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.

I’m proud to share that SAP has once again been recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Warehouse Management Systems (WMS)*. In our opinion, this recognition underscores SAP’s continued commitment to innovation in warehouse execution and reflects the confidence our customers place in SAP to run some of the world’s most complex, high-performance, and mission‑critical warehouse operations.

In today’s environment of ongoing disruption, rising customer expectations, and persistent labor and cost pressures, warehouse operations are more strategic than ever. We believe long-term recognition in this market requires more than point solutions; it demands scale, depth, and an orchestrated approach that connects warehousing with other supply chain functions.

A recognition we believe is built on scale, reach, and execution

We believe scale matters when it comes to warehouse management. Warehouse operations are increasingly complex and diverse, and organizations often operate networks that span regions, industries, and levels of automation. Warehouse management is not a one‑size‑fits‑all challenge, and global organizations need solutions that can support regional requirements while remaining consistent and integrated across complex networks.

SAP Extended Warehouse Management (SAP EWM) is designed to support organizations running SAP ERP or SAP S/4HANA as well as non-SAP environments. With customers across 24 industries, SAP EWM supports a broad range of warehouse complexity—from regional distribution centers to highly automated, high‑throughput operations. It enables organizations to standardize execution, improve visibility, and integrate warehouse processes with transportation, manufacturing, and broader supply chain operations.

SAP EWM continues to expand its innovation footprint with APIs for seamless robotics integration, as well as AI-assisted capabilities such as predictive labor demand planning and slotting. SAP’s Joule AI solution—embedded across applications—can further enhance SAP EWM by enabling natural-language interactions and supporting AI capabilities that operate both within workflows and in the background, helping organizations improve workforce efficiency and execution agility.

A portfolio approach to meet different warehouse needs

SAP’s warehouse strategy is built around choice and flexibility. In February 2026, SAP announced the general availability of SAP Logistics Management, an AI‑enabled, cloud‑native, microservices-architecture-based solution designed to complement SAP’s established logistics portfolio by supporting local, satellite, and mid‑scale logistics operations.

SAP Logistics Management helps unite warehouse execution and transportation planning in a single solution, supporting pick‑pack‑ship processes while enabling integrated freight coordination and carrier collaboration through SAP Business Network. Designed to work seamlessly with SAP Cloud ERP Private, the solution helps organizations connect localized operations with broader enterprise landscapes, improving coordination and real‑time visibility across logistics networks. Embedded AI capabilities, including support for Joule, can assist users with faster decision‑making and more intuitive interactions across logistics workflows.

Together, SAP EWM and SAP Logistics Management enable organizations to align technology investments with operational complexity, supporting mixed warehouse networks that include both highly automated facilities and smaller, distributed sites.

Platform strategy and supply chain convergence

Warehouse execution does not operate in isolation. SAP’s platform strategy connects warehousing with transportation, manufacturing, quality, maintenance, global trade, sustainability, and partner collaboration across the supply chain.

SAP EWM can be used with SAP Signavio solutions to support process analysis and continuous improvement. It can leverage standardized APIs across SAP ERP and SAP S/4HANA to connect with adjacent execution systems such as transportation management, global trade, environmental health and safety, and SAP Digital Manufacturing. This platform-based approach helps organizations move beyond siloed execution toward coordinated, end‑to‑end supply chain

Looking ahead

SAP remains focused on helping customers modernize warehouse operations while navigating broader ERP and cloud transformations. While organizations must carefully evaluate deployment models, cloud strategies, and long‑term road maps, SAP continues to invest in warehouse management solutions that scale globally, integrate deeply, and support evolving business requirements.

We believe that being recognized by Gartner as a Leader for the 12^th consecutive time reflects continued execution across SAP’s warehouse management portfolio and the trust customers place in SAP to manage critical logistics operations worldwide.

Read the full Magic Quadrant report from Gartner to learn more about why SAP is a Leader. Learn more about the capabilities of SAP Extended Warehouse Management.

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

*Gartner, Magic Quadrant for Warehouse Management Systems, by Simon Tunstall, Rishabh Narang, Federica Stufano, 29 April 2026.

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

If you haven’t heard about AI agents, you might want to check if your Wi-Fi’s working, or maybe you really have been living under a rock. In just a short time, these digital co-workers—or assistants, copilots, and other nicknames—have taken center stage in tech. And the hype is real. Expectations for what AI agents can do are sky-high; some imagine they’ll soon run the whole show, making decisions for us while we sip our coffee. But do we really want them to do everything on their own? And can they actually do that?

