Demand for professionals who can build, govern, and orchestrate these agents is rising faster than supply, making graduates with hands-on agent-building experience among the most sought-after profiles in today’s job market.

This year at 麻豆原创 Sapphire, 麻豆原创 laid out its vision for the Autonomous Enterprise, where AI agents manage and execute business processes end to end. For universities, this raises an immediate question: How do graduates get ready for a world where AI agents are part of daily operations?

麻豆原创 is now providing new no-cost offerings and resources for universities that give lecturers and students hands-on access to AI agent building, process management, and enterprise architecture tools. The goal is to help higher education keep pace with the rapid adoption of agentic AI in industry and prepare graduates for a changing job market.

Preparing the next generation of AI agent builders

麻豆原创 has put together a new set of offerings and resources that help universities embed agentic AI-related concepts and technology into their teaching hands-on. Three offerings, each covering a different angle of agentic AI, are now accessible at no cost for academic lecturers and their students:

• : Before building an agent, the process it will operate in must be understood. 麻豆原创 Signavio Process Transformation Suite gives lecturers and their students access to process mining, modeling, and process transformation capabilities. They can model and analyze existing processes, spot inefficiencies, and design improved workflows that include AI agents. Additionally, students and lecturers can now experience process modeling with 麻豆原创 Signavio Process Modeler as part of 麻豆原创 Learning Hub, student edition.
• : For students to understand where agents sit within an organization’s IT landscape, this is the tool. Newly available at no cost for academic lecturers via 麻豆原创 Learning Hub, student edition, 麻豆原创 LeanIX lets students model enterprise architectures and reason about what changes when introducing AI agents into an existing system landscape.
• : Lecturers and their students can access an agent-building environment from 麻豆原创 and leverage various enablement resources. These allow students to explore configuring and building an AI agent, either in a guided demo experience or in a live system hands-on.

What makes this especially valuable is how the pieces connect. Students can explore different components of agentic AI hands-on using 麻豆原创 solutions. They learn that building an agent is only part of the job. Understanding process context, architectural and governance implications is equally important.

Collaboration with educational institutions globally

麻豆原创 will also collaborate intensively on embedding agentic AI into teaching with lecturers from more than 10 universities globally, including:

• Budapest University of Technology and Economics, Hungary
• E枚tv枚s Lor谩nd University, Hungary
• Hasso Plattner Institute, Germany
• HEC Montr茅al, Canada
• Karlsruhe Institute of Technology, Germany
• National University of Singapore Business Analytics Centre, Singapore
• TEC de Monterrey, Mexico
• Technical University of Munich, Germany
• Tongji University, China
• Technical University of Dresden, Germany
• University of California, Irvine, U.S.

The institutions will get exclusive early access to 麻豆原创’s latest agent building platform capabilities, benefit from agent building deep dives for students with 麻豆原创 experts, and from the opportunity to articulate academic needs with regards to teaching agentic AI related concepts hands-on to 麻豆原创.

鈥淲e want students to work with the same tools and scenarios that companies are using right now,鈥� Dr. Katharina Schaefer, head of Academic Partnerships at 麻豆原创, said. 鈥淏y giving lecturers free access to our agent-building resources, we make it easy for them to bring that reality into their courses. Students who build AI agents on real enterprise processes during their studies will have a head start when they enter the job market.鈥�

For faculty, the practical element is what counts. Students do not just read about AI agents in a textbook. They build them on real systems with real constraints.

“What excited me is that students get to work with enterprise-grade tools, thanks to this new platform,” said Prof. Jes煤s Aguilar-Gonzalez, TEC de Monterrey. “Students from our School of Engineering & Sciences build agents connected to real business processes and have to think about architecture and governance. That is much closer to what they will face in their first job than any textbook exercise.”

What sets this apart is its enterprise context: Agentic AI is taught in connection with business processes and the system landscape that supports them, so students learn how AI fits into real operations rather than experimenting in isolation.

Building the workforce of the future

As part of the , 麻豆原创 has been partnering with more than 2,800 educational institutions for decades to enable students to learn, research, and innovate with business applications and technology. With these offerings, 麻豆原创 supports students in developing sought-after 麻豆原创 skills, preparing them for job opportunities worldwide.

Ready to bring agentic AI into your classroom? Visit the or reach out via universityalliances@sap.com to get started.

Demand shifts quickly, supply networks are more exposed to disruption, cost and margin pressure remain constant, and the decisions that determine whether a company can respond with confidence rarely sit inside one function.

The enterprise is left with a critical question: How do you move fast enough to capture opportunity without putting fulfillment, margin, or customer trust at risk?

Many of the world鈥檚 largest organizations navigate this challenge on a regular basis. It is exactly the kind of moment that exposes the limits of how enterprises currently operate. Connecting the dots across functions, systems, and decisions still takes too much time, too much manual effort, and too much stitching across fragmented landscapes. By the time teams have gathered the data, aligned the functions, modeled the trade-offs, and agreed on a response, the environment has already shifted.

This is why we introduced the Autonomous Enterprise at 麻豆原创 Sapphire. The goal is to sense change earlier, understand its impact across the enterprise, coordinate the right response, and keep people in control of important decisions. This is a fundamental shift in how businesses can operate: intelligence that is continuous, decisions grounded in real-time context, and an enterprise that moves as a connected system rather than a collection of disconnected parts.

Autonomy at scale

An Autonomous Enterprise is an organization that can continuously sense what is happening across its operations, reason over those signals using business context and established rules, and act across end-to-end processes without depending on manual coordination at every step. AI assistants and agents advance work across the enterprise in alignment with the goals, policies, and constraints defined by humans.

Every AI-driven action is auditable and traceable. Human judgment is deliberately embedded in decisions that require accountability and exceptions that fall outside defined parameters.

Three principles underscore the Autonomous Enterprise:

1. Process knowledge: Deep, industry-specific understanding of how a business truly runs
2. Business data: Enriched, connected, contextual data that gives AI something real to work with
3. Governance: The backbone that keeps everything upright, traceable, and within policy

Beneath it all is the 麻豆原创 platform, ensuring every layer works in concert, every agent operates within guardrails, and every outcome can be traced back to a decision made by a human.

Intelligence that works across the business

The average business landscape probably doesn鈥檛 look like one system, one vendor, or one clean stack. Your processes still have to run end to end across all of it: record to report, plan to make, source to pay, hire to retire, order to cash. If AI is going to work in the enterprise, it has to work across this landscape, not inside one application or vendor boundary.

IDC shows that more than 50% of business decisions still take between one and seven days. That is the gap we are closing鈥攆rom days to moments.*

At the core of the Autonomous Enterprise is the 麻豆原创 Autonomous Suite. Joule becomes the way you interact, as a single entry point into your business. In the middle, the 麻豆原创 Autonomous Suite connects your core domains: finance, supply chain, spend, HCM, and customer experience. And underneath, everything is grounded in your business context, your data, your processes, your rules, your governance.

With 麻豆原创鈥檚 unified foundation of applications, data, and business context, AI is embedded directly into how work gets done, enabling autonomous, end-to-end execution rather than isolated use cases.

The operating model behind this is built on a clear division of responsibility: people set priorities, policies, and guardrails. Assistants understand role and process context and coordinate activity across domains. Agents carry out the defined work, detecting signals, triggering actions, and resolving routine tasks continuously in the background.

And while automation is a part of this, the bigger shift is intelligence and optimization. The system is no longer following predefined workflows. It is using business context to understand what is happening, and what should happen next. This is the shift from systems of record to systems that help run the business.

Autonomous Finance shows what changes

Finance offers a clear example of how this model changes the work itself. Many finance organizations still contend with manual steps, fragmented data, and slow cycles. In a volatile environment, that lag translates directly into slower responses to risk, missed opportunities, and diminished confidence in the decisions that shape performance.

With Autonomous Finance, more of that work can be handled by the system, allowing finance teams to spend less time chasing numbers and more time shaping decisions. The function begins to move from reconciling the past to shaping the future.

Autonomous Finance is not one capability, one agent, or one use case. It is built across the entire finance process, from planning to revenue management, treasury, closing, compliance, and tax. Within each area, assistants are supported by specialized agents working continuously in the background. Some focus on forecasting, some on billing, some on cash, and some on closing. The important point is that these capabilities are connected, so decisions in one area can flow into the others. Connected assistants, specialized agents, continuous optimization. That is the model.

The impact across these areas compounds. Finance teams reclaim meaningful capacity as manual reporting, reconciliation, and transaction processing give way to continuous intelligence. Cash cycles compress. Close timelines shorten. Forecasting becomes more accurate and more responsive to changing conditions.

Because these capabilities are connected, improvements in one area reinforce the others: faster billing flows into better cash visibility, which flows into stronger planning confidence, which flows into more decisive action at the executive level. Compliance strengthens as well, not through added controls, but through better intelligence embedded in the process itself, supporting requirements across ISO, SOC, and SOX with greater accuracy and less manual effort.

The result is not incremental improvement in isolated tasks. It is a fundamentally different operating posture for the finance function, one where the system handles orchestration and people direct outcomes.

Industry AI adds depth

Autonomous domains give breadth across business functions, while Industry AI provides the depth of knowledge. The same supply chain problem looks very different in life sciences, in industrial manufacturing, in agribusiness, in retail, or in energy. The rules, regulations, data models, and value chains are different.

麻豆原创 is not starting from generic AI and trying to teach it how an enterprise works. We start with decades of industry and process knowledge, already embedded in the systems that run the world鈥檚 most complex businesses. Our AI is grounded in sector-specific processes, end-to-end value chains, operational realities, and compliance requirements. And our ecosystem extends this with specialized expertise, so organizations can adapt the intelligence to their markets and their industries.

This is not AI for the sake of AI. This is AI applied to the real operating model of each industry.

The path forward

That is the real shift: not AI operating in isolated tasks, but AI helping the enterprise continuously sense, reason, act, and learn. People remain in control throughout, while the system handles the orchestration required to bring together the right data, context, and decision at the right moment.

The Autonomous Enterprise marks a shift from managing processes to directing outcomes. It moves organizations from reacting to events to anticipating them, and from stitching together decisions after the fact toward helping the business move as one connected system.

