Four AI Use Cases SAP Showcased at Hannover Messe for Embedded AI in Operations

SAP outlined four AI-driven use cases at Hannover Messe 2026, showing how artificial intelligence is moving beyond analytics into real-time manufacturing and supply chain operations.

According to the company, the demonstrations focused on how embedded AI agents can improve resilience, reduce downtime, and speed up decision-making. SAP said the use cases connect digital intelligence with physical processes across production, logistics, asset management, and end-to-end supply chain orchestration.

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.

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

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. 

What this means for SAPinsiders

Execution, not visibility, is becoming the AI benchmark. Manufacturers have invested in analytics for years; SAP’s demos show value shifting to AI embedded in execution workflows, where decisions directly impact production, logistics, and service outcomes.

AI agents are redefining ERP’s role in operations. By embedding intelligence into core processes, ERP systems evolve from systems of record to systems of action, orchestrating real-time responses across supply chain functions.

Physical AI is emerging as the execution layer of operational AI. The integration of robotics, logistics execution, and AI-driven workflows signals a shift toward operational AI as an umbrella, with physical AI systems such as robotics translating digital decisions into real-world processes and measurable throughput outcomes.