Supply chain teams never lack decisions to make. What they increasingly lack is time.
I’ve spent most of my career building supply chain technology to drive business outcomes at scale. Earlier in my career, nobody was talking about AI. But I was helping build what we’d now call an autonomous supply chain.
At scale, manual decision-making simply cannot keep pace with growing consumer expectations. That’s why the next phase of supply chain AI needs to move beyond analysis to help organizations turn insights into action across the processes and applications that move goods.
Decision velocity: where supply chain speed is won or lost
Even the most intelligent supply chains can struggle to turn a meaningful signal into a well-governed response. I think of that as decision velocity: how quickly an organization can recognize change and coordinate the right response based on relevant business context.
In supply chain, decisions are inherently interconnected. Planning affects manufacturing, which depends on product and asset readiness, suppliers, logistics partners, and more. I hear this from our customers today: each decision could be rational; the sum of them was not.
AI can automate individual tasks, but isolated intelligence only creates isolated value.
Agents need to understand how a decision in one domain affects the next. That’s where supply chain applications become critical, providing the business context, connected processes, and controls that agents need to act.
New Joule Agents extend AI across the supply chain
This year at SAP Connect, we’re expanding the capabilities of six Joule Assistants introduced earlier at SAP Sapphire and adding specialized Joule Agents that can take on critical supply chain tasks. These capabilities will help organizations respond faster and automate more routine work while keeping people at the center of informed decision-making:
- The Product Design Assistant will be able to interpret product designs, recipes, and specifications and orchestrate compliant product changes, helping accelerate time to market.
- The Supply Chain Planning Assistant will help planners sense, simulate, and resolve exceptions in a single workspace, helping teams understand downstream impacts and address disruptions before they ripple across the enterprise.
- The Manufacturing Assistant will help teams respond to plant-floor disruptions as they happen, while new capabilities in the Logistics Assistant span warehousing, outbound optimization, fulfillment, and transportation dispatching, helping turn logistics insight into action.
- New agentic capabilities for the Asset Operations Assistant will help translate equipment and maintenance signals into action by supporting the initiation, screening, and simulation of maintenance requests. And the Business Network Assistant will improve collaboration with suppliers and logistics partners in areas such as sourcing, contracting, and exception handling.
What connects these scenarios is the ability for agents to operate within the business context already governing the supply chain, so an insight in one area can inform the next and, when authorized, trigger coordinated action. General availability for these new capabilities is planned for Q4 2026.
Customer results show autonomy taking hold
Customers are already putting this shift into practice.
Takeda Pharmaceuticals will use the Supply Chain Planning Assistant to help pinpoint likely causes behind planning issues and propose corrective steps, supporting adaptive planning processes over time.
Rebecca Kaufmann, senior vice president and head of Enterprise Platforms at Takeda Pharmaceuticals, said, “We are combining the SAP industry and technology knowledge with our organizational real-life experience. The Supply Chain Planning Assistant will provide us with AI-detected root causes and AI-suggested remediation and also automated performance tracking resulting in a self-healing capability.”
Doehler, a global producer of natural ingredients for the food, beverage, life sciences, and nutrition industries, is applying AI to logistics issue resolution.
Stephan Schissler, CIO at Doehler GmbH, says, “Our people’s greatest value lies in deciding what to do next—and now they can focus entirely on that. The Logistics Issue Resolution Agent detects the root cause, recommends the resolution, and turns a multi-hour firefight into a one-click decision. Our logistics team has recovered roughly a third of the time once lost to troubleshooting, and our processes are becoming self-resolving rather than exception-driven.”
This is how autonomy delivers practical value: moving from manually managing exceptions toward more intelligent supply chain processes.
Building autonomy on a foundation of trust
As AI takes on a greater role in supply chain decisions, trust must be built into how it operates. Leaders need to understand what AI decided and why, define what it is authorized to complete, intervene when necessary, and know who is accountable.
That is the direction behind everything we are introducing at SAP Connect in 2026. By grounding Joule Assistants and their agents in the processes and data of the SAP Supply Chain Management portfolio, we can help organizations move from insight to coordinated action while keeping people at the center of the decisions that matter most.
For supply chain leaders, that is where autonomy becomes tangible: less time spent on routine work and resolving exceptions, faster responses when conditions change, and more time for the strategic decisions that strengthen resilience, efficiency and customer value.
Ultimately, it comes down to decision velocity you can trust.
Devesh Mishra is general manager and chief product officer for SAP Supply Chain Management.