Insights
Articles and analysis on the topics that matter most for complex transformations and governance-compliant AI integration.
Why AI Projects Fail — and How a Structured Operating Model Prevents It
More than 40 percent of all AI projects never reach production. The reason is rarely the technology. It lies in the absence of an operating model. This article presents a framework of eight building blocks that makes AI systems manageable, accountable, and scalable.
The MOTIVE Framework as a Leadership Model for Controllable AI Use
Prompt engineering has been commoditised. What organisations need is a leadership discipline: the ability to define which tasks AI should perform, what a good result looks like — and who is accountable for it. The MOTIVE Framework provides the structure.
How Autonomous AI Agents Change Capabilities, Processes and Operating Models — and Why Enterprise Architecture Must Be the Governance Authority
Agentic AI does not merely affect technology stacks — it intervenes deeply in Business Architecture, IS Architecture and infrastructure. This whitepaper shows which tensions arise, why classical EA governance is insufficient, and what governance architecture is needed for controllable Agentic AI operating models.