Shaping Standards for Physical AI and Agentic AI: Two AI Workshops

Two interactive workshops exploring safety, interoperability, transparency, and future standardization requirements for Physical AI and Agentic AI.

As artificial intelligence evolves beyond traditional software applications towards autonomous systems that make decisions and interact with the physical world, new challenges arise for safety, interoperability, transparency, and trust. The German Institute for Standardization (DIN) invites experts from research, industry, public administration, and standardization to explore how standards can support the development of trustworthy AI.

The event combines two workshops focusing on Physical AI and Agentic AI. The morning session examines AI-powered robots, machines, vehicles, and other physical systems, addressing safety requirements, interoperability, and priorities for future standards. The afternoon workshop focuses on autonomous AI agents and multi-agent systems, discussing transparency, security, and potential areas for standardization.

Participants can attend either workshop individually or join the full day. A shared lunch and networking session provides an opportunity to exchange perspectives and connect with professionals working on AI development and standardization.

Date: December 4, 2026
Time: 9:30 AM–3:30 PM
Location: DIN e. V., Burggrafenstraße 6, 10787 Berlin
Organizer: DIN – German Institute for Standardization
Participation: Registration required; access code: kinorm26
Audience: Researchers, AI developers, industry representatives, standardization experts, and public administration professionals
Focus: Physical AI, Agentic AI, AI safety, interoperability, transparency, trustworthy AI, and standardization
9:30 AM–12:00 PM: Workshop 1 – Standards for Physical AI
12:00–1:00 PM: Joint lunch and networking
1:00–3:30 PM: Workshop 2 – Standards for Agentic AI
Workshop format: Participants may attend one or both workshops
Goal: Discuss current challenges, identify potential standardization requirements, and prioritize future areas of action