This does not require waiting for a perfect, fully transformed landscape. Organizations can begin by applying AI on top of existing landscapes and evolving their business as they go. That work is already underway with many of our customers. What they have in common is that they are starting now, moving faster, making better decisions, and building the foundation for a more autonomous enterprise, step by step.

This is a journey. And it begins with the recognition that the enterprise of the future will not be defined by how efficiently it executes predefined processes, but by how intelligently it can sense change, weigh trade-offs, and move with confidence when it matters most.

For more on 麻豆原创鈥檚 broader Autonomous Enterprise announcement, read The Future of the Enterprise Is Autonomous. For more details on 2026 麻豆原创 Sapphire announcements, see the .

Manoj Swaminathan is general manager and chief product officer of 麻豆原创 Autonomous Suite, Finance & Spend, and member of the Extended Board of 麻豆原创 SE.
Eric van Rossum is chief marketing officer of 麻豆原创 Global Product Marketing and chief product officer of 麻豆原创 Industries and Globalization.

*IDC Resource Map for 麻豆原创, 麻豆原创 Custom Survey 2026: Enterprise Process Automation Survey鈥� April 2026, sponsored by 麻豆原创, doc #US54531626 _RMD , May 2026

In today’s dynamic business landscape, characterized by the rise of AI, process intelligence is vital for gaining data-driven insights that boost efficiency, support smarter decision-making, and drive business growth鈥攁nd 麻豆原创 Signavio maintains an ongoing dedication to innovation and customer satisfaction in this arena.

We believe this year鈥檚 evaluation reflects the expanded category definition from Gartner, assessing platforms that unify process mining, task mining, modeling, analysis, optimization, monitoring, automation discovery, and governed repositories within a single, integrated environment.聽

The Gartner庐 Magic Quadrant™ research methodology highlights that “Leaders execute well against their current vision and are well positioned for tomorrow.” 麻豆原创 Signavio has been recognized as a Leader among 16 vendors, evaluated based on its Ability to Execute and Completeness of Vision.

“Our aim is to help our customers create a repeatable, sustainable transformation capability, rather than treating it as a series of independent projects,鈥� Dee Houchen, chief marketing officer at 麻豆原创 Signavio, said. 鈥漌e believe process intelligence is fundamental to what this approach can deliver for organizations today, driving greater enterprise observability, smarter decision-making, accelerated transformation, and measurable business outcomes. With 麻豆原创聽Signavio, this is made possible through one unified聽suite,听empowered聽by deep AI capabilities,听as well as intelligent聽agents聽and assistants.聽We are proud of being recognized as a Leader by Gartner, and feel this reaffirms our ongoing commitment to innovation and customer satisfaction, with value realization as our guiding principle.鈥�

As ever, the Gartner report provides useful context regarding the state of the process intelligence market. See why we feel we were recognized as a Leader in the report:

• Our innovative process atoms concept serves as the AI-ready foundation for business transformation, gathering and curating an AI-consumable layer of 鈥渃ompany memory鈥� that can provide the precise, contextual process knowledge AI agents need in order to take informed action.
• Our technology, approach, and value accelerators help achieve full enterprise observability and surface actionable insights with an end-to-end integrated suite, supporting organizations to identify, prioritize, and prove the value of your transformation initiatives, track and showcase ROI, and maximize business impact.聽

The Gartner Magic Quadrant equips businesses with valuable insights to make informed decisions. For a complimentary copy of the latest resource featuring 麻豆原创 Signavio solutions (Gartner, Magic Quadrant for Process Intelligence Platforms, by聽,听,听, 5 May 2026), visit .

Lucas de Boer is global marketing program lead for 麻豆原创 Signavio.

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

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�

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

The foundation of the autonomous enterprise is the 麻豆原创 Business AI Platform, which infuses AI with the process knowledge, data, and governance organizations depend on. 

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

Business Transformation Management solutions from 麻豆原创 help deliver the promise of the autonomous suite. Here鈥檚 how.

麻豆原创 Agent Hub: Command center for agentic governance

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

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

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

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

New AI capabilities

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

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

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

Looking ahead to a new paradigm

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

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

At 麻豆原创 Signavio we call this storehouse 鈥渃ompany memory.鈥� Company memory, comprised in part of process atoms, captures all the knowledge of operational practices, business rules, preferences, and more so that it can be accessed by agents as needed to check conformance and change behavior.

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

Business transformation never stops

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

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

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Andre Wenz is chief product officer of 麻豆原创 Signavio.
Dominik Rose is chief product officer of 麻豆原创 LeanIX.

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

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

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

At 麻豆原创, stories like these inspire our vision for the enterprise in which AI transforms how people and processes work鈥攐ne where people set the direction and AI executes. We call it the the Autonomous Enterprise.

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

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

Joule: One place to direct the entire business

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

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

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

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

麻豆原创 Autonomous Suite: The operational core of the modern enterprise

While Joule Work empowers every individual to do their best work and expand their impact, the 麻豆原创 Autonomous Suite transforms how entire business functions, or 鈥渁utonomous domains,鈥� work.

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

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

Each organization is also unique. Over time, your business has defined how your work gets done. These are the rules, workflows, and how systems respond when something unexpected happens, like a failed transaction, so processes don鈥檛 break. In the Autonomous Enterprise, AI delivers its greatest value by respecting these boundaries, turning your unique ways of working into a true advantage.

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

麻豆原创 Business AI Platform: The foundation of the Autonomous Enterprise

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

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

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

Through deep integration with the , 鈥攁nd the new 麻豆原创 Domain Models trained on 麻豆原创 code, customer data, metadata, and business processes鈥擩oule Agents reason over real, semantically rich enterprise data rather than generic knowledge. 麻豆原创 Domain Models are available through the 麻豆原创 Early Adopter Care program, with general availability planned for Q3 2026.

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

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

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

Empowering everyone to solve business challenges with AI

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

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

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

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

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

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

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

Introducing 麻豆原创 Business AI Platform

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

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

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

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

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

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

Designing the Autonomous User Experience

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

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

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

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

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

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

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

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

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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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The other key characteristic of business transformation: it鈥檚 not going away.

Organizations that ignore the need for change find themselves constantly on the back foot, unable to take advantage of new opportunities, and in an endless loop of reactivity.

But even those businesses that know they need to change fall into a common trap: treating 鈥渢ransformation鈥� as a project, something to be ticked off the list as 鈥渃ompleted,鈥� never to be thought of again. Until the next system-wide shock, that is.

Transformation as a capability

The organizations best placed for success are those that avoid both these approaches. They succeed by building their transformation muscle鈥攖he capacity to run multiple transformations, consistently and concurrently.

Let鈥檚 be clear: for modern enterprises, change is not something that happens as a time-limited or even clearly definable event. Change is much closer to an operational reality, something so intrinsically connected to how businesses work that it can鈥檛 be separated from decisions, processes, and all the other elements that allow an organization to function.

鈥淢ost enterprises run four or more transformations a year. Building a聽repeatable transformation capability聽you can strengthen over time makes all the difference,” Dee Houchen, chief marketing officer for 麻豆原创 LeanIX and 麻豆原创 Signavio, says. “The capacity to adapt and transform is not just a competitive edge, it鈥檚 a basic business requirement. And so, knowing where your transformation strengths and weaknesses lie is critical to ensuring your business can function effectively in today鈥檚 complex environment.鈥�

In other words, effective business transformation is just as important to the way a company works as any other aspect you could name. Organizations with the skills and knowledge to transform repeatedly and at scale, and to flexibly apply those skills and that knowledge in different contexts, will be those that survive and thrive.

So how can you determine whether your business has the right transformation muscles?

Assessing your capability

麻豆原创 has created a quick and easy online tool that can measure your organization鈥檚 transformation capability as it stands right now, so you can make the right decisions to build your business for the future.

Grounded in assessing levels of business transformation management maturity around the globe, the tool uses this data as a baseline to assess transformation capability across five domains: strategy and leadership, applications and technology, process, data, and people.

Using self-reported information about your business, the tool can take less than 10 minutes to benchmark your capability against peers, as well as pinpoint strengths, gaps, and execution risks. But this is not simply a static information-gathering exercise. The tool can set your baseline, helping determine where your organizational strengths and weaknesses are. It鈥檚 up to you to take the next steps.

鈥淭he real value of this tool lies in using it to unlock value in your business,鈥� Houchen says. 鈥淭he baseline is important, but it鈥檚 the targeted, actionable recommendations that can really strengthen your transformation capability.鈥�

鈥淭he tool provides recommendations across critical areas like executive commitment, strategic planning, technology modernization, process optimization, data management, and organizational culture鈥攁nd some you can already start putting in place,鈥� Houchen adds. 鈥淲ithin a matter of months, you can build a robust, repeatable transformation capability, or, if you鈥檙e more advanced already, continue to strengthen that capability and start to expand the possibilities for value-adding through transformation.鈥�

Building your capability

The transformation maturity assessment tool can also go beyond organizational recommendations and can even provide insights on how you can best improve your underlying approach鈥攖he transformation mindset that can help drive future success. The tool can help you explore critical components like:

• The role of strategic commitment in enabling transformation
• Opportunities to modernize your technology foundation
• How processes support value-driven execution
• The best ways to manage transformation data
• How organizational culture supports empowerment and adaptability

鈥淯sing this tool helps ensure your readiness to navigate the complexities of modern business, turning business transformation from a project into a part of the operational fabric of your organization鈥攁 repeatable, scalable competitive advantage,鈥� Houchen says.

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Lucas de Boer is a marketing execution senior specialist at 麻豆原创.

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

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

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

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

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

Some highlights from Q1 2026:

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

Joule

Joule, enhancements

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

To set up, see: , , and .

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

For more information, see .

麻豆原创 Joule for Consultants, enhancements

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

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

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

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

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

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

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

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

Get started .

SECTION

麻豆原创 Business AI for supply chain

Project Setup Agent
Beta release

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

Get started .

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

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

Get started .

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

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

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

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

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

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

Get started .

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

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

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

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

and get started .

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

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

Get started .

