• Which current tasks in reporting, monitoring, or communication could be fully automated?
• How could an AI agent improve your daily work experience?
• Which risks do you see if AI takes over communication with stakeholders (e.g., wrong message, lack of context)?
• Would you trust an AI agent to start a process on its own (e.g., reordering materials, rescheduling production)?
• What is the “low-hanging fruit” for AI in your company, and what is still too complex?

Digitalization and Industry 4.0 came with bold promises: unlocking technological and economic potential. But where do we stand today – and what have we actually achieved over the past decade? The numbers are telling: while the IT market volume has doubled, productivity has stagnated. Many projects fail before completion, run over budget, or fall short of expectations. This presentation explores causes within implementation projects and outlines a solution that connects, modularizes, and flexibilizes processes and data – to finally unlock the true potential of digitalization sustainbale.

• why digitalization has so far failed to deliver on its productivity promise.
• how process and data integration challenges hinder IT/OT transformation.
• how AI agents and LLMs can automate evaluations, process analyses, data classification, and root cause analysis within a UNS.
• what productivity gains leading studies expect from agentic AI in industrial processes.
• how an integrated process-data model becomes not just managed, but actively orchestrated by AI agents.

• Where do you see the biggest obstacles to implementing AI agents in your current IT/OT landscape?
• Which processes in your company could be most easily automated or supported by agentic AI?
• How can we ensure trust, transparency, and accountability when AI agents make or trigger decisions?
• What role will standards and governance play in scaling UNS-based AI use cases?
• How do we balance quick PoCs with the need for robust, long-term architectures?