Writing
Writing
Essays on AI leadership, private AI, and where the ROI is. Most of it comes from engagements I ran; the rest is sourced, and linked.
Leadership & Operating Model Inside the Monthly AI Executive Report: what an AI executive owes you in writing
What a fractional Chief AI Officer owes you in writing every month — section by section, with a full sample report you can read.-
Buying Judgment Who watches the builders? What implementation oversight actually looks like
The quiet failure mode of AI implementations isn't bad code. It's unsupervised scope. Here's what a month of real oversight looks like, no's included. -
Buying Judgment How to evaluate AI vendors when every deck looks the same
Every enterprise AI pitch says the same things, so capability claims can't differentiate. Gates before scores, your workflows over the demo, price last. -
Workflows & ROI How I decide which AI initiatives to kill
Most AI portfolios die of politeness. The quarterly fund/hold/kill memo: every initiative names its P&L line, shows spent vs. returned, gets a verdict. -
Leadership & Operating Model Why AI training fails, and what a champions program does instead
The standard rollout produces a spike, then a slide back to the same 15% of enthusiasts. Here's the program that replaces it, and the numbers to watch. -
Workflows & ROI What a 90-day AI roadmap looks like for a professional services firm
The actual plan an AI Executive Assessment produces — days 0–14, 15–45, and 46–90 — including what I deliberately leave out. -
Workflows & ROI How to build an AI opportunity backlog
The scoring method I use to turn a wall of AI ideas into three to five workflows worth building — and a public list of everything I killed. -
Workflows & ROI Why internal knowledge assistants fail on messy company data
The model is almost never the problem. After three years shipping retrieval systems, these are the corpus failures that kill knowledge assistants. -
Leadership & Operating Model The CEO's guide to AI governance without bureaucracy
At 50–500 people, AI governance is a handful of owned decisions, not a committee. Done right, it speeds adoption instead of slowing it. -
Private & Secure AI When private AI makes sense — and when it doesn't
Private AI is an architecture decision, not an ideology. The honest criteria I use to tell clients when to build it — and when to skip it. -
Leadership & Operating Model Why AI adoption is an operating model, not a tool rollout
Most AI pilots stall because no one owns the decisions behind them: data rules, approved tools, workflow priority, and how ROI gets measured.