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

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

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

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

Get started .

麻豆原创 Business AI for finance

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

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

Get started .

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

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

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

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

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

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

Get started .

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

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

Get started .

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

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

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

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

Get started .

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

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

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

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

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麻豆原创 Business AI for spend management

Expense Report Validation Agent
General availability

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

Get started .

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

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

Get started .

Expense Automation Agent
麻豆原创 Early Adopter Care

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

See the demo .

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

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

Get started .

Policy Navigator
麻豆原创 Early Adopter Care

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

Get started .

麻豆原创 Business AI for procurement

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

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

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麻豆原创 Business AI for customer experience

Catalog Optimization Agent
General availability

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

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

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

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麻豆原创 Business AI for IT and developers

Joule Studio code editor and Joule Studio CLI

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

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

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Joule with 麻豆原创 Datasphere
General availability

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

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麻豆原创 Document AI, enhancements

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

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

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

Generative AI Hub in AI Foundation, enhancements

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

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

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

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

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

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

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

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

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

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

See .

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

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

Get started .

麻豆原创 Business AI for industries

Tender Analysis Agent
General availability

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

Get started .

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

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

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

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

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Joule with 麻豆原创 Intelligent Clinical Supply Management
General availability

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

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

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

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麻豆原创 Business AI for business transformation management

Joule with 麻豆原创 Signavio solutions
General availability

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

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

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

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

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

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

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

Across industries, customers are asking for guidance that is simple, predictable, continuous, and connected to the measurable business outcomes they need.

Ever-focused on customer success, our services and support portfolio coupled with both our robust toolchain and strong team of experts help organizations carve a clearer path to adopt the latest 麻豆原创 innovations, strengthen operations, and transform with confidence in a fast-changing environment.

Enabling faster value realization through continuous transformation

Every organization is working to keep pace with rapid market change. Technology cycles move quickly, expectations rise, and adopting AI requires clear priorities and coordinated execution aligned with business value. They seek ongoing guidance, measurable outcomes, and a partner that supports the transformation journey at every stage.

At 麻豆原创, we understand this. Customers require transparency in how support is delivered, predictable outcomes from their investments, and a simpler way to adopt innovation across their landscapes, especially as artificial intelligence becomes a core operational capability embedded in business processes.

This is why the introduction of the renewed 麻豆原创 Services and Support portfolio arrives at an important moment. It brings clarity to how customers work with 麻豆原创 and offers a consistent experience that supports continuous transformation, not one-time change.

With our renewed 麻豆原创 Services and Support portfolio, we provide [customers] a clearer path to adopt innovation, apply AI responsibly, and run their landscape with confidence.

麻豆原创 Executive Board Member Thomas Saueressig

During the marking the launch of the renewed portfolio, Thomas Saueressig, member of the Executive Board of 麻豆原创 SE, Customer Services & Delivery, captured the purpose of this portfolio in clear terms.

鈥淐ustomers are looking for orientation in a fast鈥憁oving environment,鈥� Saueressig said. 鈥淲ith our renewed 麻豆原创 Services and Support portfolio, we provide a clearer path to adopt innovation, apply AI responsibly, and run their landscape with confidence. It brings structure to continuous transformation and helps turn strategic priorities into measurable outcomes.鈥�

His message reflects what customers expect from 麻豆原创: They want support that is structured, proactive, and unified across the entire environment.

Three success plans designed for measurable business impact

The renewed portfolio introduces three success plans that meet customers where they are. Each plan builds on the previous one and provides a flexible model that scales with organizational needs. Customers can also combine plans across their landscape. For example, they may choose the Advanced Success Plan for the 麻豆原创 SuccessFactors environment while selecting the Max Success Plan to support their AI, data, and analytics strategies.

Foundational Success Plan

Included with every 麻豆原创 cloud solution, this plan enables customers to run their solutions efficiently and maintain business continuity. It supports ongoing value creation through curated content, structured learning, application lifecycle management capabilities, and preventive mission-critical support. It builds on the 麻豆原创 Enterprise Support offering and is expanded with technical operations for cloud solutions and onboarding.

Advanced Success Plan

This plan strengthens teams with specialized expertise. Organizations receive proactive guidance to detect risks early, accelerate innovation, adopt innovations faster, and optimize processes. AI-assisted insights support informed decision-making and activation sessions help refine how new capabilities are used.

Max Success Plan

This plan represents 麻豆原创鈥檚 most strategic level of engagement. It includes all elements of the Advanced Success Plan and adds dedicated success plan managers, cross-solution process improvements, and tailored AI use case adoption. It is designed for enterprises navigating complex transformations or scaling the use of 麻豆原创 Business AI.

Dominique Tessaro, CIO from Vinci Energies, a customer of more than 20 years evaluating the success plans, noted, 鈥淲e need different levels of 麻豆原创 involvement, depending on the solution. Some need higher attention, and others need medium attention with a few extra project-specific services. This flexibility is what I really like about the new success plans. Like a car, I can strategically steer the engagement in the direction that will serve our needs.鈥�

Like a car, I can strategically steer the engagement in the direction that will serve our needs.

Vinci Energies CIO Dominique Tessaro

Accelerating outcomes through simplicity and partnership

The updated portfolio is designed around one principle: to help customers realize value faster and with greater certainty. This means reducing complexity, improving how guidance is delivered, and strengthening the partnership between 麻豆原创 and every customer. It also means helping organizations adopt innovation, including 麻豆原创 Business AI, at the pace that is right for their business.

Beyond the success plans, customers can extend their experience with streamlined professional services, development services, and application management offerings. These provide additional expertise for specialized needs, tailored solution development, and long-term operational resilience. Each offering is grounded in 麻豆原创 product knowledge and industry insight.

This launch aligns customer expectations with a modern engagement model supported by intelligent tooling and human expertise. It provides the structure needed to guide organizations through uncertainty while keeping transformation aligned with strategy and focused on measurable outcomes.

Thomas Pfiester is head of Customer Engagement and Adoption and a member of the Extended Board of 麻豆原创 SE.

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.

Joule is an AI solution that turns siloed data and tasks into intelligent, connected workflows that help improve decisions, speed up end-to-end processes, and create a unified AI experience across 麻豆原创 and non-麻豆原创 systems. With AI agents for all core functions, powered by 麻豆原创 business process expertise, an AI strategy scales faster and wider.

In this context, the unique value of combining Joule with 麻豆原创 Signavio is the powerful combination of deep process context from 麻豆原创 Signavio and orchestration across 麻豆原创 applications, including but not limited to 麻豆原创 S/4HANA, 麻豆原创 Business Technology Platform (麻豆原创 BTP), and 麻豆原创 SuccessFactors solutions.

After months of successful collaboration with customers in the 麻豆原创 Early Adopter Care program, this launch marks a major step toward delivering a conversational experience, making it easier than ever to explore, understand, manage, and transform processes with 麻豆原创 Signavio solutions.

But how does this work in practice? Let鈥檚 look at an example.

Joule in action

Imagine accessing , an organization鈥檚 single source of truth for process alignment, in order to understand more about a particular process, order-to-cash. What once might have taken hours of investigation can now happen in minutes through a simple conversation.

Asking Joule, 鈥淲ho is the process owner of the order-to-cash process?鈥� prompts Joule to suggest the process that most closely matches the query, then retrieve the owner information from the process diagram attributes.鈥�

Following up with 鈥淧rovide me with a description of the process flow鈥� means Joule skills convert the process visual into a clear process description. You can dive deeper into the process as well, perhaps by comparing the difference in process execution in different regions. Just ask, and Joule skills provide a textual summary that highlights the key differences between the two process models.

Joule offers a connected user experience across 麻豆原创 and non-麻豆原创 systems, allowing employees to ask questions and interact with Joule from anywhere. In other words, while working in 麻豆原创 Signavio, users can interact with data and capabilities from other systems, or while in other systems, users can access 麻豆原创 Signavio capabilities.

Simple and seamless

This connectivity and seamless access is designed to simplify day-to-day tasks in multiple ways, and Joule with 麻豆原创 Signavio offers skills across three use cases: informational, navigational, and transactional. Plus, additional analytical capabilities are planned for future releases. As a summary, these use cases鈥攐r interaction patterns鈥攃omprise the following:

• Informational:鈥疛oule acts as an intelligent assistant, helping users understand how to perform specific tasks or generating a textual comparison between processes. For example, ask Joule: 鈥淲hat鈥檚 the difference between draft and published process models?鈥濃�痮r 鈥淗ow can I set up a dashboard?鈥�
• Navigational: Joule simplifies content navigation across 麻豆原创 Signavio solutions and guides users through the 麻豆原创 Signavio Process Collaboration Hub to access various assets such as process and journey models, and value accelerators. For example, prompt Joule: 鈥淥pen the Order-to-Cash process model published for EMEA鈥� or鈥�淔ind accelerators for the Financial Process鈥�
• Transactional: Joule enables users to perform actions conversationally, such as creating and deleting assets within the 麻豆原创 Signavio Process Transformation Suite, including processes, journey models, and dictionary items. For example, tell Joule: 鈥淐reate a new dictionary term and link it to the Returns process.鈥濃�痮r 鈥淒elete the journey model called Sales Process.鈥�

Unlocking value with agentic AI

Right now, Joule works across 麻豆原创 applications as a process companion, meaning that 麻豆原创 Signavio process context and intelligence is accessible to the user across all Joule-compatible applications, including, among others, 麻豆原创 S/4HANA, 麻豆原创 SuccessFactors solutions, and 麻豆原创 BTP. But this is just the beginning.

麻豆原创 is developing Joule Agents embedded into every business function and accessed with role-based assistants, which use 麻豆原创鈥檚 process expertise to automate complex workflows and deliver AI value at scale. Joule Agents for 麻豆原创 Signavio solutions can help accelerate content discovery and process analysis, create value cases, and enhance user onboarding.

The age of AI brings an expectation of immediate insights and context-based support when and where you need it, and Joule with 麻豆原创 Signavio solutions means process navigation and execution is no exception.

For clearer decision-making, seamless integration, and enhanced automation, visit the to learn how to activate Joule and get your own conversation started.

