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
Find AI leverage in your org: the unusually productive people already doing more work. Use consumption and workflow signals to spot them.
Evaluating Spend
AI spend analysis for leaders: classify direct and indirect AI spend, find every billing source, and run the five-minute audit your CFO will accept.
Choosing Tools
How to choose AI tools when leverage sits in the top 5% 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 talent and spot workflow designers on your team. Interview questions and assessments that reveal disposition, judgment, and leverage.
Measuring Returns
Measure AI returns by team consumption, visible work change, and operating decisions instead of a vendor ROI multiplier.
Managing Risk
The five AI failure modes that actually hit enterprises, the dull controls that catch them, and which AI rules genuinely bind you in August 2026.
Recent Articles
All articles →Your AI Champions Need a Job Description
An AI champion program works when the role has one workflow, manager-backed time, and a result more useful than activated seats.
Claude Skills Need an Owner
Claude Skills can turn a proven workflow into shared team work. Use them with a named owner, a review point, and a result worth measuring.
How to Hire for AI Skills
How to hire for AI skills: screen for changed workflows, sound judgment, and work that improves after the candidate leaves the screen.
What Your Board Is Going to Ask About AI
Your board doesn't want an AI strategy. It wants four answers: a defensible number, named people, a one-page policy, and a plan for when AI breaks.
How Many AI Seats Should Your Company Buy?
How many AI seats to buy per employee, which flat plans deserve an audit, where metering belongs, and the benchmark your CFO will accept.
Should You Build Your Own AI?
Build vs. buy for enterprise AI comes down to one question: who absorbs the churn when the model gets deprecated? Here's the narrow case where building wins.