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# Inside Mercedes-Benz: How CIO Katrin Lehmann is Empowering 5,000 Developers and Driving Digital Change

Mercedes-Benz CIO Katrin Lehmann argues that AI will not kill coding jobs, but instead skyrocket developer demand. Discover how she empowers 5,000 engineers to drive digital innovation.

- **Speakers:** [Katrin Lehmann](https://www.wearedevelopers.com/@katrin-lehmann), [Sead Ahmetovic](https://www.wearedevelopers.com/@sead-ahmetovic)
- **Event:** Coffee With Developers
- **Published:** July 2, 2025
- **Duration:** 43:55
- **URL:** https://www.wearedevelopers.com/videos/1360-inside-mercedes-benz-how-cio-katrin-lehmann-is-empowering-5-000-developers-and-driving-digital-change

## Summary

Mercedes-Benz CIO Katrin Lehmann’s transition from a two-decade tenure at SAP—where she rose to become their first Chief Data Officer—to leading enterprise IT for a historic automotive giant illustrates the accelerating convergence of legacy manufacturing and digital-first innovation. Managing all aspects of enterprise technology and a global community of 5,000 developers, she champions a data-driven, agile engineering culture. Her strategy emphasizes extensive platform engineering, integrating the SAFe agile framework, and actively using process mining alongside continuous developer surveys to eliminate corporate bottlenecks so engineers can focus on creative problem-solving rather than administrative hurdles.

A central theme of her leadership is the aggressive yet thoughtful adoption of artificial intelligence. By rolling out GitHub Copilot at scale and exploring agentic AI, Lehmann aims to significantly boost productivity. Recognizing that AI lowers the cost of software creation, she argues this will paradoxically increase the demand for developers as organizations seek to digitize everything. To govern this moving frontier, her executive team engages in weekly reverse mentoring sessions with internal tech experts, getting hands-on experience building their own AI agents and keeping leadership intimately connected to rapid tech cycles.

Reflecting on the broader European technology ecosystem, Lehmann urges a cultural shift toward greater tech investment and a tolerance for risk. She notes that while Europe has the educational foundation and talent, it often lacks the venture capital momentum found in the US. Drawing a parallel to early skeptics of the automotive industry—who believed the automobile would never replace the horse—she firmly dismisses fears that AI is a passing trend or a job-killer. Instead, she advocates for a future where continuous learning, exponential technologies like quantum computing, and a surge of diverse, young talent building local startups will define the next era of digital dominance.

**Keywords:** enterprise IT management, github copilot rollout, agentic AI productivity, SAFe agile framework, platform engineering ecosystem, data-driven engineering culture, process mining for developers, reverse mentoring for executives, european tech investment, automotive digital transformation, executive AI adoption, future of developer demand, AI assisted software engineering, CIO career transition, removing developer bottlenecks

## Chapters

1. **Transitioning from economics to a tech career path** (02:34) — Learning programming through data migrations builds a technical foundation without a traditional computer science degree.
1. **Establishing the first chief data officer role at SAP** (07:42) — Building a dedicated data department highlights the imperative of top-down data-driven decision making.
1. **Moving from a pure software company to automotive** (09:09) — Transitioning to physical products showcases the real-world impact of software embedded in daily life.
1. **Utilizing personal networks for executive career opportunities** (13:04) — Bypassing traditional application processes through industry networking can lead directly to executive leadership interviews.
1. **Governing enterprise IT as a global automotive CIO** (15:17) — Managing global enterprise IT encompasses workplace support, production software, and cybersecurity across multiple subsidiaries.
1. **Rolling out GitHub Copilot to thousands of developers** (17:34) — Testing new tools with pilot groups ensures successful adoption and encourages peer-based learning among technical teams.
1. **Implementing agile frameworks alongside legacy milestone product planning** (18:45) — Balancing agile methodologies with strict hardware launch dates requires persistent cultural evolution within traditional product organizations.
1. **Removing developer friction through continuous feedback and tooling** (20:59) — Utilizing process mining and regular surveys streamlines internal workflows to maximize programming creativity.
1. **Leveraging generative AI and agents for executive productivity** (22:54) — Adopting large language models to prepare for meetings and retrieve institutional knowledge frees up time for critical tasks.
1. **Prioritizing continuous tech learning through executive reverse mentoring** (24:33) — Dedicating formal weekly time with innovation experts enables leaders to build hands-on skills with new automation tools.
1. **Driving software demand through increased developer productivity tools** (30:18) — Lowering software delivery costs via productivity assistants expands the market necessity for highly skilled technical talent.
1. **Advancing autonomous driving capabilities with specialized software talent** (34:17) — Experiencing high-speed autonomous systems on closed tracks underscores the critical safety role of embedded software engineering.
1. **Accelerating European technology ecosystems with increased strategic investment** (35:37) — Shifting from a conservative mindset to active regional venture funding prevents technical talent from migrating abroad.
1. **Encouraging underrepresented talent to pursue software engineering roles** (39:35) — Studying informatics and embracing advanced technical challenges empowers new professionals to disrupt static industry norms.
1. **Rapid fire perspectives on modern technology and habits** (41:04) — Quick reflections on daily preferences reveal an enthusiasm for the upcoming industry disruption caused by quantum computing.

## Related Moments

- [Driving developer productivity with AI in automotive tech](https://www.wearedevelopers.com/videos/916-beyond-the-hype-real-world-ai-strategies-panel) (from "Beyond the Hype: Real-World AI Strategies Panel")
- [Driving organizational change through clear engineering mandates](https://www.wearedevelopers.com/videos/100238-how-building-with-ai-can-double-the-throughput-of-your-engineering-team) (from "How building with AI can double the throughput of your engineering team")
- [Strategic goals for the Cariad automated driving division](https://www.wearedevelopers.com/videos/1082-code-to-road-in-12-hours) (from "Code to Road in < 12 hours")
- [Transitioning from traditional software development to artificial intelligence consulting](https://www.wearedevelopers.com/videos/1825-the-software-engineer-2030-from-coder-to-ai-orchestrator-patrick-schnell) (from "The Software Engineer 2030: From Coder To AI Orchestrator? - Patrick Schnell")
- [Scaling AI adoption to non-traditional enterprise developers](https://www.wearedevelopers.com/videos/100256-can-this-elephant-dance-ibm-bob-and-the-future-of-ai-first-software-development) (from "Can This Elephant Dance? IBM Bob and the Future of AI-First Software Development")
- [The transforming role of developers in the AI era](https://www.wearedevelopers.com/videos/100337-user-1st-technology-2nd-stop-building-ai-nobody-uses-start-delivering-real-business-outcomes) (from "User 1st! Technology 2nd! Stop building AI nobody uses - start delivering real business outcomes")

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