AI leadership
summaries.
Leadership guides for AI decisions: spend, tools, talent, policy, risk. Opinionated, regularly updated, written for directors and above. Written by someone who builds these systems.
Guides
All guides →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
Five AI failure modes that hit enterprises: data leakage, wrong answers, over-reliance, shadow AI, ungoverned automation, and the controls that catch them.
Recent Articles
All articles →The State of AI: Q3 2026
Quarterly briefing for leaders. What changed this quarter, why your AI bill became a usage meter, the agents IT didn't approve, and what to tell your board.
Stop Running AI Pilots
Most enterprise AI pilots never reach production, and the format is the reason. A pilot produces a demo, not a P&L owner. Run a production cut instead.
Shadow AI Is a Signal, Not a Threat
Every shadow AI incident is preceded by a procurement gap your company didn't close. Your people aren't being reckless. They're doing their jobs with the only tool that works.
AI Marketing Assistants: Analysis, Not Copy
Most marketing teams start with AI copywriting and stall there. The workflows that actually compress are analytical: monitoring, reporting, spec-based content.
Proactive AI Agents: Removing the Human Trigger
AI tools are reactive by design — a human opens, prompts, closes. Total leverage is bounded by how often that happens. Event-driven agents remove the human.
ChatGPT vs. Claude vs. Gemini: What to Actually Buy
The comparison is the wrong question. The right answer is three tiers, not one vendor. Here's what to buy for whom.