This year, leading experts from the energy industry once again gathered at the SAP for Energy & Utilities Conference—this time in Toulouse in the south of France. Throughout the three conference days featuring keynotes and case studies, AI was an omnipresent topic. 

AI works when the foundation is right 

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

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

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

From AI hype to real value 

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

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

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

Distributed energy requires intelligent networking 

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

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

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

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

SAP Experience Centers: experiencing AI, not just discussing it 

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

A new chapter for the energy industry 

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

Global supply chains are being reshaped by structural—not cyclical—forces, and traditional operating models are struggling to keep pace. Agentic AI, embedded across end-to-end workflows, is emerging as a critical enabler of a more autonomous supply chain operating model.

As discussed in a new whitepaper, Navigating the New Supply Chain Paradigm, this perspective is grounded in interviews with supply chain leaders across six industries: automotive electronics and software, agricultural equipment, chemicals, global technology, automotive supply, and home appliances.

Their experiences reveal where companies are investing, where adoption challenges remain, and where the next wave of value is likely to emerge.

Supply chains are entering an era of permanent disruption

Four structural forces are reshaping global supply chains simultaneously: geopolitical instability, economic pressure, demographic shifts, and accelerated digital transformation.

Since 2017, trade between geopolitically distant economies has slowed relative to trade among closer partners, signaling growing fragmentation in global commerce. Energy and input costs remain elevated, while labor shortages and digital skill gaps continue to constrain operations.

Europe alone could face 745,000 unfilled truck driver positions by 2028, and 63% of companies cite talent shortages as a primary transformation barrier.

Together, these pressures are pushing supply chains beyond the limits of the traditional “plan-source-make-deliver” model.

Companies are shifting from optimization to AI-enabled orchestration

Supply chains are increasingly viewed as strategic levers for resilience, service differentiation, and competitive advantage.

Across all six companies interviewed, each is investing in at least three forward-looking AI use cases in planning alone.

• A leading agricultural equipment company has deployed more than 1,000 AI agents to support orchestration, scenario planning, and value chain visibility. A global chemicals company is embedding AI across planning and scenario management while emphasizing explainability and trust.
• A home appliance company is applying AI selectively to improve forecasting, transport optimization, warehouse safety, and logistics costs.

The common theme: organizations are redesigning how the enterprise senses, decides, and acts.

Resilience is now defined by decision velocity

In today’s fragmented environment, resilience is no longer about static buffers. It is about how quickly companies can convert disruption signals into coordinated action across sourcing, production, planning, and logistics.

• An automotive electronics and software company centralized electronics ordering across roughly 30 plants and redesigned crisis-management processes, reducing disruption response times by approximately 95%.
• A global technology company adopted a regional “two-leg” supply chain model, using inventory strategically to respond faster to disruptions.

The emerging differentiator is not forecast accuracy alone, but the speed from disruption detection to execution. Visibility remains important, but visibility without coordinated action is no longer enough.

Trust and governance are the biggest barriers to scaling AI

Despite rapid interest, 90% of AI use cases remain stuck in pilot mode. The challenge is not model accuracy alone; it is trust, explainability, fragmented systems, and manual overrides.

• One global chemicals company found that scaling AI depended less on technical performance and more on whether users could understand and trust the outputs. This led to stronger human-in-the-loop governance and progressive autonomy thresholds.
• A major automotive electronics company requires transparent, traceable AI reasoning before planners rely on AI-generated recommendations.

The path to autonomy will be incremental: companies will first augment human decision-making, then automate routine and semi-structured decisions as governance, trust, and data maturity improve.

The next frontier is the Autonomous Enterprise

The Autonomous Enterprise is an operating model where AI workflows, contextual business data, and embedded governance work together to anticipate disruption, coordinate action, and continuously improve performance.

The shift is moving from isolated copilots to coordinated agent-to-agent workflows spanning the supply chain.

In autonomous production environments, supplier reliability agents can monitor vendor risk while workforce orchestration agents align labor capacity with demand. Procurement agents execute sourcing decisions, and production planning agents dynamically rebalance schedules in response to changing conditions.

A similar pattern is emerging in asset management, where alert-processing, maintenance, warehouse replenishment, and goods-movement agents collaborate to resolve operational issues with minimal human intervention.

