Lunch Box - Increasing Maturity Levels of AI in Engineering Teams

Most enterprises are experimenting with AI in software engineering — but few are seeing real, systemic impact. One of the reasons: Today, the conversation is still largely focused on individual productivity: How can we make a single engineer faster? How do we create “10x developers”?
But this perspective is too narrow. To unlock the full potential of AI, we need to move beyond isolated productivity gains and rethink the entire process from idea to production.

This session introduces a practical maturity model that captures how organizations actually evolve: From resistance and strict control to shadow usage and vibecoding to AI-augmented individual performance.
But there are further stages — where the real transformation begins: Not just optimizing developers, but fundamentally redesigning how software is built, integrated, and operated across the SDLC.

Georg Kreimer (ex-Celonis, ex-Hybris) developed a 5-level maturity model for AI in software engineering.
In this talk, he shares the model and discusses what it actually means in practice — across organization, processes, tools, training and governance.

-------- What to expect --------
- A realistic view on how enterprises adopt AI in engineering
- Why most companies are stuck at early maturity levels
- What changes when moving from individual productivity to system-level thinking
- Practical implications for scaling AI across the SDLC

-------- Who should join? --------
Engineering leaders and architects, Platform and DevOps teams, AI and data practitioners, anyone working on bringing AI into software development beyond experimentation

-------- About the group --------
The AI Native Enterprise is a community for people who believe that AI is not just a feature, but a fundamental shift in how organizations are built and operated.