Unfiltered perspectives on technology and AI investment decisions, commitment failures, and the analytical discipline that separates high-conviction capital from expensive mistakes. Written from 25 years of operating accountability — not commentary from the sidelines.
"The majority of AI investment losses were not technology failures. The technology worked exactly as specified. The failure was in the commitment decision that preceded it."
"Standard due diligence asks whether the technology can work. Decision intelligence asks whether this organisation, at this stage, with this leadership, can actually make it work. Those are different questions."
"The decision to commit is the point of maximum analytical leverage. Once capital is deployed and execution has started, the questions become harder and the options become fewer."
Three pieces on why AI and technology investment failures are commitment failures — and what validated decision intelligence looks like before capital is deployed. All claims verified against primary research.
BCG found 74% of companies failing to generate value from AI. McKinsey: only 6% of enterprises qualify as high performers. RAND: AI fails at double the rate of conventional IT. The industry blames execution. The failure is in the commitment decision that preceded it.
$30 billion in 2024 AI pilots. 95% delivered zero measurable return. 42% of organisations abandoned most AI initiatives in 2025 — up from 17% the prior year. The PoC cannot answer the question that determines whether the investment will succeed.
Standard DD evaluates whether the technology works. RAND found AI fails at twice the rate of conventional IT — despite adequate technical capability. The failure is upstream of the technology. Here are the five questions that find it before capital is committed.
Operational perspectives from 25 years of leading transformation, managing risk, and driving commercial growth across 50+ countries.
After leading change across 50+ countries, the pattern is consistent: the organisations that succeed treat transformation as a commitment architecture challenge, not a project management one.
The failure almost always traces back to the original commitment decision — and to the leadership team that made it without the analytical architecture to hold it under pressure.
Operating in seven languages across 50+ countries changes what risk signals you can read, which markets are accessible, and how deeply commitment actually lands. Language is decision infrastructure.
Evidence-based documentation of the Commitment Intelligence Method™ and its analytical foundations — published to advance the quality of decision-making in technology and AI investment environments.
The theoretical and practical foundation behind the Commitment Intelligence Method™ — covering the three analytical lenses, their application to technology and AI investment decisions, and the analytical process by which commitment positions are built and defended.
Open to academic collaboration, joint research initiatives, and practitioner partnerships in the areas of decision quality, technology investment outcomes, and AI adoption failure patterns. Particularly interested in longitudinal studies on commitment decisions and capital deployment outcomes.