Executive Guides for AI
For directors and above. Opinionated. Updated.
The Executive's Mental Model for AI
AI isn't a transformation. It's five operational decisions you already know how to make. The frame that turns vendor pitches, board questions, and budget meetings into 30-second exercises.
Recognizing Leverage
AI leverage in your org looks like an unusually productive employee you didn't hire. Here's how to find the people already doing the work, and why you almost certainly can't name them yet.
Evaluating Spend
What an AI budget should look like when it's working. Seats vs. usage, plan tiers, shadow AI, and the five-minute audit your CFO will accept.
Choosing Tools
How to choose AI tools when leverage is concentrated in 15% of your users. The framework: who picks, what to fund, when to standardize, and Microsoft.
The One-Page AI Policy That Ships in Two Weeks
Most AI policies stall in committee while the workforce picks its own tools. One page. Approved tools, off-limits data, clear ownership. Done in two weeks.
Driving Adoption
Why half your AI seats are idle and what to do about it. Not a training program. The disposition gap, the workflow gap, and the manager signal.
Selecting Talent
How to hire AI-leveraged people and spot them on your team. The interview questions, signals, and assessments that surface disposition over credential.
Measuring Returns
How to measure AI program returns without an ROI framework. Seat-level decisions, workflow signals, and the one paragraph your CFO will accept.
Managing Risk
The four AI failure modes that actually hit enterprises: data leakage, wrong answers, over-reliance, shadow AI. And the operational controls that catch them.