AI agents: hype or real added value for your supply chain?
How AI agents can support your SCM processes
AI agents are currently one of the most discussed topics in AI. However, their classification is particularly difficult in supply chain management: complex dependencies, heterogeneous systems, and high operational risks make it difficult to separate real added value from exaggerated expectations.
In our webinar on March 19, 2026, at 10 a.m., we will provide clarity: Using a live demo, we will show how AI agents can be integrated into existing SCM landscapes in a pragmatic, controlled, and profitable manner, and what advantages this offers.
What you can expect in the webinar:
- Clear classification: What AI agents really are in the SCM context—and how they differ from traditional automation and analytics.
- Specificuse cases: Which agentic applications are already realistic and economically feasible today.
- Livedemo: How agents adjust demand forecasts, analyze ERP statuses, and intelligently align production and sales plans.
- Informed decisions: Simulation and evaluation of plan variants at the machine level , including specific recommendations for action.
- Control & Governance: How changes can be securely written back into the system using guardrails, approval logic, and transparency .
- Structured guide: How to integrate AI agents into your existing SCM processes step by step.
Take this opportunity to learn about the requirements for the effective use of AI agents in the SCM environment—and the benefits you can realistically expect today. Click here to register for the free webinar:
Speaker
Janek Kapahnke has been developing planning and analysis solutions with customers from various industries for over 5 years. Today, he is responsible for the area of supply chain management and focuses on innovative solutions for current challenges in supply chain planning.
Florian helped build up the smart data division at celver AG from the very beginning, focusing in particular on cloud, data science, and AI. As team leader for data science, he is responsible for projects related to the development of modern, cloud-based data platforms and the development of machine learning and AI solutions. His focus is on implementing scalable architectures and data-driven applications that create measurable added value for customers.
