Writing for leaders of $50 million to $500 million businesses: the evidence on why AI spend returns nothing, the five pressure points where changing how the work runs pays most, and the honest answers to the questions boards actually ask. Every post stands alone; together they are the argument of The 2026 AI Strategy.
The pillar: why most AI spend returns nothing, the five places the return hides, the survival math, and the 90-day sequence.
The most quoted failure rate in business has a legible cause and five fixable disciplines.
A four-step working session that prices the human hours your business spends operating software instead of serving customers.
When the growth plan needs hours the labor market will not sell you, the capacity is already on your payroll.
Enterprise-grade retention just became affordable at mid-market scale, and it is the highest-margin growth available.
Two-thirds of leaders distrust their own data. The mess is not the excuse; it is the starting point that pays first.
The judgment that took decades to build is exactly what AI-native challengers encode and sell cheaper. The move that answers it.
Confidence-weighted value over AI cost, quarterly, with a stop rule. The metric that keeps a program funded.
Two levers, both real: cost named honestly, redeployment named role by role. No euphemism.
Predictable questions reward preparation. All twelve, with what they are really asking and how to answer.
Four chapters of The 2026 AI Strategy live on this site with no gate: The 2026 AI Paradox, the frameworks, The Software Tax, and The Maturity Path.