Lucas de Boer is Global Marketing program lead for 麻豆原创 Signavio.

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

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

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

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

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

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

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

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

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Boost insights and workforce skilling with AI-powered guidance

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

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

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

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

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

Build lasting connections with 麻豆原创 Customer Loyalty Management

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

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

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

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

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

Learn more about 麻豆原创 CX in Q4 2025

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

• 鈥�&苍产蝉辫;
•   
•   

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

Competitive pressures, systemic risks, technological disruption, and workforce shifts are reshaping the modern business landscape constantly, meaning most organizations already run multiple transformations simultaneously. In fact, Forrester鈥檚 research reveals that 72% of organizations are pursuing four or more transformation initiatives annually.

However, despite its continuous nature, many still treat business transformations as a series of disconnected projects, limited to specific functions or technology upgrades鈥攁 fragmented approach that slows execution, reduces impact, and prevents organizations from realizing the full value of their investments.

That鈥檚 why 麻豆原创 partnered with Forrester Consulting to deliver a comprehensive survey of enterprise-level global organizations, assessing levels of business transformation management maturity.

The results clearly show that developing a repeatable, scalable transformation capability is how organizations best prepare themselves to address the challenges mentioned above and transform successfully again and again. Building and growing such a capability means bringing together strategy, processes, technology, and culture into a cohesive and strategic framework that accelerates execution, improves measurement, and enables ongoing innovation.

The 6% club

Conducted online with over 1,000 cross-industry senior decision-makers at organizations in APAC, EMEA, Latin America, and North America, the survey was able to segment respondents into four maturity tiers鈥攂eginner, intermediate, advanced, and leader鈥攂ased on their strengths across five dimensions: strategy and leadership, applications and technology, process, data, and people and culture.

Only 6% of the surveyed firms qualified as transformation leaders, with most organizations still facing significant gaps in execution, governance, and cultural alignment. The findings also showed:

• Transformation is now 鈥榖usiness as usual.鈥� Over half of organizations (52%) plan to increase transformation investments by 11% to 20% in the next 12 months; another 22% expect to boost spending by more than 20%. Only 1% plan to reduce investment.
• Barriers to success are common. Fifty-six percent of respondents struggle with poor data, 55% encounter persistent organizational silos, and 52% highlight employee fatigue from continuous change
• Governance is lacking. Only 24% of organizations have a cross-functional transformation governance board, and just 25% embed transformation goals into KPIs. 

Fortunately, even organizations that haven鈥檛 yet reached the leader stage are conscious of the benefits of building a transformation capability, with respondents highlighting the following expected outcomes:

• Increased ability to pivot in response to market shifts or disruptions (68%)
• Faster upskilling and reskilling of the workforce (66%)
• Faster execution of strategic initiatives (65%)
• Increased consistency and reliability in process execution (65%)
• Increased leadership alignment and accountability (64%)

Unlocking the benefits

Overall, survey respondents were committed to transformation at scale, but fragmented execution and the lack of an overall strategy have hampered their efforts. This missing piece of the puzzle is where business transformation management solutions from 麻豆原创 can be of most use.

鈥淭ransformation challenges will always exist, particularly in aligning localized execution with an enterprise-wide approach,鈥� Dee Houchen, head of Marketing for 麻豆原创 Signavio and 麻豆原创 LeanIX, says. 鈥淥ur research shows that true transformation leaders embed change into their organization鈥檚 DNA. That means prioritizing early employee involvement, building dedicated change functions, and putting a high premium on digital adoption management.鈥�

鈥�,  , and solutions offer clarity and transparency in business transformation, helping organizations turn transformation from isolated plans into comprehensive action across the entire organization,鈥� Houchen adds. 鈥淭his report is an invaluable resource for anyone wondering how they can build repeatable transformation capability and become transformation leaders in their own right.鈥�

Lucas de Boer is global marketing program lead for 麻豆原创 Signavio.

As the pace of digital demand accelerates and mission priorities grow more complex, it is clear that traditional modernization approaches can no longer keep pace.

To deliver on rapidly evolving government missions, agencies must move beyond lifting and shifting legacy systems. The true transformation lies in reimagining operating models to support continuous, secure, and scalable innovation.

Shift from modernization to transformation

Legacy IT structures, designed for predictability and control, often limit progress. Risk-averse approaches that once provided stability now constrain agility and innovation. Federal agencies leading the way are adopting future-ready, cloud-native architectures that emphasize interoperability, flexibility, and resilience. These architectures do more than modernize technology; they modernize how agencies work, collaborate, and deliver results.

Reducing technical debt has become a strategic imperative, but emerging technologies also demand a balance of governance and innovation. Federal leaders are reframing their approach to modernization as an ongoing process, a state of persistent transformation where technology, mission, and operations evolve in sync.

Measuring what matters: from cost to capability

As agencies embrace new models of delivery, success must be evaluated through a dual focus:

• Total cost of ownership (TCO): Sustaining efficiency by lowering infrastructure costs and simplifying operations
• Total cost to innovate (TCI): Accelerating value creation by enabling teams to activate, test, and scale new capabilities with minimal risk and complexity

This broader lens allows agencies to view modernization as an investment in agility, resilience, and readiness鈥攅nsuring they can respond to what鈥檚 next, not just what鈥檚 now.

Partnering for a smarter, more agile government

Driving this shift requires strategic collaboration across the public and private sectors. Programs such as the U.S. General Services Administration鈥檚 initiative are redefining how government acquires and deploys technology. By consolidating procurement and engaging directly with technology providers, OneGov helps create greater transparency, efficiency, and long-term value for taxpayers.

In alignment with this vision, 麻豆原创 has partnered with GSA to provide federal agencies with expanded access to both 麻豆原创 licensed-based products and white glove migration, all while avoiding data egress fees. These initiatives help agencies reduce technical debt, accelerate digital transformation, and establish a secure, cloud-native foundation for the future.

Building the innovation-ready enterprise

Modernization is not a destination, it is a capability. Agencies that continually adapt their operating models will define the next generation of public service. The path forward is clear:

• Reimagine modernization as operating model transformation, not just technology refresh
• Balance efficiency with innovation by measuring both cost savings and speed to value
• Build future-ready enterprises where mission and IT operate as one, powered by cloud, automation, and AI

Together, we are shaping a smarter, more secure, and more agile federal enterprise, one that is ready to meet the demands of a rapidly changing world and deliver enduring value to citizens.

David Robinson is president of Cloud ERP and acting managing director of U.S. Public Services at 麻豆原创.

These include 麻豆原创 Cloud ERP Private,听麻豆原创 Business Data Cloud,听麻豆原创 Integrated Business Planning and聽麻豆原创 Signavio solutions.

Following its spinoff from Continental AG in September 2025, AUMOVIO is redefining the automotive landscape with its bold vision to make mobility safe, exciting, connected and autonomous. With over 100 years of experience and a global footprint of more than 86,000 employees across over 100 locations, AUMOVIO is now embracing 麻豆原创鈥檚 intelligent enterprise solutions to become even more dynamic, agile and competitive.

鈥淭his move to the cloud and these solutions will transform our operations,鈥� said Thorsten Pache, CIO of AUMOVIO. 鈥淲e鈥檙e building a digital-first foundation that allows us to scale innovation, respond to market shifts in real time and deliver intelligent mobility solutions that anticipate the needs of tomorrow鈥檚 drivers.鈥�

The deployment of 麻豆原创 Cloud ERP Private provides AUMOVIO with a more secure and flexible digital core, while 麻豆原创 Business Data Cloud enables real-time data harmonization across its global footprint. 麻豆原创 Integrated Business Planning supports comprehensive supply chain visibility and responsiveness, and 麻豆原创 Signavio solutions empower continuous process optimization and transformation.

鈥淥ur collaboration with AUMOVIO demonstrates how cloud technology can accelerate reinvention,鈥� said Thomas Saueressig, member of the Executive Board of 麻豆原创 SE, Customer Services & Delivery. 鈥淏y combining advanced planning, process intelligence and a unified data foundation, AUMOVIO is well positioned to lead in the era of connected and autonomous mobility.鈥�

AUMOVIO鈥檚 transformation reflects its commitment to innovation, operational excellence and collaborative spirit. AUMOVIO is now better positioned to deliver cutting-edge solutions, from sensors and displays to autonomous driving platforms, while maintaining operational excellence and customer-centricity.

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This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
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The autonomy of AI agents in decision-making and innovative problem-solving is what makes this disruptive technology so attractive to companies, yet also one that demands focus and clarity.

Organizations need to understand where it is appropriate to deploy AI agents while ensuring they behave as intended: staying within their operational scope, using only authorized data, and maintaining compliance with the company鈥檚 guidelines and regulations.

If in the world of espionage, agents would normally operate in the shadows,听in the corporate world, companies need to ensure that AI agents operate in plain sight. Their behavior should be transparent, measurable, and always under control.

As organizations scale their use of agentic AI, the specter of a new challenge emerges: understanding where exactly in their processes agents should be applied, if they are acting the way they are supposed to, and what their impact and cost really are. After all, AI agents are a business resource like any other, and should always be governed by an organization鈥檚 leadership, in alignment with that organization鈥檚 goals.

This is where agent mining capabilities in 麻豆原创 Signavio solutions come into play, bringing visibility, accountability, and continuous optimization to the growing ecosystem of AI-driven process transformation.

The problem: invisible autonomy in enterprise AI

AI agents become more autonomous — and sometimes more ambiguous — as they learn and evolve. Their decisions happen in milliseconds, driven by complex reasoning that can appear as an invisible black box to end users.

Without transparency, organizations risk blind automation, which means agents operate efficiently on paper but unpredictably in practice, potentially introducing errors, inefficiencies, or unnecessary costs.

At the same time, agents operating visibly allow organizations to see and learn from the agents鈥� behavior, potentially revealing new approaches, creative solutions to existing problems, or unexpected positive outcomes.