The business impact is significant. Agentic AI has improved procurement workflow efficiency by 20 to 30%, reduced scrap by 55%, lowered nonperfect batches by 80%, and helped reduce inventory by 20 to 30% while cutting logistics costs by five to 20%.

Collectively, these improvements mark the transition from reactive supply chains to systems that can increasingly anticipate, decide, and execute autonomously.

Building the autonomous supply chain

Capturing this opportunity requires three capabilities that remain fragmented in many organizations today:

• Organizational intelligence: The ability to detect patterns, anticipate risks, and reason across constraints
• Contextual data: Trusted operational data, business rules, workflows, and policies that ground AI decisions in enterprise reality
• Embedded execution: Integrating intelligence directly into workflows so actions can move from recommendation to execution without manual intervention

This creates a virtuous cycle: better data improves decisions, better decisions improve processes, and improved processes generate richer operational data over time.

Importantly, companies do not need to rebuild the enterprise from scratch. Deterministic systems of record remain essential for control, compliance, and auditability. The real transformation lies in rewiring how decisions are made and governed.

Organizations moving fastest are focusing first on high-value, high-frequency decisions such as forecasting, inventory optimization, disruption sensing, transport planning, procurement workflows, maintenance, and customer-service resolution.

The bottom line

The future of supply chain management will not be defined by more digital tools alone. It will be defined by the ability to operate the supply chain as a connected, adaptive, and increasingly autonomous system.

For leaders who move first, supply chain will evolve from a cost-management function into a competitive differentiator, enabling faster time to market, stronger service levels, and greater resilience. The organizations that lead will not be those running the most AI pilots. They will be the ones using AI to redesign how the enterprise senses, decides, and acts across the end-to-end supply chain.

For more information about Autonomous Supply Chain Management, download the white paper, Navigating the New Supply Chain Paradigm.

Hagen Heubach is chief marketing officer for Supply Chain Management at SAP.

Within the global manufacturing industry, maintaining a competitive edge requires a delicate balance between driving internal efficiency and fostering strong external relationships. For Applied Materials, a leader in materials engineering solutions for the semiconductor industry, this challenge became the foundation for a strategic finance transformation program, with an SAP Taulia solution emerging as a key enabler.

The journey began in early 2019 with the launch of Agile Finance, an end-to-end transformation initiative designed to support the company’s aggressive growth trajectory, which included a goal to double in size. The initiative was built around three strategic pillars: enhancing the efficiency and effectiveness of the finance organization, promoting career fulfillment, and establishing a robust digital operating model. The impact was significant, with the finance function achieving approximately 35% productivity gains in its labor force.

The third pillar—the move to a digital operating model—is where the partnership with SAP Taulia began.

“The SAP Taulia Dynamic Discounting solution was introduced not merely as a cost-cutting measure, but as a strategic tool to transform and digitize the interaction with Applied’s extensive, global supplier base,” Junaid Ahmed, corporate VP, Finance at Applied Materials, says. “We understood that to reap the benefits of digitization, we had to ensure the suppliers were on board. It needed to be a win-win outcome.”

Unprecedented flexibility for suppliers

The program empowers suppliers—thousands of them worldwide—to self-select which approved invoices they wish to discount for early payment. This is not a continuous, all-or-nothing commitment but rather a decision made on an invoice-by-invoice basis. This flexibility allows suppliers to manage their working capital needs with greater precision, taking advantage of early payment during their own critical periods, such as quarter-end or year-end, to help meet their own financial targets.

The system also drastically improves transactional efficiency. Suppliers no longer have to call Applied to track invoice status, approval, or payment date. All this information is available 24/7 in the SAP Taulia solution, reducing resource allocation on both sides and ensuring both reap the benefits of moving to an integrated, digital system.

Strategic benefits for Applied Materials

For Applied, the program is a testament to its focus on balancing efficiency with strong supplier relationships. The philosophy is a “win-win” built on a crucial spread: Applied Materials, as a Fortune 500 company with strong cash flow, has a significantly lower cost of capital than many of its suppliers. By funding the discounts, Applied captures a return—the discount income—while offering its suppliers funding at a rate close to their cost of capital, but with greater convenience.

This relationship-focused approach is critical. Applied’s supplier account managers actively support the program because they recognize its mutual benefit, not viewing it as a finance mandate to push costs onto the supply base.

