About
I both work with AI and have studied how organizations adopt them. This combination gives me a solid foundation of understanding both the technology and the real world in which it is used.
I have designed and shipped AI tools in real business environments: automated classification pipelines, conversational AI systems, and automation workflows that connect language models to real business tasks. I've taken projects from ideation through deployment, working with tools such as Python, JavaScript, and n8n. Outside of professional work I build for myself, including a browser extension using the OpenAI API for real-time political bias analysis on web content as well as other personal applications and automations.
My MSc thesis at Aarhus BSS was a qualitative case study examining how generative AI exploration contributes to organizational learning in an SME. The research question: what does a company learn about its own conditions and limitations for AI adoption through hands-on use? I drew on organizational learning theory and IT strategy to answer it. The question wasn't "does AI create value," but under what conditions, for whom, and how you get there.
A BA in International Business Communication from Aarhus University, including an exchange semester at the University of Vermont in the USA, built my foundation in strategy, intercultural communication, and how technology travels across different organizational and cultural contexts.
What I do
Building
I design and ship AI solutions in production: classification pipelines, conversational tools, and automation workflows that connect language models to real business tasks. I work across Python, JavaScript, and n8n, and I take projects from the problem and ideation phases through deployment. The measure is always whether it works in practice, not just in theory.
Understanding
Through my MSc research and an extensive literature review of AI value creation, I've developed a grounded view of how AI actually gets adopted — where it delivers, where it stalls, and what holds people and organizations back. The limiting factor is rarely the technology. It's knowing where to start and what to do with it.
Translating
Most people working with AI today aren't engineers. They're professionals trying to figure out how to make it useful in their day-to-day work. I bridge that gap by turning technical capability into practical understanding, and making AI accessible to the people who actually need to use it.
Connect
I'm always up for conversations about AI - what's working, what isn't, and where it's all heading. If you're navigating it in your life, figuring out where to start or how to build real capability, or just want to exchange ideas, reach out below.