The Data-Driven Workshop: Key Insights from the AW 4.0 Industry Session

To enable AI in real-world workshops, we must first rethink how data is shared, governed and used. At the Car Repair 4.0 workshop, the industry started doing just that.

Intro:

In August 2023, the DE-CIX MeetingCenter in Frankfurt became a hub of future thinking for the automotive aftermarket. The workshop, hosted by eco – Association of the Internet Industry and the Autowerkstatt 4.0 project, brought together leading voices from suppliers, service providers, mobility platforms, and research institutes. The mission: to discuss how data and AI can reshape independent workshops and enable new service models.

Represented companies included: ZF Aftermarket, Schaeffler, Continental, ADAC, DAT, Goodyear Retail Systems, Daimler Truck, IfA, Driver (Pirelli Group), GRS, MS Motorservice, Knorr-Bremse, Pico Technology and others.

Participants of the AW 4.0 industry workshop at DE-CIX MeetingCenter, hosted by eco and LMIS, with experts from ZF Aftermarket, ADAC, Schaeffler, DAT, Goodyear, Daimler Truck, and others – working together to shape a shared data and AI ecosystem for the future of automotive repair.

Why this matters:

To make AI work in real-world workshop environments, we must rethink how data is shared, governed, and translated into value. The 2023 AW 4.0 workshop marked a concrete step in that direction—where practical experiences, structural challenges, and collaborative intent converged. Context: The Autowerkstatt 4.0 project, supported by the German Federal Ministry for Economic Affairs and Climate Action (BMWK), is building a reference architecture for safe, explainable AI in diagnostics and repair. Within the Gaia-X ecosystem, it aims to demonstrate how data sovereignty, trusted data sharing and AI readiness can be turned into real-world impact.

At the workshop, industry participants shared practical challenges from the shop floor: fragmented data systems, tool incompatibility, limited access to manufacturer data, and knowledge silos among technicians. The consensus was clear: data must become a shared asset – not a competitive bottleneck. Signals from the Workshop:

• Data quality and sharing models will define who can lead. Poor standardization and high licensing costs make data access a privilege. That must change.

• Repair intelligence needs structure. AI is only as useful as the data it's built on. Semantics, interfaces and technician trust are key enablers.

• AI can help fight the skills gap. But only if paired with intuitive tools and continuous upskilling programs.

• Gaia-X principles must guide design. Sovereignty, interoperability, security and modularity are not optional for future-ready workshop systems. What comes next: The workshop ended not with a pitch, but with a shared recognition: that scaling digital services in workshops requires collaboration, standardization and trust. AW 4.0 will continue developing the conditions for AI to succeed – but adoption will depend on whether the industry sees this as a system challenge, not just a tech update.

Final Thought:

"The future workshop won’t just be connected. It will be collaborative."

Want to help build the digital foundation for smarter workshop systems? Let’s connect.