At Hannover Messe 2026, SAP used four industrial AI use cases to make a broader point for ERP leaders: the next phase of enterprise automation will not sit outside core systems, but inside the workflows where planning, production, logistics, service, and asset decisions are actually made.
SAP showcased how embedded intelligence can work across transactional environments tied to SAP S/4HANA and adjacent cloud applications, helping organizations move from visibility and alerts toward guided action and execution.
Live Use Case 1: Supply Chain Orchestration
SAP showed a supply chain system that acts like a central control hub, connecting planning, logistics, manufacturing, and execution in one place. It monitors what’s happening across the network and helps companies respond quickly when disruptions occur.
The system uses AI to pull in outside signals – like weather events, port delays, or supplier issues – and adjusts plans in real time. This helps teams spot problems early and make faster, data-driven decisions.
It also links planning directly with execution, so changes flow automatically into manufacturing and operations without needing manual updates.
Some of the key features include:
- Production Planning and Operating Agent for releasing orders and tracking them in real time.
- Supply optimization analysis that summarizes and explains planning data.
- Inspection robots that detect hazards, assess conditions, and identify root causes.
Analysis
What This Means for ERP Insiders
SAP’s Hannover Messe message suggests AI is being embedded into the handoffs between planning, shop-floor activity, logistics, maintenance, and service, where execution delays often create the biggest operational bottlenecks.
Live Use Case 2: Smart Production
SAP and DMG MORI showed a “smart production” setup running on a CNC machine, covering the full process from design and planning to actual production.
As the machine operated, the demo highlighted how everything is connected—from engineering and tool management to CNC programming and SAP Digital Manufacturing—so the process runs smoothly end to end. Operators can use a dashboard that provides AI-driven insights into operations and maintenance while the machine is running.
After production, the process flows into logistics using SAP Logistics Management, which brings together warehouse and transportation tasks, especially for smaller facilities. Joule, SAP’s AI assistant, helps by pulling together and prioritizing key shipment details, and can also provide real-time shipping rates.
Key AI features:
- Joule uses natural language to help manage warehouse and transportation tasks
- Joule’s AI agents provide manufacturing insights and support decision-making across the workflow
Analysis
What This Means for ERP Insiders
The real opportunity is workflow compression, not just better insight. SAP’s direction points to reducing the lag between detecting an exception and acting on it, whether that means validating production constraints, reserving materials, dispatching technicians, or orchestrating outbound tasks.
Live Use Case 3: Intelligent Packaging
SAP and Uhlmann demonstrated an “intelligent packaging” setup built around a high-speed production line, showing how systems connect from SAP S/4HANA to SAP Digital Manufacturing and into Uhlmann’s automation layer.
The demo followed the production of packaged ginger shots, with autonomous mobile robots from Symovo moving products away from the line. It showed how SAP supports regulated industries like pharmaceuticals and life sciences, with built-in compliance and end-to-end visibility across the production process.
The setup is designed to speed up operations by reducing order processing time, while also improving inventory visibility, data consistency, and reducing the need for manual intervention.
Key AI features
- AI-driven condition monitoring to improve equipment uptime and service efficiency
- Flow analysis tools that help model processes and optimize production
- Agent-based exception handling to identify and resolve issues automatically
- Joule AI agents that support decision-making across the workflow
- Joule-powered insights for orders and production lines
Live Use Case 4: Humanoid Robotics
At the end of the line, SAP also showed a humanoid robot as part of its Project Embodied AI, performing physical tasks and connecting digital planning with real-world execution.
The idea is to use humanoid robots to handle repetitive, complex, or hazardous tasks, helping improve throughput, reduce downtime, and maintain better alignment between planning and execution. These systems can also improve inventory visibility and data accuracy across warehouse operations.
Key AI features included Joule and Joule Studio enable robots to understand their environment, make decisions, and learn over time.
The benefits of humanoids include increased operational speed and higher throughput, improved uptime and cost efficiency in areas that are dangerous or difficult for humans, and better alignment between planning and execution.
A recent pilot by SAP, Accenture, and Vodafone Procure & Connect integrating humanoid robots with SAP Extended Warehouse Management (SAP EWM) shows how these robots can operate safely in warehouse environments and report findings back into SAP systems in real time.
From AI insight to operational AI execution
SAP’s Hannover Messe demos point to a shift from AI as a reporting tool to AI embedded directly in day-to-day operations. Across supply chain, production, packaging, and robotics, the focus is on connecting systems, automating decisions, and responding to disruptions as they happen.
While the use cases are still evolving, they show how AI agents like Joule are starting to play a more active role in running industrial processes, not just analyzing them.
Analysis
What This Means for ERP Insiders
This raises the strategic importance of AI-ready ERP architecture. As SAP connects AI agents to SAP S/4HANA, workforce scheduling, logistics, asset management, and business network processes, the underlying architecture matters as much as the AI itself.