Furthermore, the “dynamic” nature of the discount rates is a powerful risk mitigation tool. Unlike fixed contractual discounts, the rates can be adjusted in response to global economic changes, such as shifts in interest rates. When interest rates rose after the pandemic, Applied was able to adjust the discount rates accordingly with minimal pushback, as the core proposition remains the valuable spread between the parties’ cost of capital.

The SAP Taulia Dynamic Discounting solution has been rolled out globally, giving all suppliers the opportunity to use it. This has been critical over the last 12 months as many businesses around the globe have been subject to new and often unexpected tariff costs impacting their margin and their liquidity.

“The flexibility of the solution means suppliers can access funds when they need them, which helps them navigate some of the economic uncertainty that many businesses are facing,” Dirk Holoubek, managing director, Finance Shared Services, explains. “2025 saw a 23% increase in usage of the discounts, reflecting the pressures that suppliers are feeling right now on their cash flow.” 

The solution’s capability to drive sophisticated analytics is also a major strategic asset. It helps provide insights into the different costs of capital between Applied and its supplier base. This data allows for targeted outreach and communication, ensuring that the offer of capital support is proactively extended to the suppliers that need it most.

The strategic value of the solution is further cemented by its ownership. The acquisition of Taulia by SAP brings several advantages.

“Trust is really important to both us and our suppliers,” Ahmed says. “For our suppliers to adopt a new solution, they need to know its technology they can rely on in the long term. Being part of SAP creates that assurance in the long-term future of the program.”

Looking forward, Applied Materials is already focused on the next stage of the transformation project: Agile Finance 3.0, which is focused on enabling the organization to become AI-first. The company is deploying a global, organization-wide AI assistant to drive personal productivity, but the strategic application of AI in the supplier management space is even more profound.

AI is expected to transform decision-making enablement by analyzing critical information and communicating effective options. In the future, AI will be able to proactively assess the specific needs and attributes of the supplier base, enabling Applied to address issues more quickly and resolve them earlier. The benefits are already tangible in e-invoicing: AI has made the solution more flexible and “human-like,” capable of reading minor changes in invoice format that would have previously caused electronic errors. This reduced rigidity and increased flexibility are directly contributing to the overall efficiency of the digital operating model.

By leveraging the SAP Taulia Dynamic Discounting solution, Applied Materials has not only digitized a process but also strategically transformed its financial operations, creating a system that is agile, resilient, and focused on maintaining mutually beneficial relationships with its global supplier ecosystem.

Cedric Bru is CEO of SAP Taulia.

Vinyl may be one of the music industry’s oldest formats, but it is experiencing a powerful resurgence. In 2025, for the first time this century, vinyl record sales exceeded $1 billion, underscoring renewed customer demand for physical media and premium listening experiences.

This momentum is aligned with consumer audio brand Victrola’s journey. Since its creation in 1906, Victrola has evolved into a global company known for its iconic record players, modern audio products, and mission to bring lifelong music memories to everyone

As it expanded into new sales and distribution channels, the company began to outgrow the limits of its existing ERP system. While its SAP ERP Central Component (SAP ECC) system was stable and served the business well over the years, Victrola needed more scalability and flexibility to match its ambitions. According to Adam Schneider, SVP of Digital Strategy at Victrola, the goal was not simply to maintain operations, but to create a foundation that could support innovation. “We needed something that fueled our creativity at Victrola,” he said. And SAP Cloud ERP was the right fit.

Victrola’s “let’s go” mentality

A move to the public cloud offered more than a technical upgrade; it empowered Victrola to adapt. In that spirit, the team approached the transformation as a complete reimagining of its system with a cloud-first mindset.

“We have a ‘let’s go’ mentality in every single meeting we do. You’ll see a lot of fist bumps at Victrola and we love it. It really keeps that change front and center,” Schneider said.

The project team prioritized change management, openly communicating the reasons for moving to the cloud and the expected benefits. Giving the “why” made a big difference, Schneider said, and everyone was “excited for something new.”

It was also important for the team to engage with and get buy-in from company leaders, who were concerned about disruption during Victrola’s peak sales quarter. To address these concerns, the team ensured the transformation was a business-led project, involving about 75% of Victrola’s leaders, Schneider said.

Another way the team worked to prevent operational disruption and build confidence in the stability of the new system was to involve a partner with deep expertise in SAP Cloud ERP. The right partner would also fit seamlessly into Victrola’s unique, candid, music-oriented culture, Schneider said, which it found in Reply.

