How AI actually lands inside companies.
Hands-on analysis at the intersection of delivery, organization and governance: substantive, current, citable. Four themes that decide whether AI makes it from pilot to production.
Articles
Return on AI: measuring the value of AI initiatives honestly
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.
Read more →The AI governance operating model: roles, bodies and evidence
Governance works when it is an operating model: clear roles, decision bodies and evidence, built into delivery. That way it enables fast, auditable AI.
Read more →The AI-ready organization: beyond the pilot
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.
Read more →EU AI Act readiness for the mid-market
What the EU AI Act requires from mid-market companies: deadlines, risk classes and a practical readiness checklist, also after the Digital Omnibus.
Read more →From automation to agentic AI: what changes for organizations
Rule-based automation follows fixed paths. Agentic AI plans, decides and adapts. The real leap is in control, operations and accountability.
Read more →EU AI Act: The deadline moved, the work didn't
The Digital Omnibus postponed the high-risk obligations. Why that's no reason to relax, and what the extra time is actually worth.
Read more →AI with the workforce: why co-determination speeds up adoption
Introducing AI is always a question of skills and participation too. Peer-reviewed research shows that works councils strengthen training exactly where automation hits hardest.
Read more →Digital transformation: setting the stage for impact
Impact comes from the interplay of technology, organization and people, carried by strategy, competence and culture.
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