the challenge of feeding a projected 10 billion people by 2050 while unlocking faster innovation, stronger operational resilience and scalable impact across the business.

鈥淎I is the catalyst for agricultural transformation and has quickly become a core competitive edge for Syngenta,鈥� said Feroz Sheikh, chief information and digital officer at Syngenta Group. 鈥淥ur partnership with 麻豆原创 is transforming how we run the enterprise, modernizing core operations and unlocking new ways to work 鈥� a testament to our commitment to becoming an agriculture company with AI at its core.鈥�

鈥淪yngenta鈥檚 transformation sets a benchmark for digital innovation in agriculture,鈥� said Philipp Herzig, chief technology officer at 麻豆原创 SE. 鈥淭ogether, we鈥檙e demonstrating how cloud and AI technologies can drive sustainable growth and efficiency in one of the world鈥檚 most critical industries. This partnership will help Syngenta future-proof its operations to feed the world responsibly.鈥�

Scaling an AI-First Operating Model for Agriculture

Syngenta鈥檚 transformation will begin with鈥槎乖� Cloud ERP Private solutions, modernizing core operations across the value chain to deliver agility, resilience and scalability. The company鈥檚 ambition is clear: unlock innovation faster, strengthen its leadership in agriculture and future-proof operations against volatility.

Through the 麻豆原创 Business Data Cloud solution, Syngenta will create a unified, more secure and scalable data foundation essential for real-time decision-making and AI integration. Combined with 麻豆原创 Business AI and AI-assisted tools such as the Joule copilot, this will help the company explore smarter, faster decisions that drive operational efficiency and accelerate innovation. Additionally, Syngenta will be able to deliver better products and services to growers worldwide while enabling them to retain control and privacy over their proprietary information.

Visit the . Get 麻豆原创 news via  and .

Media contacts:
Lesa Plingen, +49 622 776 9000, lesa.plingen@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com
Syngenta Media Relations, media@syngentagroup.com

Top image courtesy of Syngenta

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

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BITZER, a听global leader in heat and cooling technologies, partnered with NEURA Robotics and 麻豆原创 to showcase the potential of cognitive robots powered by embodied AI from 麻豆原创 to transform and streamline warehouse operation.

.

This is where 麻豆原创 and the 麻豆原创 partner ecosystem make a decisive difference.

Together, we help customers translate AI strategies into meaningful outcomes by pairing partner industry expertise with听麻豆原创 Business AI, which brings hundreds of purpose-built, domain-rich capabilities embedded across 麻豆原创 applications. These capabilities help automate processes, elevate decision-making, and enhance employee productivity across the enterprise.

麻豆原创 Business Technology Platform (麻豆原创 BTP) amplifies this foundation by giving customers the ability to integrate, extend, and build AI-powered solutions in a scalable and secure environment.

Across industries, 麻豆原创 and our partners are helping customers unlock real value from AI. The examples below show how organizations are already achieving tangible impact today.

Driving efficiency with AI-powered process automation

Manual, repetitive processes remain one of the biggest barriers to operational excellence. The 麻豆原创 partner ecosystem plays a critical role in helping customers uncover these inefficiencies and redesign them with AI-driven automation.

For frozen-food manufacturer听FRoSTA, 麻豆原创 partners听sovanta AG,听and听Amista听identified invoice processing as a major bottleneck. By orchestrating the workflow using听麻豆原创 Build Process Automation听and extracting, interpreting, and validating data through听麻豆原创 Document AI, the partners were able to . Invoices that once required several minutes of manual effort now flow through the system in under a minute, with roughly 60 percent fully automated. Employees can redirect their attention to higher-value work, such as resolving exceptions and collaborating with suppliers.

This is the power of pairing partner expertise with 麻豆原创 Business AI and 麻豆原创 BTP solutions: Organizations quickly shift from isolated task automation to connected, intelligent workflows that scale across departments and regions. What begins as a single use case becomes the foundation for a broader automation strategy鈥攁ccelerating processes, reducing manual effort, and tightening the connection between data, people, and decisions.

Accelerating innovation by making AI accessible to every team

As demand for AI grows, many organizations face a familiar hurdle: the scarcity of specialized AI talent. Partners in the 麻豆原创 ecosystem help close this gap by combining their industry knowledge with tools in 麻豆原创 Business AI and 麻豆原创 BTP that make it easier for teams across the business to experiment, prototype, and deploy AI solutions at speed.

A strong example comes from Aspen Pumps, which partnered with NTT DATA听to . Using low-code capabilities from听麻豆原创 Build to design and orchestrate workflows and 麻豆原创 AI Core to power AI models, the team rapidly developed a series of automation bots鈥�12 in total. These now streamline activities such as invoice validation, order routing, and even interpreting CAD drawings to accelerate quote creation. Many proof-of-concept initiatives were completed in under a week, demonstrating how accessible innovation becomes when intelligent capabilities are built directly into the tools teams already use.