The solution: AI Agent mining

Agent mining enables organizations to understand and optimize the behavior of AI agents operating across their business processes. Agent mining in 麻豆原创 Signavio solutions provides the ability to:

• Trace agent behavior to see how agents make decisions, navigate process steps, and adapt to different contexts
• Analyze impact and measure the agents鈥� influence on key metrics like process time, accuracy, and compliance
• Monitor cost by tracking computational or LLM-related expenses, helping ensure cost-efficient performance
• Benchmark performance by comparing outcomes of agent runs to identify areas for refinement

But it鈥檚 also more than just a monitoring tool. AI agent mining is an intelligence layer for the AI workforce. By transforming invisible actions into measurable insights, it empowers organizations to:

• Increase transparency into agent behavior and decision logic
• Control operational costs by understanding and optimizing LLM usage
• Ensure compliance through auditable decision trails
• Continuously improve performance by learning from live agent execution
• Measure true business value of AI automation, not just efficiency metrics

Agent mining from 麻豆原创 Signavio can extend from Joule Agents built by 麻豆原创 to third-party or custom-built AI agents, offering a unified lens across an organization鈥檚 AI landscape.

A broader vision: AI agent excellence

Unless we鈥檙e watching the Mission: Impossible franchise, no one wants to see rogue agents on the loose, which is why agent mining is just one of four pillars under 麻豆原创 Signavio鈥檚 comprehensive approach to AI agent excellence. The pillars that help ensure intelligent agents are not just deployed, but deployed intelligently, include:

• Agent discovery: Identifying the right processes and opportunities where AI agents can drive the greatest impact
• Agent context: Providing agents with the right process knowledge and compliance parameters to act responsibly and efficiently
• Agent mining: As outlined above, observing and analyzing how agents actually behave in operation
• Agent value impact: Quantifying the business value that agents deliver, such as efficiency gains, cost savings, or improved customer experience

Together, these pillars ensure that organizations not only automate processes but continuously learn from and improve their performance. The world is not enough; it鈥檚 critical to have both working in sync.

As 麻豆原创 Signavio General Manager Dr. Gero Decker shared, 鈥淎I agents represent a fundamentally new paradigm, and a key question remains: How should we perceive them? Should we view AI agents as advanced technical constructs or as non-human humans?聽It’s a complex question that organizations must address as they deploy AI agents at scale.”

鈥淎t 麻豆原创 Signavio, we are preparing for the future by focusing on the organizational and process dimensions of agentic AI adoption,” he said. “Our AI agent excellence approach aims to ensure that AI agents are integrated seamlessly, efficiently, and compliantly into the broader enterprise. In this rapidly evolving landscape, no company can afford to stand still. Our vision is to be an engine for innovation and reinvention, helping companies grow and adapt.鈥�

麻豆原创 Signavio solutions can empower organizations to ensure their AI agents are not only effective but also transparent and accountable, paving the way for smarter, more strategic automation — in other words, AI agent excellence.

Lucas de Boer is a Global Marketing program lead for 麻豆原创 Signavio.

This month at , we announced a wave of 麻豆原创 Business AI innovations all built on the same technology foundation that powers our that we are now delivering to our customers and partners, allowing them to add even more value in the future.

We showed how the future of enterprise software is built on an AI-native architecture, powered by 麻豆原创 app, data, and AI foundation. With this approach, we are enabling a platform shift across the tech stack in a non-disruptive fashion, empowering developers to work faster and smarter using the frameworks and tools of their choice.

麻豆原创 HANA Cloud and 麻豆原创 Business Data Cloud: powering our AI-native future

麻豆原创 HANA Cloud is the database for 麻豆原创鈥檚 AI-native software architecture and the foundation of our broader data fabric strategy. At 麻豆原创 TechEd, we announced new AI capabilities for 麻豆原创 HANA Cloud that spur AI innovation.  

For example, Model Context Protocol (MCP) support for 麻豆原创 HANA Cloud is now generally available. This provides direct access to rich multi-model engines. Agents can be grounded in full enterprise data context: navigating relationships across customers and suppliers, understanding geographic dependencies through spatial data, and performing semantic searches through vector embeddings — all within a single in-memory engine.  

We鈥檙e also expanding 麻豆原创 HANA Cloud knowledge graph engine capabilities (Q1 2026) so customers can automatically generate knowledge graphs from 麻豆原创 HANA Cloud metadata. What used to take weeks of manual modeling can now happen automatically in minutes. But that鈥檚 not all. We鈥檙e also enabling agentic memory in 麻豆原创 HANA Cloud. With long-term memory, AI agents can memorize past inputs and decisions — learning and remembering just like humans — and become continuously smarter.

These advances show that 麻豆原创 HANA Cloud is truly powering an AI-native future. .

Bringing together the power of 麻豆原创 BDC and Snowflake

We are bringing the power of Snowflake together with 麻豆原创 Business Data Cloud (麻豆原创 BDC), calling it 麻豆原创 Snowflake. This partnership enables zero copy data sharing with Snowflake via 麻豆原创 BDC Connect.

Enterprises already using Snowflake today can leverage 麻豆原创 BDC Connect to integrate their existing instances of Snowflake with 麻豆原创 BDC, giving them seamless, real-time access to combined, semantically rich 麻豆原创 with non-麻豆原创 data in 麻豆原创 BDC. 麻豆原创 Snowflake will be made generally available in Q1 2026, and 麻豆原创 BDC Connect for Snowflake in H1 2026. Find more information here.

麻豆原创-RPT-1: a new category of AI models

One of our most exciting announcements at 麻豆原创 TechEd was the launch of our first enterprise relational foundation model 麻豆原创-RPT-1, pronounced: 鈥渞apid one.鈥�

Businesses run on structured data. But large language models (LLMs) struggle with a general understanding of table structures and associated semantics. This requires the use of machine learning, or 鈥渘arrow AI,鈥� for tasks like classification, regression, and more. But classical machine learning necessitates training a model on each task, which easily can lead to hundreds of separate models.

麻豆原创-RPT-1 puts them all into one single, pre-trained model that understands relational business data and predicts business outcomes. Unlike language, image, or video models, 麻豆原创-RPT-1 accurately predicts business based on tabular data such as payment delays, supplier risks, upsell opportunities, customer churn risk, and more.

We believe that 麻豆原创-RPT-1 is a super capable foundation model today. It provides up to 2x better prediction quality compared to narrow models and 3.5x better prediction quality as compared to LLMs. .

麻豆原创-RPT-1 comes in three versions. 麻豆原创-RPT-1-small is for super-fast predictions and 麻豆原创-RPT-1-large is for highest accuracy. Both will be generally available in Q4 2025 in the generative AI hub in AI Foundation. 麻豆原创-RPT-1-OSS is the open-source version, available in Hugging Face and GitHub.

You can test 麻豆原创-RPT-1 today with your data or our use case data samples via no-code UI or via API in the new 麻豆原创-RPT-1 playground, an intuitive and interactive space to test for free and open to everyone and .

We are continuously adding new capabilities to AI Foundation and models to the generative AI hub, empowering developers to experiment with orchestration tools and leading models to scale AI development and productization across 麻豆原创 and non-麻豆原创 environments. For example, Perplexity is now generally available in the generative AI hub, so users can correlate business data with external data from the internet. Evaluation Services and Prompt Optimizer, in close collaboration with NotDiamond, are now also generally available in AI Foundation, freeing up users to adopt the most appropriate model for their use cases without the need for rewriting prompts. .

Digital sovereignty made in Germany, for Europe

Digital sovereignty is becoming increasingly important, reflecting the need for regional AI services that align with local regulations, standards, and values. As an example, Europe will benefit from its own strong, trustworthy infrastructure to support innovation, data protection, and ethical AI.

AI Foundation, including various models and all the services we offer, is already available on our own cloud infrastructure. As a next step, we are expanding our 麻豆原创 Cloud Infrastructure offering in our 麻豆原创 data center in Walldorf, Germany, to Deutsche Telekom through the Industrial AI Cloud project, providing secure, high-performance infrastructure for AI innovations across public institutions, defense, and society. 麻豆原创 delivers 麻豆原创 Cloud Infrastructure, 麻豆原创 Business Technology Platform, and applications 鈥� including our AI Foundation with frontier AI from Mistral, Cohere, and others 鈥� on Telekom鈥檚 Munich data center. Both companies uphold the highest standards of data protection, security, and reliability.

This marks a milestone as more European companies join the Industrial AI Cloud project, advancing applied AI across Europe with trusted, business-embedded solutions that unlock the full potential of industry data. See the announcement here.

Enabling customers to build, extend, share, and orchestrate AI agents

To help manage Joule Agents and Joule skills, we have introduced the concept of AI Assistants 鈥� role-based AI teammates, accessed through Joule 鈥� like a financial assistant that brings together agents for cash collection, treasury, and more. We will provide AI Assistants in Joule for every core business role, offering our users an agentic experience like never before.

Out-of-the-box Joule Agents are powerful, but we know that every company has unique requirements. We believe AI should adapt to users鈥� systems, not the other way around, so we are enabling them to use Joule Studio to extend 麻豆原创鈥檚 pre-built agents with custom fields, tools, and reasoning logic while retaining all the deeply grounded integration capabilities 麻豆原创 provides. Joule Studio also provides low-code tools to build custom agents that integrate with all other Joule Agents, Joule skills, and 麻豆原创 BDC.

Using a low-code approach, users can build Joule Agents visually with natural language and drag-and-drop. But we also want to meet the needs of developers who want ultimate flexibility. Our pro-code approach gives developers the freedom to build agents using the agentic framework of their choice 鈥� for example, LangGraph, CrewAI, Google鈥檚 Agent Development Kit, and more. 麻豆原创 Cloud SDK for AI now supports agentic development, ensuring these pro-code agents can be seamlessly integrated and giving developers the best of both worlds: deep integration and full flexibility.

No matter how you want to build agents, an important question is how to integrate them into the larger ecosystem beyond 麻豆原创. We鈥檙e making Joule Agents fully compatible with the agent-to-agent (A2A) protocol soon, so agents can discover and collaborate with each other.