“We wanted someone that could really provide that business knowledge on the public cloud,” he said. “From a timing perspective, we couldn’t afford to have people figuring out the project as they’re on the project, so it really was the expertise of the public cloud that was a huge part in this.”

With a winning team assembled, Victrola’s move to the public cloud was well-supported and bolstered by stakeholders across the company, SAP, and Reply.

Fine-tuning the foundation

Victrola’s SAP Cloud ERP transformation covered order-to-cash and finance processes as well as large warehouse operations. The implementation itself was strategically timed to avoid overloading the team during the critical Q4 sales period, and it took about six months in total. Schneider said that the business adapted to the new system gradually: within the first month confidence grew, and by four months post-launch operations normalized with ongoing fine-tuning.

Victrola chose not to migrate historical data due to changes in organizational structure when it came to data management and the greenfield nature of the cloud system. This decision avoided technical debt and complexity. In addition, legacy customizations were largely eliminated through fit-to-standard workshops.

“We were looking for the ability to adapt with us, and we wanted a system that could be as simple or as complex as we needed it to be,” Schneider said.

With the new cloud system, Victrola experiences greater trust in data accuracy and reporting agility. Financial processes have improved significantly, with profit and loss reporting time going from four hours to just 10-15 minutes. Faster closes and easier margin analysis contribute to Victrola’s improved agility, more informed decision-making, and stronger business performance.

“We’re more trusting in our data and that’s because we went through that exercise of really retooling what our landscape looked like and what our foundation looked like,” Schneider said. It’s because of that re-engineering of data and transactions that Victrola has eliminated over 250 hours of finance-related work.

The next track

Now that Victrola is running on the public cloud, the sky is the limit when it comes to growth and innovation. “When we think about our AI strategy, I’m no longer scared of our system,” Schneider said. “We’re now applying an AI strategy to a state-of-the-art system that SAP very much supports.”

When asked what advice he’d give to companies contemplating a move to the cloud, Schneider said that there is never a perfect time to start, but it’s better to welcome transformation rather than fear it.

“I don’t think there is ever a perfect time to do these transformations,” he added. “I do think once you get into them, you start to really embrace them and feel good about it and say ‘It’s happening, let’s go.’”

Interested in learning more about how SAP supports the transition from SAP ECC to SAP Cloud ERP? Get started here.

Photo courtesy of Victrola.

Sebastian Weber, CIO of E.ON, one of Europe’s largest energy companies, is quite amazed that humans don’t freak out more as technology that seems like science fiction becomes subtly ingrained in our lives.

He mentioned driverless cars in San Francisco, autonomous drones conducting warfare, and robots that are trained to care for humans as real humans would. Speaking at the recent TAC Insights sponsored conference featuring SAP for Energy and Utilities, Weber admitted he finds it all rather scary, but also very exciting.

For an energy company operating critical infrastructure, this pace of technological change is not just fascinating or frightening—it creates a responsibility to adopt innovation in a controlled, resilient, and purpose‑driven way.

Riding the waves

Weber sees these developments as a continuation of various “big waves” of technology that keep touching our hearts and minds as they shape the world around us. Who can imagine the world without the internet? Who can deny that the mobile phone didn’t revolutionize the consumption of IT when people started expecting the same ease of use in the workplace?

“AI is creating the same response,” Weber explained. “ChatGPT makes my life easier at home solving gardening issues, so I expect it to make my life easier at work.”

One of E.ON’s biggest challenges is closing the widening gap between the rapid pace of technological innovation in the outside world and the organization’s internal ability, shaped by its structure and DNA, to absorb and implement these changes effectively.

This tension became evident when leadership questioned whether sustained IT spending at large scale was justifiable. It soon became clear that continuous investment is the price of system stability, affordability, and resilience in a digitized energy system if E.ON is serious about becoming the leading playmaker in Europe’s green energy transformation.

To achieve this ambition, the company has defined three strategic priorities—growth, sustainability, and digitalization—recognizing that falling behind in digital capabilities would carry far greater long-term costs.

“Bringing the system up to speed requires internal readiness. It means we must think deeply about investments, prioritization, and most importantly, people and culture,” said Weber. “One thing is sure: we won’t be going back to what was normal speed before.”

