AIR Regensburg Cluster Mobility & Logistics Rückblick (Cluster Mobility & Logistics)

Connected for Intralogistics

05/18/2026

M-AIR to Present AI Initiatives at Digital Day 2026 at Deggendorf University of Applied Sciences

On May 12, 2026, Digital Day 2026 took place at Deggendorf Institute of Technology. Under the guiding principle of “practical & actionable,” representatives from industry and academia came together to discuss specific applications of digital technologies for small and medium-sized enterprises.

The R&D network M-AIR – Multimodal AI for Adaptive Intralogistics and Robotics – was also in attendance. The project team used the event to distribute flyers and engage in direct conversations about approaches to making industrial intralogistics more flexible, understandable, and user-friendly in the future through AI applications. The focus included voice control, AI-based process support, and the question of how companies can gradually integrate new technologies into existing workflows.

The program offered numerous points of reference for this. Panels and practical sessions focused on the topics of AI agents, digitalization & sustainability, leadership & AI, and knowledge management with AI. The discussions during the networking breaks were particularly valuable. Many participants were seeking guidance on getting started with AI applications and were interested in concrete, robust, and transparent solutions beyond mere tool demonstrations. For M-AIR, it became clear that there is a great need for practical transfer formats—especially where AI intersects with real-world processes in production, logistics, and intralogistics.

We would like to thank the organizers of Digital Tag as well as all our discussion partners for the open exchange in Deggendorf.


NOTE

The M-AIR R&D network is funded by the Federal Ministry for Economic Affairs and Energy. The network brings together companies and research institutions that are jointly exploring new approaches for AI-based applications in production, logistics, and industry. The focus is on multimodal AI models for adaptive robotic systems and their use in intralogistics environments.

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