As companies race to implement this new technology, they’re discovering it’s not all as smooth as envisioned. Following a recent Gartner report, high costs and fuzzy business value are creating speed bumps. As it turns out, the technology itself isn’t the problem, it’s how and why we use it. Like any shiny new gadget, AI agents only matter when they solve real problems that make people’s lives easier. So, what kinds of issues are they good at tackling? And how do we make sure we’re designing systems that serve actual humans and are not just chasing the latest tech trend?

That’s where things get interesting: deciding when you truly need an agent, how much freedom it should have, and what challenges and tasks it’s meant to address all while ensuring it genuinely helps people, instead of just ticking the “we use AI” box. The real magic happens when humans and agents team up, working side by side for the best results. How do we make the most of this human-agent partnership?

If you’re looking for a practical way to get started, the SAP AppHaus Joule Agent Discovery and Design workshops offer a hands-on approach to help tackle these exact questions. With a blend of human-centered design methods, these workshop formats put people first, working to ensure agentic systems aren’t just flashy but genuinely useful.

Want to try it out for yourself? Here’s how you can run your own workshops and define impactful agentic systems.

A toolkit to build human-centered agentic solutions

The Joule Agent workshops are offered as two different formats, each designed to guide you through a different stage of building effective agentic systems: the Joule Agent Discovery workshop and the Joule Agent Design workshop. Together, these workshops provide a hands-on, human-centered path for creating AI agents that can truly deliver value.

First stop: Joule Agent Discovery workshop

The Joule Agent Discovery workshop is a structured approach to uncover the most valuable opportunities for agentic technology. It focuses on real-world challenges and identifying where automation can make the biggest impact. In two to three hours, participants dive into questions such as: What specific inefficiency or challenge needs solving? What could be automated? Who would benefit most from automation? What needs to be achieved with the automation? How complex and variable is the problem at hand?

The workshop also introduces participants to agentic technology and examines how much the selected challenges would benefit from it. By the end of this workshop, participants identify one or more high-value use cases that are well-suited to agentic technology. This helps ensure that efforts are focused on meaningful improvements rather than adopting technology for its own sake.

Second stop: Joule Agent Design workshop

Next is the Joule Agent Design workshop, which brings together those closest to the process—end users and business experts—to define the details of the agent: its responsibilities, required skills, and how it will collaborate with people. The workshop follows a practical structure:

1. Define the focus area: Clarify what target users need to achieve within the selected process and identify which aspects would benefit most from automation.
2. Identify tasks to delegate: Use the metaphor of “hiring a super-specialist” to decide which responsibilities should remain with people and which can be assigned to agents. Exercises help determine how many agents are needed, the risks of automating certain tasks, and where consistency versus autonomy is required.
3. Describe the super-specialist job: Draft a job description for each agent, outlining necessary skills and responsibilities.
4. Instruct the super-specialist: Define the instructions or workflow, including information requirements, decision points, and where human involvement is needed.

By the end of the workshop, each agent is described in detail, including its tasks, required knowledge and tools, and an initial set of instructions. This forms the foundation for configuring the agent’s system prompt.

The workshop material also offers guidance on structuring the system prompt based on the gathered information, ensuring a smooth transition from workshop insights to practical implementation. The entire process is designed to be completed in a single day and can be conducted virtually in Mural.

Learning how to run these workshops

To help ensure that anyone can confidently run these workshops—no advanced degrees or secret codes required—a set of self-paced courses are available and can be completed at the individual pace of the learner:

• Discovering High-Value Opportunities for Agentic AI: This course offers a comprehensive introduction to the Joule Agent Discovery workshop. It provides a clear, step-by-step guide, explains the exercises in detail, and gives practical advice on how to facilitate effective sessions. You’ll gain the skills to identify agentic opportunities and successfully lead your team through the process.
• Spotting Agentic Opportunities in Practice: This short webinar also centers on the Joule Agent Discovery workshop, but it specifically highlights a practical method for assessing the agentic potential of automation ideas. Consider it your quick reference for making informed decisions about automation.
• Designing Agentic Systems with a Human-Centered Approach: The latest addition to our curriculum, this course walks you through the Joule Agent Design workshop step by step. It covers each exercise, shares real-world examples, and offers facilitation tips. You’ll also learn how to adapt the workshop format for various time constraints and organizational needs.

All the resources required to facilitate these workshops are freely available on the innovation toolkit for AI website. Learners can simply visit the site, explore the materials, and start their agentic journey with confidence to turn ideas into new useful, human-centered AI solutions.

Karen Detken is an expert user experience designer at SAP AppHaus.