Becoming strategic

E.ON operates across three domains: energy grid, customer solutions, and energy infrastructure solutions.  This broad scope creates a high level of operational complexity, requiring scalable, transparent, and collaborative ways of working across the organization.

To meet these challenges, E.ON is strengthening its internal capabilities and investing in its people. By expanding in-house expertise, the company has welcomed over 1,000 specialists, including more than 500 in data and 300 in cybersecurity, fostering greater ownership, collaboration, and innovation across the organization.

This move reflects a broader philosophy. IT is no longer just a support function; it is foundational to pioneering the energy transition and delivering competitive advantage.

As E.ON’s transformation unfolds against a backdrop of rapid technological evolution, AI is at the heart of the current inflection point. Technologies like AI-powered assistants and automation tools are not novelties; they are actively redefining how customers interact with services. E.ON recognizes this shift and is embedding advanced technologies directly into its core systems, rather than treating them as add-ons.

Closing the gap

Weber explained that digital transformation at E.ON means putting the right technology into the core of the business to better serve its 47 million customers.

It starts with platform standardization, followed by cloud ERP transformation and the SAP S/4HANA migration. Instead of building fragmented custom solutions, this strategy allows the company to integrate leading technologies into a cohesive architecture, ensuring scalability while avoiding unnecessary complexity. These basic investments in foundational infrastructure have delivered tangible results, including an 77% reduction in IT downtime within five years.

A key lesson from E.ON’s journey is the importance of embedding digital capabilities into the heart of operations. “We’ve moved away from isolated innovation hubs such as digital labs or experimental ‘garages’ in favor of integrating digital tools directly into business processes,” Weber explained.

While innovation is essential, E.ON places equal emphasis on governance and control. Managing a digital ecosystem at this scale requires strong oversight to ensure security, consistency, and cost discipline. The company implemented centralized governance structures, including standardized contracting and unified IT system management to help maintain control without stifling innovation.

Equally important is investment in people. Through targeted training and capacity building initiatives, employees are empowered to turn new technologies into measurable business impact.

Harnessing AI

As with many companies, AI is at the center of E.ON’s forward-looking strategy, but the company is approaching it with deliberate caution. Rather than rushing to build proprietary platforms, E.ON is leveraging partnerships with established technology providers while maintaining flexibility in its IT portfolio. This approach allows the company to explore the potential of AI in customer service automation, predictive maintenance, and operational optimization without overcommitting to unproven solutions.

“In essence, our experience highlights a broader truth about digital transformation,” said the IT expert. “Success really depends on balance. We absolutely must push innovation forward, but not at the expense of stability, cyber security or governance.”

Equally, digital tools alone are not enough. Without proper training and alignment with business needs, even the most advanced technologies can fail to deliver value. E.ON addresses this through a “BizDevOps” mindset, ensuring that digital initiatives are an integral part of business goals and supported by the right capabilities.

In summary, E.ON’s transformation illustrates what it takes to modernize at scale in a complex, highly regulated industry. By doubling down on IT investment, bringing expertise in house, and adopting a disciplined yet forward-looking approach to innovation, the company has positioned itself for the future of energy.

The result is not only improved system performance or reduced downtime. It’s a fundamental shift in how technology drives business success, turning technology into a cornerstone of making new energy work—reliably, affordably, and at scale.

Earlier this year, SAP welcomed senior procurement leaders from automotive, industrial manufacturing, aerospace, and defense organizations to our annual Direct Procurement Customer Roundtable in Walldorf. These companies manage some of the most complex product portfolios and supply networks in the world. Direct materials represent their largest spend category—and their largest risk surface. They understand deeply where value is created, where it erodes, and where operational risk accumulates.

What made the event distinctive was its candor. Customers did not come to present polished success stories. They came to compare realities. And those realities were refreshingly honest.

Why direct procurement is hitting a breaking point

The pressure on direct procurement is not coming from one direction. Geopolitical instability and accelerating technological change are forcing sourcing decisions earlier in the product lifecycle, at precisely the moment when many organizations are least equipped to act. Meanwhile, institutional knowledge is leaving faster than systems are modernizing. The experienced individuals who once held fragile processes together are retiring or moving on, and the systems meant to replace that knowledge are not yet ready.

The result is an operating model that prevents procurement leaders from influencing value at the moments that matter most. Several customers described a tension they are actively dealing with. Sourcing is being pulled upstream into design and development, while the tools and processes that support it are still anchored downstream.