A2A exposes rich semantics describing an agent鈥檚 capabilities, allowing both 麻豆原创 and third-party agents to work together seamlessly. We are collaborating with partners 鈥� AWS, Google, Microsoft, ServiceNow, and more 鈥� to standardize this protocol for full interoperability. This capability will allow Joule to orchestrate tasks across multiple agents, both 麻豆原创 and non-麻豆原创, increasing automation and productivity across the enterprise. Read more here.

To manage and govern agents across the enterprise, is now generally available, providing centralized control of 麻豆原创 and non-麻豆原创 agents. In addition, is available now for tracing agent actions, benchmarking against KPIs, and identifying bottlenecks or opportunities for agents to further improve business.

No 麻豆原创 TechEd without ABAP news

The ABAP journey continues with 麻豆原创-ABAP-1, which will be available in the generative AI hub in Q4 2025. Trained on ABAP code, it is designed to build ABAP AI use cases, enabling developers to build smarter, custom AI solutions in modern ABAP code. .

In addition, ABAP Cloud development is coming to Visual Studio (VS) Code. The new ABAP Cloud extension for VS Code delivers a streamlined, file-based development experience with built-in AI assistance. Powered by an ABAP language server, it will initially support 麻豆原创 Fiori UI service development and expand to additional ABAP Cloud scenarios over time. This brings ABAP development into the same environment where developers already build with UI5 and CAP. General availability is planned for Q2 2026. .

What鈥檚 next: embodied AI and quantum

麻豆原创 TechEd is always an opportunity to look to the future. This year, that future includes not just humans, but also autonomous devices, including humanoid robots.

By integrating Joule Agents natively with robots, 麻豆原创 is bringing business logic into the physical world, enabling a wide range of autonomous devices to operate with enterprise context. We highlighted our strategic partnerships with robotics companies and system integrators to serve customers like Sartorius, Bitzer, and Matur Fompak, demonstrating how our expanding physical AI ecosystem enables robots to understand business processes and execute complex tasks autonomously.

Early proof-of-concept deployments show Joule successfully integrated with 麻豆原创 business applications and autonomous systems across asset performance, logistics, field services, and warehouse operations. While still in the pioneering stage, these implementations illustrate how 麻豆原创 is extending Joule to serve both human users and autonomous devices, shaping the future of enterprise AI.

Read more about the partnerships and implementations here.

AI is a new compute paradigm that changes everything. But there is another compute paradigm on the horizon: quantum computing. It鈥檚 early days, but 麻豆原创 is driving the future of enterprise computing with a vision to help businesses get ready for quantum computing.

麻豆原创 is not building quantum hardware; instead, we are focusing on creating quantum algorithms for business applications. These solutions are simple to deploy 鈥� on when needed, off when not 鈥� and are designed to be hardware-agnostic, collaborating with partners such as IBM to ensure seamless integration without re-platforming. This approach will enable organizations to unlock operational efficiency and drive better business results at enterprise scale.

I couldn鈥檛 be more excited about what鈥檚 next for our customers鈥� future as we bring 麻豆原创鈥檚 AI-native architecture to life.

Philipp Herzig is CTO of 麻豆原创.

The announcements underlined all the ways that 麻豆原创鈥檚 Business Transformation Management solutions, and the integrated toolchain to which they belong, can empower organizations to develop a scalable and sustainable transformation capability.

Cost optimization, EA standardization, and AI adoption

Companies increasingly look to fund innovation, particularly when it comes to AI, by digging into existing budgets.

At the summits, Andr茅 Christ, co-founder and general manager at 麻豆原创 LeanIX, announced new features focused on application TCO (total cost of ownership) to help companies find cost savings across the IT landscape that can be reallocated to more strategic investment. These TCO features include the addition of cost KPIs to the architecture executive dashboard, the ability to enhance factsheets with configurable calculations, and an application TCO view in the application landscape report.

Christ also announced a new approach to target architecture planning in 麻豆原创 LeanIX, allowing customers to start by diagramming their future state and then modeling backwards. Architects and business leaders thus can get a more streamlined experience, from design to execution, allowing them to make thoughtful, data-driven decisions every step of the way. 

To help further facilitate landscape transformation and management, Christ also announced the upcoming release of AI-assisted architecture guidance.

Finally, Christ made several announcements regarding 麻豆原创 LeanIX鈥檚 support for AI adoption and governance. Here, he returned to the announced at 麻豆原创 Sapphire. Just as 麻豆原创 LeanIX can serve as the single source of truth for the application landscape, 麻豆原创 LeanIX can now serve as the single source of truth for AI agents. This begins with the discovery of agents鈥攃ustom agents, Joule Agents, and third-party agents鈥攁nd their subsequent tracking and management.

The goal of 麻豆原创 LeanIX鈥檚 agent governance features is to allow organizations to understand what business capabilities agents support, what applications they access, and where they can have the greatest impact. To this end, Christ further announced a new agent radar report and the ability to assess agent adoption through executive dashboards.

As the last announcement with regard to AI, Christ also announced the launch of the MCP server for 麻豆原创 LeanIX solutions. Model context protocol (MCP) servers are an open-source standard interface that links AI models with enterprise data, helping AI assistants connect to 麻豆原创 LeanIX workspaces and inventory data. This feature helps organizations leverage AI agents to maintain data and activate AI workflows.

With the AI agent hub and the MCP server, 麻豆原创 LeanIX can help accelerate the adoption of AI agents while also enabling consistent and scalable governance.

Process excellence, untapped value, and the organization of the future

The summit in Austin also afforded 麻豆原创 Signavio鈥檚 Founder and General Manager, Gero Decker, the opportunity to talk about new features and capabilities in the 麻豆原创 Signavio portfolio. Just as Christ talked about the ways that 麻豆原创 LeanIX helps free up resources to fund innovation, Decker focused on the ways 麻豆原创 Signavio supports organizations in their 鈥渜uest for value.鈥�

Transformation is not an end in itself. The goal of transforming the IT landscape, processes, and even the overall business is to unlock and realize new value. 麻豆原创 Signavio has long helped companies find and pursue opportunities for such process improvement and value creation. Now, the AI-enabled transformation advisor, when connected to 麻豆原创 Signavio Process Insights, can make this even easier by allowing users to use text-based prompts鈥攕uch as 鈥淐an I reduce costs in my sales operations?鈥濃�攖o help generate analysis and recommended next steps.

While improving individual processes in this way can deliver real value, processes don鈥檛 run in a vacuum. In order to address this, Decker also announced transformation management capabilities providing visibility into the interconnections and cross-effects between processes.

By allowing customers to better see and understand the impact of transforming processes on one another, 麻豆原创 Signavio solutions can enable truly holistic, data-driven decision-making.

Decker also addressed agentic AI by introducing a number of that will see general availability in Q1 2026. These agents, which will include a Screen Guide Agent, a Value Case Creation Agent, a Dashboard Analyzer Agent, a Process Content Recommender Agent, and a Workspace Administration Agent, can enable 麻豆原创 Signavio solutions to help automate repetitive tasks and accelerate content discovery.

A new breed of digital learning technology

麻豆原创 completed the acquisition of WalkMe shortly before last year鈥檚 summit in Frankfurt, Germany. In The Hague and Austin, WalkMe took the stage as a key player in the Business Transformation Management portfolio.

The big announcement WalkMe shared at the summits focused on . By embedding training directly into the applications employees use every day, even when workflows extend across multiple applications, this new solution can empower learning teams to give employees both a comprehensive learning infrastructure and content they need to keep up. 

The key capabilities of this solution include: comprehensive training delivery with in-app search and discovery, in-app consumption, and customizable learning portals; intelligent content authoring with AI-first authoring that turns prompts and company knowledge into multi-media, multi-modal experiences; and the ability to curate and expose training in context with flexible conditions and triggers and behavior-based segmentation.

These capabilities come equipped with powerful analytics so you can measure and understand user behavior and engagement as well as assess content performance.

The transformation journey is just beginning

The summits showcased the power of 麻豆原创 LeanIX, 麻豆原创 Signavio, and WalkMe as individual portfolios as well as their combined power as the foundation of a transformation capability. The events also highlighted the amazing potential of these solutions to shape the way companies transform into the future.

At a time when AI is disrupting operating models and every function across the enterprise, the summits offered a reminder of the central role 麻豆原创 can play in this disruption. From funding and managing transformation to enabling the workforce to adapt and excel in a rapidly changing world, this portfolio of tools can give every organization what they need to help address the challenges of today while unlocking opportunity for tomorrow.

Matthew T. Grant is a senior writer for 麻豆原创 LeanIX and 麻豆原创 Signavio.

Top photo copyright: Christian Palm

Ahlstrom is a large international manufacturer of specialty materials, with 36 plants around the world and about 7,000 employees. The company鈥檚 strategy is to be a global leader in its field.

The business transformation project, called Stella, is the largest single investment in company history. Its purpose is to transfer operations, except HR and product development, to the new 麻豆原创 S/4HANA Cloud environment. The old group business system dated back to the 1990s and no longer met the needs of global manufacturing. Ahlstrom also uses 麻豆原创 Ariba for its procurement, which had already been implemented.

鈥溌槎乖� S/4HANA Cloud was clearly the best solution for us, especially for production management and planning,鈥� shared Ahlstrom CIO聽Kristiina Lammila, who is responsible for the project. “With it, we can harmonize our operations and bring all our plants under the same system.”

Unifying systems and data

One of the main challenges of the project was integrating different systems and unifying fragmented data. With modernization, processes can be streamlined, daily work made easier, and time freed up for more strategically important tasks.

鈥淲e have managed to make significant progress with 麻豆原创 S/4HANA Cloud standard solution,” Lammila said. “We use private cloud, which also allows for fairly flexible modifications. One plant is already live, and next year seven more plants will join. The goal is to complete the entire transformation within five years.”

According to Lammila, the system enables flexible transfer of production from one plant to another and global optimization of the supply chain.

Benefits for both employees and customers

systems benefit all stakeholders. Streamlined production processes reduce waste and improve quality. Harmonized purchasing brings savings and the most visible change for Ahlstrom鈥檚 customers is smoother supply chains and better availability of products. The use of AI and analytics is expanding. Especially in sales support, AI solutions built on 麻豆原创 Sales Cloud data are already in use at Ahlstrom.