By lowering the barriers to experimentation, 麻豆原创 and partners help organizations innovate faster and more confidently. Teams can explore new ideas, test them safely, and scale what works鈥攚ithout waiting for scarce technical resources or lengthy development cycles. Innovation becomes a daily practice, not a specialized activity reserved for a few.

Building a future-ready foundation with scalable, extensible architecture

As AI becomes more deeply integrated into business operations, leaders are prioritizing platforms that will scale with them, not constrain them. This is where 麻豆原创 partners help customers design architectures that can evolve with changing market needs while preserving the stability of their core systems.

Steel manufacturer听Al Ghurair Iron and Steel (AGIS)听offers a powerful example. Working with听Deloitte, the company using 麻豆原创 Business AI embedded in 麻豆原创 S/4HANA Cloud, private edition, combined with the integration and extension capabilities of 麻豆原创 BTP. A planning cycle that once required 15 minutes of manual coordination now takes less than five. The solution has been replicated across multiple locations, and more than 400 calculations are now automated, giving teams more time to analyze results and optimize operations rather than manage spreadsheets.

When 麻豆原创 Business AI and 麻豆原创 BTP come together with partner expertise, companies gain a foundation they can rely on as their AI ambitions grow. They can scale new capabilities across plants, regions, or business units; extend processes without disrupting mission-critical systems; and seamlessly connect 麻豆原创 and non-麻豆原创 environments into a cohesive, intelligent landscape.

Turning AI potential into business transformation

These stories demonstrate what becomes possible when customers, 麻豆原创, and our partners work together: faster processing, smarter decisions, empowered employees, and architectures built for long-term agility and growth.

With the combined strength of the 麻豆原创 partner ecosystem, the domain-rich intelligence of 麻豆原创 Business AI, and the extensibility of 麻豆原创 BTP, organizations can move beyond pilots and embed AI where it matters most: in the daily processes and decisions that run their businesses.

Learn more about what’s possible for your business with 麻豆原创 Business AI at .

麻豆原创 now unites all existing milestones under a single strategic framework: a sovereign AI and cloud offering designed for Europe. 麻豆原创 now offers a truly full-stack sovereign cloud offering, empowering customers to select the right level of sovereignty and deployment for their needs, whether in 麻豆原创鈥檚 own data centers, on trusted European infrastructure or as a fully managed solution on-site.

EU AI Cloud supports EU data residency and full sovereignty, helping ensure that every organization can meet its unique regulatory and operational requirements.

Cohere: Unlocking Sovereign, Agentic and Multimodal AI Capabilities for European Enterprises

麻豆原创 and Cohere are joining forces to deliver frontier agentic AI capabilities with Cohere North, extending existing state-of-the-art multimodal AI capabilities through EU AI Cloud and sovereign offerings. Cohere North will be integrated into 麻豆原创 Business Technology Platform (麻豆原创 BTP), enabling customers with data residency constraints across industries to build robust, production-ready AI into their core business processes. Together, 麻豆原创 and Cohere will help enterprises unlock deeper insights, more accurate decision support and more intelligent automation across complex workflows without compromising on sovereignty, compliance or performance.

A Strong and Growing Ecosystem

EU AI Cloud is powered by a strong and growing ecosystem of leading European and global partners. By integrating advanced AI models and applications from partners such as Cohere, Mistral AI, OpenAI and others directly into 麻豆原创 BTP, EU AI Cloud delivers a pathway for building, deploying and scaling AI-powered applications. Customers can consume these partner offerings as SaaS, PaaS or IaaS, and deploy them flexibly across 麻豆原创鈥檚 own infrastructure or trusted European partners.

This collaborative approach ensures that European enterprises and public sector organizations benefit from the latest AI innovations securely, in full compliance with European standards and with the sovereignty and flexibility they require.

Deployment Choices for Every Security Profile

EU AI Cloud offers flexible deployment through 麻豆原创 Sovereign Cloud, giving customers full control across infrastructure, platform and software tailored to their regulatory and operational needs. AI models run on 麻豆原创鈥檚 software abstraction layer (麻豆原创 Cloud Infrastructure + 麻豆原创 BTP) in European data centers, ensuring compliance and independence from U.S. hyperscalers.

• 麻豆原创 Sovereign Cloud on 麻豆原创 Cloud Infrastructure (EU): 麻豆原创鈥檚 Infrastructure-as-a-Service (IaaS), developed with open-source technologies and operated within 麻豆原创鈥檚 European data center network. All data remains within the EU to ensure compliance with European data protection regulations.
• 麻豆原创 Sovereign Cloud On-Site: 麻豆原创-operated infrastructure offering within a customer-owned or customer-selected data center. It provides the highest levels of data, operational, technical and legal sovereignty while maintaining 麻豆原创 cloud innovation and architecture.
• Selected Hyperscalers per Market: For customers that choose to run 麻豆原创 commercial SaaS on global cloud providers, with sovereignty features as required.
• Delos Cloud: A secure and sovereign cloud solution in Germany, designed to support the public sector鈥檚 transformation and meet country-specific sovereignty requirements.

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About 麻豆原创

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

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