AI Operating Systems

AI rarely creates enterprise value through a model alone. It needs an operating system around it: clear business priorities, capable teams, engineering foundations, governance, change management, and evidence that the resulting solutions work.

I write about the mechanics of making that system work inside established organizations. The publication covers AI operating models, product management, engineering, adoption, governance, and the difficult path from a promising use case to a valuable solution in production.

The articles are practitioner arguments grounded in hands-on work, research, and experience. Expect practical frameworks and strong opinions, with attention to the trade-offs that appear when AI meets organizational complexity, engineering constraints, and regulation.

About me

I lead AI Scaling and Strategy for Swedbank Baltic Banking, where I help shape the AI operating model and turn business needs into valuable, compliant solutions.

My work sits between business priorities, product development, engineering realities, change management, governance, and regulation. I combine strategy with hands-on execution, including work with a small federated development team.

I have spent more than 20 years in banking. My experience spans finance and financial steering, credit risk, digital transformation, innovation, and AI product development. That progression shapes how I think about AI: as an operating and value-creation challenge, not only a technology deployment.

I am especially interested in systems thinking, operating models, decision frameworks, and the mechanics that help enterprises use AI responsibly and effectively.

This is a personal publication. Views expressed here are my own.