What customers shared about their reality

While all participants operate with a strong SAP footprint, spanning SAP ERP and SAP S/4HANA, many acknowledged that direct materials sourcing remains fragmented and disconnected from the digital core. The picture they described was familiar but worth stating plainly: engineers, buyers, and suppliers still collaborating through e-mail, local tools, and disconnected applications; there’s an overreliance on a small number of experienced individuals to make things work; and multiple ERP landscapes run in parallel, with direct sourcing living largely outside all of them.

One observation stood out clearly. The real friction is not the sourcing events themselves. It is the handoffs, the gaps between systems and teams where decisions get made too late, data is reconciled manually, and no single digital thread connects product intent to sourcing execution.

In other words, the process functions, but it functions in silos.

Participants also noted that traditional indirect source-to-pay approaches simply do not support direct materials adequately. They lack native support for procurement embedded in new product development, sourcing scenarios that evolve with engineering change, demand aggregation across programs, and contracts treated as executable objects rather than static documents. That last point came up repeatedly, particularly the need to treat contracts as executable objects. This is also where the SAP Ariba direct materials sourcing add-on in SAP S/4HANA is starting to resonate more strongly in ongoing customer discussions.

Where customers are focusing next

What emerged from the discussions wasn’t a long list of priorities, but a firm shift in where companies are focusing their efforts.

Moving sourcing upstream into product development—rather than reacting after design decisions are already locked—was a consistent theme. So was reducing dependency on hero buyers: individuals whose personal expertise and relationships are currently holding critical processes together.

Commodity volatility and renegotiations also came up as structural challenges, not one-time events. Organizations want to handle these systematically rather than heroically. And several participants raised the reality of managing multi-year SAP S/4HANA journeys without stalling progress in the meantime—a genuine tension that demands honest road map planning.

While the direction is widely understood, most organizations do not yet have the setup to execute against it at scale.

These priorities help explain why customers are increasingly adopting the SAP Ariba direct materials sourcing add-on alongside SAP Ariba Procurement Planning, SAP Integrated Product Development, and SAP Business Network—capabilities that together can support the connected execution model direct procurement actually requires.

How AI fits into direct procurement

AI generated significant interest, but expectations were measured and, I would say, appropriately so.

The consistent message was this: AI only matters once the fundamentals are addressed. Agent-based capabilities depend on clean processes and consistent data. Without a unified digital thread across product design, sourcing, contracting, and execution, AI does not generate insight—it amplifies noise.

Leaders also expressed clear skepticism toward black-box automation. They want AI that is explainable and embedded directly into sourcing, negotiation, and execution workflows, not layered on top of broken processes and presented as a fix.

This thinking aligns closely with SAP’s vision for the Autonomous Enterprise, introduced at SAP Sapphire just weeks after our Walldorf discussions. The vision anchors AI agents directly in transactional business processes, data, and governance—exactly what customers said they needed before they could trust AI in direct procurement environments. Hearing them articulate that requirement so clearly, before the announcement, felt like meaningful validation.

Where this is all heading

The Walldorf roundtable confirmed a clear trajectory. Direct procurement organizations are moving away from heroics and spreadsheets and toward system-led execution. They are aligning sourcing transformation with their SAP S/4HANA road maps and preparing their organizations—not just their systems—for a future where AI supports decision-making across the full procurement lifecycle.

Direct procurement, seen through this lens, is not a standalone transformation. It is a foundational building block. Connecting product, sourcing, contracts, and execution through a single digital thread is what enables AI to operate accurately, compliantly, and at scale. That connection has to exist before any of the more ambitious automation goals become realistic.

For SAP, conversations like the one in Walldorf directly inform our product direction and investment priorities. There is no substitute for sitting in a room with people navigating these challenges every day, without a script.

What was clear in Walldorf is that the direction is no longer in question for participating organizations. The challenge now lies in execution and in how quickly organization can move from fragmented, person-dependent processes to cohesive models that reflect how direct procurement operates today.

Karolina Bombardelli is global go-to-market lead for Direct Procurement at SAP.

The European Union took a landmark step with the EU Pay Transparency Directive, requiring employers to make pay practices more transparent and equitable. This represents a significant move toward greater accountability at a time when the gender pay gap across the EU still averages 11%, despite decades of equal pay legislation throughout Europe. 