鈥淲e can integrate even more closely with our customers, as many of them also use 麻豆原创,鈥� Lammila explained. “This facilitates and streamlines the flow of information between companies.”

From the employee鈥檚 perspective, 麻豆原创 S/4HANA Cloud makes teamwork easier. For example, order and inventory balances can be checked conveniently based on real-time data. Lammila also pointed out that the updated system supports employer branding, as job seekers expect to have appropriate and up-to-date tools at their disposal.

Strong change leadership is key to success

Lammila advises companies planning similar projects to approach transformations as comprehensive initiatives that must engage all employees, including management, not just the IT department.

鈥淪trong management commitment and a shared vision of where we are going and how to get there are needed. The project must be led as a deep transformation, and the end result must not be compromised due to haste. Poorly executed work is difficult to fix later,鈥� she concluded.

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

The Gartner Magic Quadrant research methodology says that “Leaders execute well against their current vision and are well positioned for tomorrow.”

In this year鈥檚 Magic Quadrant, 麻豆原创 LeanIX was positioned furthest and highest in both Completeness of Vision and Ability to Execute, which also marks the first time an 麻豆原创 solution has been positioned in this way.

We believe this result reflects the unique strength of 麻豆原创 LeanIX solutions in helping enterprises:聽

• Make confident, data-driven technology investment decisions 
• Drive transformation initiatives that deliver measurable business impact 
• Accelerate AI innovation while ensuring responsible governance 

“Our goal is to empower our customers to build transformation as an ongoing capability, rather than a one-off project,鈥� Dee Houchen, chief marketing officer at 麻豆原创 Signavio, said. 鈥淎s transformation never ends, our solutions help companies secure a full picture of the applications they鈥檙e running聽and, more importantly, the capabilities they offer. This means understanding exactly how those applications can be best deployed to maximize efficiency and productivity. Enterprise architecture planning is at the heart of this approach, and we believe being recognized as a Leader for the fifth consecutive year by Gartner reaffirms our unwavering commitment to value realization for our customers.鈥�

In today’s dynamic business landscape, enterprise architecture planning and implementation are vital for organizational transparency, smarter decision-making, and business growth, and 麻豆原创 LeanIX maintains an ongoing dedication to innovation and customer satisfaction in this field, as part of 麻豆原创鈥檚 integrated business transformation toolchain.

In our opinion, this repeated recognition of 麻豆原创 LeanIX solutions provides useful context regarding the state of the enterprise architecture market. As a vendor, 麻豆原创 LeanIX empowers organizations to make informed decisions about technology investments, map and support large-scale business transformation, and implement sound AI governance to ignite AI innovation across the enterprise.

The Gartner Magic Quadrant equips businesses with valuable insights to make informed decisions. Get a .

Lucas de Boer is Global Marketing program lead for 麻豆原创 Signavio.

Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner鈥檚 research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER is a registered trademark and service mark of Gartner and Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.

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

The real challenge: connecting priorities

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

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

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

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

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

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

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

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

Embedded AI: tangible value, secure, and seamless

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

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

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

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

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

Data and intelligent applications: unified and actionable

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

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

From insight to action: transformation in practice

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

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

Services and support: accelerating innovation and realizing value

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

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

Customer perspective: Southern California Edison鈥檚 journey

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

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

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

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

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

New research shows how business AI delivers ROI

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

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

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

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

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

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

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

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

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

New Joule Agents autonomously get work done

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

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

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

New embedded intelligence across 麻豆原创 applications

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

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

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

Governing AI with visibility and control

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

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

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

What鈥檚 next for business AI

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

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

Ready to start your AI journey?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The solution will be available Q4 2025.

AI and intelligence: the next imperative

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

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

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

Deep research in Joule

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

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

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

Intelligent applications for customer experience

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

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

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

Adoption that drives value

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

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

The path forward

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

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

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

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

The AI revolution is transforming the workplace, but a new survey from WalkMe, an 麻豆原创 company, reveals that employees are largely left to navigate it on their own.

While workers are eager to use AI, most lack the support and training needed to use it responsibly and effectively, fueling security risks, wasted productivity, and lost return on investment (ROI).

For enterprises, this problem is compounded by complex digital landscapes, where poor adoption of new tools can erode the value of strategic technology investments.

What the survey found

The second annual 鈥淎I in the Workplace Survey鈥� polled 1,000 working U.S. adults who use AI in their jobs to understand the reality of AI adoption. The findings highlight a significant gap between employee eagerness and organizational readiness:

• Shadow AI is everywhere: 78% of employees admit to using AI tools that were not approved by their employer. More than half (51%) report receiving conflicting guidance on when and how to use AI at work.
• Productivity paradox: Despite 80% of employees believing AI improves productivity, nearly 60% admit it often takes longer to figure out how to use an AI tool than to complete the task without it.
• Training gap: The number of daily AI users increased by 16 points since last year’s survey, but only 7.5% of employees have received extensive AI training, an increase of only 0.5% since last year鈥檚 survey. Another 23% have received no training at all.聽
• Cultural confusion: Almost half (45%) of workers admit to pretending to know how to use an AI tool in a meeting to avoid scrutiny, while 49% have hidden their use of AI to avoid judgment. This trend is even more pronounced among Gen Z, with 55.5% pretending to understand AI tools and 62% hiding their use.

The survey’s findings underscore a critical challenge for large organizations across industries. As AI capabilities are integrated into enterprise applications, ensuring employees can effectively and securely use these tools is paramount to realizing their full business value. Unmanaged AI adoption creates a governance crisis, where security and compliance risks can increase, and valuable productivity gains are lost.

WalkMe helps customers navigate this challenge. Our Digital Adoption Platform (DAP) acts as an essential guidance and governance layer, enabling employees to harness the full power of the technology tools at their disposal. The right digital adoption strategy can help businesses manage the risks of shadow AI while unlocking the full potential of their AI investments across complex landscapes.

WalkMe leadership and analyst commentary

鈥淏eyond the productivity paradox, we鈥檙e facing a full-blown governance crisis,鈥� said Dan Adika, CEO and co-founder of WalkMe. 鈥淲hen nearly 80% of employees are using shadow AI tools, organizations are not just losing money 鈥� they鈥檙e losing control. Businesses are missing a massive opportunity to strategically empower their people and realize the full potential of AI.鈥�

鈥淎I has become an essential enterprise skill. But without training and guardrails, shadow AI creates risk and undermines ROI,” said Gina Smith, PhD, research director of IT Skills for Digital Business at IDC. 鈥淭he companies that build AI鈥憆eady skills and digital adoption strategies now can avoid such loss. They are the organizations who will lead the next era of work.鈥�

Methodology

Propeller Insights conducted the survey for WalkMe from July 16-23, 2025, polling 1,000 working U.S. adults who use AI on the job. The sample was balanced across age, gender, industry, company size, and seniority, with a 卤3 percentage point margin of error. Because respondents were screened for AI use at work, the 100% adoption rate reflects the study design, not the broader U.S. workforce.

Learn more

Adriel Sanchez is chief marketing officer of WalkMe.

We believe this recognition is testament to 麻豆原创鈥檚 long-term vision of integrating all components required for strategic, continuous business process improvement and innovation.

According to the IDC MarketScape, 鈥淏usiness automation technologies have evolved from fragmented solutions into comprehensive business automation platforms (BAPs). These platforms enable enterprises to address diverse process improvement needs through a single system supporting multiple integrated automation technologies.鈥�

Bringing together process analytics from 麻豆原创 Signavio, user guidance from WalkMe, process integration and automation technology from 麻豆原创 Business Technology Platform, and the latest Joule Agents allows organizations to significantly accelerate automation initiatives.

IDC MarketScape vendor analysis model is designed to provide an overview of the competitive fitness of ICT suppliers in a given market.鈥� The research methodology utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each vendor鈥檚 position within a given market. The Capabilities score measures vendor product, go-to-market and business execution in the short-term. The Strategy score measures alignment of vendor strategies with customer requirements in a 3-5-year timeframe. Vendor market share is represented by the size of the circles. Vendor year-over-year growth rate relative to the given market is indicated by a plus, neutral or minus next to the vendor name.

Continuous business automation

Continuous business automation is at the heart of every commercial IT deployment, as it allows companies to simultaneously scale their operations while reducing costs.

But when business applications are augmented with disparate automation technologies 鈥� such as standalone AI agent frameworks, workflow systems, integration brokers, rules engines, and process mining tools 鈥� they can become fragmented and lack business context. This approach also often requires large amounts of data to be copied outside of the business applications, which increases latency, operational costs, and the risk for expensive data quality issues.

The framework provided by enterprise automation with 麻豆原创 overcomes these issues by adding an integrated business automation toolset closely linked with 麻豆原创 Business Suite.

麻豆原创 Integration Suite helps ensure seamless data flow between 麻豆原创 and non-麻豆原创 applications to and from standardized services (APIs) and events. Using these services and events, 麻豆原创 Build then allows orchestration of process flows to implement new automations or adapt existing ones. Then, 麻豆原创 Signavio enables end-to-end process analytics and optimization with process mining and insights, providing improvement recommendations directly into 麻豆原创 Build automations. On top, autonomous, AI-powered Joule Agents can then use these automations as 鈥渟kills,鈥� which allows them to execute standardized business activities. Additionally, users can be guided through complex interactions by WalkMe overlays while feeding back user journey insights into the process improvement cycle.

Customer success across industries

Thousands of organizations across geographies and industries rely on automation solutions from 麻豆原创 to optimize their business processes across lines of business. Here are a few:

• offers a whole universe of hobbies and interests to a worldwide audience. But long before it gets collections and build-up models to customers, the company must first process its invoices with suppliers. Using 麻豆原创 process automation solutions, De Agostini now manages to process more than 90 percent of its unstructured invoices, paper or PDF, automatically.
• is a leading provider of aircraft maintenance, repair, overhaul, and modification services for commercial, VIP, and special-mission aircraft. As part of its digital road map, the company wanted to increase automation in the material logistics process for defective parts. 麻豆原创 process automation solutions are used to coordinate component repair logistics across multiple IT systems, enabling an increase in transaction volume by more than 40 percent.
• believes it has a key role to play in providing secure access to affordable energy, supporting a vibrant Canadian economy, and improving environmental performance. Process automation solutions from 麻豆原创 are used to improve automation of intercompany tax processes (ICT) and vendor invoice processing, leading to a 98 percent reduction in the time needed to reconcile ICT postings.

