Where research accountability meets business constraints
Molwin holds a foot in both worlds — peer-reviewed findings and the operating realities of small and mid-sized businesses — and builds consulting from that structural position.
From doctoral inquiry to applied practice
Molwin's doctoral research examines how AI adoption affects operations and decision-making inside small and medium businesses — the constraints that large-enterprise case studies routinely ignore. That specificity is the foundation, not the credential.
The consulting practice grows directly from that research: each engagement identifies where evidence-backed AI use reduces real cost or improves customer-facing outcomes, and where adoption would impose organizational strain that outweighs the gain.
Teaching and writing complete the loop — translating findings into accessible frameworks for practitioners who don't have time to read the journal version.
Evidence built from the ground up
Peer-reviewed work focuses on AI integration barriers in SMB contexts — budget ceilings, limited IT capacity, and the organizational readiness gap that most AI frameworks skip.
Accountable to the room, not just the page
Classroom teaching and conference presentations require the same standard: claims need to hold under direct questioning. Molwin teaches AI strategy at the graduate level and speaks at research and industry events where both audiences show up.