Daniel Peys, M.Sc Email | LinkedIn Project status: running

Problem Statement

Digital transformation and artificial intelligence, especially generative AI (GenAI) and agentic AI (AAI), are significantly reshaping enterprise business models and pro-cesses creating new potentials for competitive advantages and strategic differentia-tion. AI agents are on the rise to augment and accomplish human work across all kinds of processes and business domains. Managing and exploiting huge amounts of heterogenous data across the value chain represent critical success factors to leverage GenAI and AAI with right-time and right-quality data. In particular, upcom-ing protocols and technologies for AAI, e.g., A2A, MCP and UTCP, are placing new requirements on data management in enterprises. Hence, established enterprise data management concepts, architectures and platforms have to be revised in view of concepts such as the agentic enterprise and the agentic web.

In this research project, novel concepts and techniques for enterprise data management specifically tailored for agentic AI will be investigated and prototyped to assess their applicability and potential. The key question of this research project is

“What are novel enterprise data management approaches for agentic AI?”

Key Publications