IDC MarketScape assessment

Business automation technology is advancing in big steps and enables companies to address an ever-increasing scale and complexity of automation projects. Learn more about the future of business automation from Maureen Fleming, program vice president of Worldwide Intelligent Process Automation Market Research and Advisory Service at IDC . .

Bharat Sandhu is chief marketing officer for 麻豆原创 Business Technology Platform at 麻豆原创.

The decision to further strengthen this long-standing partnership was unveiled during a guest lecture at QUT鈥檚 Gardens Point campus, where Julian Lebherz, 麻豆原创 Strategic Advisor, addressed Master’s students enrolled in the QUT Business Process Analytics course. The lecture emphasized the importance of integrating business transformation into standard operations, highlighting real-world applications as well as why some companies are more successful than others at realizing tangible and sustainable value when it comes to deploying business process intelligence solutions.

A key highlight of this collaboration is the nomination of Lebherz as QUT Industry Fellow, underscoring the ambition and momentum of the connection between 麻豆原创 and QUT. With over a decade of highly specialized experience deploying process intelligence solutions and establishing associated delivery organizations in various industries, he is globally recognized as one of the leading experts in the field. Having served in the steering committee of the IEEE Task Force on Process Mining and co-organizing several international conferences on the subject, Lebherz will contribute significantly to the university鈥檚 academic and research endeavors, fostering a deeper integration of industry insights into the curriculum.

“麻豆原创 is committed to equipping QUT and its students with the expertise and technology required to turn business disruption into competitive advantage,” Lebherz said. “Business transformation must become a ubiquitous capability, and hence we [麻豆原创] are doubling down by strengthening partnerships with leading organizations.”

The partnership aims to explore various avenues for collaboration, including internship and research project opportunities, executive education programs, and hackathons. These initiatives are designed to provide students and researchers with hands-on experience and exposure to real-world challenges, aligning academic pursuits with industry needs.

Professor Alistair Barros, head of the School for Information Systems at QUT, expressed enthusiasm for the partnership, stating, “QUT鈥檚 School of Information Systems is intensifying both research and education of holistic business transformation and enterprise computing, encompassing the continuous flywheel of process execution, intelligence, improvement, and change deployment.”

Professor Moe Thandar Wynn, leader of QUT鈥檚 process science group and co-director of QUT鈥檚 Centre for Data Science, highlighted the benefits of strong industry ties, noting, “Our researchers and students benefit tremendously from strong industry collaboration. Partnerships like this one enable us to align curricula and research projects closely with real industry needs.”

The announcement marks a significant step forward in QUT鈥檚 position as a global leader in business process management and process intelligence. By integrating end-to-end business transformation into the academic curriculum across multiple courses, as well as deepening the connection to real-world outcomes, QUT and 麻豆原创 are set to redefine the landscape of business transformation education, preparing students to thrive in an era of constant disruption.

Lucas de Boer, Global Marketing Program Lead, 麻豆原创 Signavio

TUI implemented eight years ago, and now the company鈥檚 over 41,000 employees use various 麻豆原创 SuccessFactors solutions for performance management, talent management, learning, HR data management, and more. “With so many capabilities and so many employees, as you can imagine, it’s a steep learning curve for our employees,” Dean said. This is where TUI turned to to help standardize and automate its HR processes for an improved employee experience and increased efficiency.

Benefits for the business and employees

TUI faced three main challenges when it came to HR processes, Dean explained: employees struggled to learn new systems, legacy training approaches were expensive and difficult to maintain, and time-consuming HR tasks were impacting overall business operations. “We needed something that was going to bring us into the future but that could support the organization as well,” Dean said. The solution also needed to be available 24/7 and in multiple languages to effectively support TUI鈥檚 global employee base, which includes flight attendants, pilots, travel agents, and other seasonal roles.

TUI implemented WalkMe to help employees navigate the company鈥檚 HR processes more easily and efficiently as well as aid HR staff members. With WalkMe analytics, TUI can identify where users have challenges in existing processes and then build WalkMe solutions to create personalized and automated experiences to help mitigate those challenges. For employees, this can mean the software feels easier to use; for HR staff and the business, it can lead to fewer employee and manager errors and faster time-to-value for 麻豆原创 SuccessFactors solutions.

Dean described how WalkMe automation helped simplify TUI鈥檚 onboarding processes for new employees by automatically assigning e-mail addresses in the 麻豆原创 SuccessFactors system during the hiring process to reduce login issues on an employee鈥檚 first day. This not only improved the new hire experience, it also saved HR teams time and proactively addressed any errors.      

TUI also simplified the time-off request process for HR staff and employees.    

“We set up a process whereby if somebody is booking sick leave and they have annual leave at the same time, WalkMe will intercept them. It will say 鈥榊ou鈥檝e actually got holiday at the same time so we need you to cancel that holiday and put it through as sick time,鈥�” Dean said. 鈥淲hat that means then for us is that we’ve got less questions going to HR, less tickets being raised, and more people following the actual process for their region.鈥�

The data speaks volumes

WalkMe analytics can offer visibility into what software is being used and how. With this insight, companies can identify opportunities for improved efficiency and deploy in-app guidance and automations to address specific points in processes. “One of the real benefits of WalkMe is how the data that is available helps us make decisions around how we support employees and how we build digital adoption solutions for our employees,鈥� Dean said. 鈥淲e’ve focused a lot on the data that’s within the annual employee process and how our users are actually using their system currently.”

Analyzing aggregated annual employee form process data collected by WalkMe over 90 days, Dean saw that HR completed the process with no errors 70% of the time, completed the process with some errors 5% of the time, and did not complete the process 23% of the time. Even more, Dean could see where the errors were occurring and where users who didn’t complete the form were getting stuck. Based on this data, Dean used WalkMe to highlight the most-missed fields on the form, reminding users to complete them before moving on. “If 5% of the time they don鈥檛 know that information, I need to do something when they get here to say, 鈥楶lease make sure you have this information before you carry on.鈥� So, I鈥檓 telling them in advance they need to have that, which I can do with WalkMe,鈥� she said.

When asked how easy the analytics dashboards are to build, Dean explained that WalkMe gathers all the forms automatically so there’s no need to build anything additional. With WalkMe flow analytics, you set up the process step-by-step and then the report collects data over time. “It’s super quick and easy. With UI intelligence you get an out-of-the-box set of insights that shows usage of forms in the system. It shows me where people stop and start processing and points of friction,” she said.

Self-service employees

TUI鈥檚 brand purpose to 鈥渃reate the moments that make life richer鈥� not only applies to its customers, but extends to its employee base as well. With the help of WalkMe and 麻豆原创 SuccessFactors solutions, TUI has certainly succeeded in enriching and empowering HR and end users.

“What we’ve been able to see is 80% higher employee self-efficiency,鈥� Dean said. 鈥淪o the good news is they don’t need to contact their local support team because actually what they can do is go into our WalkMe menu and search for any of the content, 24 hours a day, seven days a week, across six different languages.鈥� TUI has also experienced 70% less time spent on training, a 40% increase in task completion, and 50% fewer support calls with the help of WalkMe.

For Dean herself, WalkMe has enhanced her role as a trainer: “It actually supports me to do that change management piece within my organization. It supports me to educate and enable our end users without me having to be available and fly all around the world.”

Discover how  can help drive adoption and streamline HR processes.

Gillian Hixson is an integrated communications specialist at 麻豆原创.

In addition, for the second consecutive year, 麻豆原创 has received the highest rating, evaluated against 19 leading vendors, across both SPARK Matrix assessment categories: Customer Impact and Technology Excellence. This leadership position highlights our commitment to helping enterprises navigate complexity with agility, intelligence, and confidence using 麻豆原创 solutions.

The has always been intrinsically linked with the concept of process observability, whereby companies have the ability to visualize processes as they should happen, as they execute on and impact customers and employee satisfaction. Through this unique, integrated toolkit of AI-infused business transformation management solutions, organizations can gain actionable visibility into the four pillars of their organization: people, processes, applications, and data.

“Our goal is to empower our customers to build transformation as a capability within their organizations, rather than seeing transformation as a one-off project,鈥� Dee Houchen, chief marketing officer at 麻豆原创 LeanIX & 麻豆原创 Signavio, said. 鈥淏y leveraging DTO capabilities to build a virtual representation of any business process with associated systems, decision-makers can simulate different process scenarios and calculate the impact of alternative automations before implementation, allowing for the creation of continuous improvement loops and ensuring transformation has the greatest positive impact. Being recognized as a Leader in the SPARK Matrix for the fifth year in a row is a reflection of the value of this approach and reaffirms our commitment to innovation and customer satisfaction.鈥�

The repeated recognition provides useful context on the current DTO vendor landscape, with several key points differentiating 麻豆原创 solutions from others on the market:

• Enterprise observability: Customers can achieve full enterprise observability, enabling them to centralize and manage transformation initiatives within a single solution.
• AI innovations: 麻豆原创 solutions offer generative AI-powered applications that leverage over 50 years of 麻豆原创 process knowledge to help provide insights and recommendations.
• Value accelerators and best practices: Thousands of value accelerators and best practices are available to help expedite benefit realization in both 麻豆原创 and non-麻豆原创 environments, helping customers start their transformation projects on the right foundation and accelerate time to value.
• Automated insights: 麻豆原创 solutions can provide users with a portfolio of advanced statistics, performance monitoring, and value analysis capabilities to support informed decision-making.
• Modeling and experience connection: We extend DTO capabilities to customer touchpoints, working to ensure comprehensive transformation efforts that connect experiences to processes.

To understand the DTO market better, including why 麻豆原创 has been acknowledged as a leader in this crucial area for five years straight, download a complimentary copy of the latest SPARK Matrix and .

Lucas de Boer is global marketing program lead for 麻豆原创 Signavio.