Consultant, lecturer and researcher in AI transformation. I lead AI transformations for DAX40 and mid-market companies, technically, organizationally and strategically, and share that in talks, teaching and research.
AI transformation means taking artificial intelligence from isolated pilots into reliable production, technically, organizationally and strategically at once, especially in regulated industries such as financial services and insurance. Whether AI succeeds usually comes down to the gap between model, organization and strategy. That is where I work: as a consultant, lecturer and researcher who connects hands-on delivery with the boardroom view. I do this work in my main role with a leading international consultancy.
GenAI solutions, AI agents, knowledge management and copilots: from spotting use cases through their short- and long-term prioritization into production, together with data engineering, MLOps and cloud platforms (Azure, AWS).
Target operating models, change and enablement programs, and governance that enables delivery, so technology lands in processes and teams and does not stall in pilots.
AI strategy and roadmap for the leadership level: prioritizing use cases by impact, steering investment and translating AI into measurable business value, grounded in years of experience and peer-reviewed research.
Peer-reviewed research in leading journals, complemented by articles for corporate practice. The basis for any serious claim about AI and how it lands inside organizations.
Modules for Master’s students and working professionals: hands-on AI combined with data governance and MLOps. The aim: enable future managers to translate AI capabilities into business decisions.
Keynotes, panels and workshops on AI and Data Science (Deep Learning and Machine Learning), for conferences, chambers of commerce and universities.
How predictive forecasting transformed planning at HRS Group
What it takes to move AI agents from demo to productive use
I am a PhD economist (TU Dortmund) and have worked at the intersection of Data Science, artificial intelligence and organization for more than twelve years. In my main role with a leading international consultancy, I lead AI transformations for DAX40 and mid-market clients, from strategy through GenAI and agentic AI solutions into production. In that role I advise boards and leadership teams on AI strategy, governance and investment decisions.
What holds my work together is the bridge between three worlds: the technical implementation of AI, the organizational change, and an understanding of AI governance and strategy. My research, in Oxford Bulletin of Economics and Statistics, Zeitschrift für Corporate Governance and British Journal of Industrial Relations, examines, among other things, exactly this intersection of technology, work and organization.
As a lecturer I teach MLOps and Data Engineering at the FOM University of Applied Sciences and co-organize the Ruhr AI Strategy Evening.
Current analysis at the intersection of delivery, organization and governance.
The return is rarely decided by the model. It is decided by whether you account for the full value and the full cost honestly, across a portfolio and a realistic time horizon.
Governance works when it is an operating model: clear roles, decision bodies and evidence, built into delivery. That way it enables fast, auditable AI.
The leap from pilot to standard operation is an organizational question: roles, skills and an operating model that carries AI in daily work, long before a better model counts.
For questions on teaching, speaking, research collaborations, or simply to discuss AI in organizations.