Now, the countdown is on. By June 7, all 27 EU member states are expected to adopt the directive into national law, marking what many HR leaders are calling “Day One” of a new era in workplace transparency.  

But while the deadline is fast-approaching, many organizations are still far from operationally ready. Even though employers will be required to share pay information with both employees and candidates during the recruiting process, current practices suggest a significant gap. For example, across Europe, salary disclosure in job postings remains inconsistent and often limited, according to recent data.

For HR leaders, the challenge is no longer understanding the directive—it’s executing on it with confidence.

The barrier to execution 

For many organizations, the challenge often starts with the state of their HR and compensation data. In multinational organizations, compensation data often spans multiple systems, payroll providers, spreadsheets, and local processes. Job classifications vary across countries, salary bands are not consistently defined, and workforce data remains siloed across regions. 

As a result, many organizations struggle to produce consistent pay comparisons, define standardized salary ranges, explain compensation decisions clearly, and generate accurate reporting across multiple countries. 

Without a connected and reliable workforce data foundation, pay transparency becomes difficult to operationalize at scale. 

Building a foundation for continuous transparency  

The organizations making the most progress are focusing first on data consistency, workforce visibility, and connected HR processes. 

This is where technology is becoming critical. AI can help organizations move beyond manual reporting by identifying pay anomalies, surfacing unexplained pay variance, and accelerating workforce equity analysis across large, complex data sets. 

With pay transparency insights (generally available on June 5),  a capability within the People Intelligence package in SAP Business Data Cloud, organizations can unify compensation and workforce data across systems while applying AI-assisted analysis to help identify inconsistencies, support explainable pay decisions, and improve reporting readiness. 

Instead of relying on fragmented systems and disconnected reporting processes, organizations can move toward a more consistent and scalable approach to transparency. 

Three areas HR teams need to execute now 

With the right data foundation in place, organizations are better positioned to address the directive’s three major operational requirements. 

1. Enabling employee pay transparency 

Under the directive, employees have the right to request information about average pay levels by gender for comparable work. For many organizations, this immediately exposes data consistency issues. Comparable roles may be classified differently across countries or business units, while compensation data often lives in disconnected systems that were never designed to work together. 

SAP SuccessFactors HCM helps organizations provide employees with pay transparency statements through SAP SuccessFactors Employee Central while supporting more consistent comparisons across worker groups. These statements can give clear insight into the employee’s annual pay and the average pay of the same worker category broken down by gender.  

2. Preparing for candidate pay transparency 

The directive also requires employers to disclose salary ranges in job postings or before interviews and prohibits asking candidates about salary history. While this may sound straightforward, many organizations are discovering they lack standardized pay ranges, consistent job architecture, or alignment between recruiting and compensation systems. 

SmartRecruiters for SAP SuccessFactors allows organizations to display salary ranges directly within job postings and support more transparent hiring experiences. AI-driven recommendations can also help organizations establish more consistent pay ranges aligned to internal equity, external benchmarks, and evolving workforce needs. 

3. Meeting gender pay gap reporting obligations 

Mandatory gender pay gap reporting represents one of the directive’s most operationally demanding requirements. Annual reporting obligations begin in 2027 based on 2026 workforce data, meaning organizations need to prepare now.  

For many HR teams, the challenge is turning complex, multi-country workforce data into accurate and defensible reporting. With pay transparency insights, organizations can use AI-assisted analysis to identify potential drivers behind pay gaps, surface workforce equity insights more quickly, and support more proactive decision-making before reporting deadlines arrive.  

What HR should do now 

The EU Pay Transparency Directive is not just introducing a new compliance requirement. It’s accelerating a broader shift toward continuous transparency in how organizations manage compensation, hiring, and workforce equity. 

The organizations best prepared for this shift are taking action now to: 

• Unify workforce and compensation data 
• Standardize job and pay structures 
• Improve reporting readiness 
• Build more consistent, explainable compensation processes across the business

As transparency expectations continue to grow among employees, candidates, regulators, and business leaders, pay equity can no longer operate as a periodic reporting exercise. It is becoming an ongoing operational capability. 

Watch the webinar replay to learn how to move from policy to execution and prepare your organization for EU Pay Transparency requirements at scale.  

Maryann Abbajay is chief revenue officer for SAP SuccessFactors.