The AI Delivery Lab is where I make that work visible. I started it on my own — it is not client work. I build what I wish every transformation team had: clear briefs, testable requirements, risk controls, working software, and honest measurement.
The arc
I studied business administration and management at the University of St. Gallen. Product work taught me to connect a market need to execution: first in product and sales at Swarovski, then in international product initiatives and technology-enabled change at Migros Delica.
At Monitor Deloitte in Zurich, I worked as a Strategy Manager. I shaped strategic visions and value propositions, guided cross-functional teams across market approach, digital capabilities, and financial resilience, advised senior stakeholders, and drove continuous improvement.
Since March 2024, I have worked as an Independent Advisor on people-centered individual and organizational development. Since July 2024, I have also served as a volunteer advisor with SINGA Switzerland, assessing business ideas and helping entrepreneurs refine desirability, viability, and feasibility.
I was on parental leave in 2025–2026.
In August 2026, I started The AI Delivery Lab. The first build takes a life-insurance intake use case from first brief to a working, safeguarded demo, a pilot design, and a value plan — all on fictional data. I direct AI coding agents to build the system and document the decisions a delivery lead still has to own.
Change and adoption
Delivery works when the process and the people change together. My coaching training supports that part of the job: facilitation, listening, feedback, training, and difficult decisions with stakeholders.
I have completed 137+ training hours with BeCoach Academy and 200+ coaching practice hours toward ICF certification. Certification is in progress.
How I work
Start with the decision
I ask which user problem matters, what evidence would change the decision, and whether AI is necessary at all.
Make behavior testable
I write down what the system must do, how well, and what happens when it fails — before a demo becomes a promise.
Build in increments
I keep scope small enough to test. Each increment has an owner, a visible artifact, and a clear release decision.
Design adoption early
Pilot users, training, feedback, support, and benefits baselines enter the plan while the product is still being shaped.
Contact
If you are working on AI delivery, business transformation, or adoption in a regulated setting, write to me.