AI Governance··3 min read
What to Do When Your AI Gets It Badly Wrong
Every AI system will produce a bad output eventually. The difference between an incident and a crisis is whether anyone decided in advance.
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The JournalEssays & Field Notes
Practical writing on AI in the wild.
Field notes from real engagements. Frameworks, postmortems, and the unglamorous discipline of shipping AI in production.
Sep 2026
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AI Strategy··3 min read
AI Data Quality: How Clean Is Clean Enough?
Perfect data is not the standard, and waiting for it is how companies spend a year preparing and ship nothing.
Read essayAI Strategy··3 min read
How to Kill an AI Project Without Killing the Programme
Every AI portfolio needs a way to end things. Most companies have no mechanism, so nothing ever stops and everything accumulates.
Read essayAI Leadership··3 min read
Chief AI Officer vs Head of AI: Which Title Fits?
One owns the portfolio and answers to the CEO. The other owns delivery inside a function. Getting this wrong is expensive.
Read essayAI Strategy··3 min read
AI Adoption Metrics That Aren't Vanity
Ninety percent of staff logged in. That number is worthless. Here are four that aren't.
Read essayFractional Leadership··3 min read
Fractional vs Interim Executive: Not the Same Hire
One is a permanent part-time seat. The other is a full-time bridge. Hiring the wrong one wastes a quarter.
Read essayAI Governance··3 min read
The One-Page AI Risk Register Worth Keeping
Enterprise risk registers are theatre for a 60-person company. Here is the version that actually gets used.
Read essayAI Strategy··3 min read
The AI Costs Nobody Puts in the Business Case
The licence fee is the number everyone quotes and the smallest one that matters. Here are the seven lines that decide whether it pays.
Read essayAI Leadership··3 min read
How to Become a Chief AI Officer (Without a PhD)
Almost nobody in this role arrived from AI research. Here are the four routes people actually take, and what gets tested on the way.
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Common questions
- What does this blog cover?
- AI strategy and leadership decisions for growing businesses: what a Chief AI Officer actually does, how to evaluate vendors, how to measure return, and why most AI projects fail. It is written for people deciding what to fund, not for people building models.
- How often is it updated?
- New pieces publish regularly, and existing ones are revised when the underlying facts change — pricing, market rates and vendor landscapes move quickly enough that stale posts become misleading rather than merely dated.
- Who writes it?
- Erin Moore, a fractional Chief AI Officer and U.S. Army veteran with an Executive MBA, an MS in Data Science and a Lean Six Sigma Black Belt. Everything is written from the buyer's side of the table, which is where the work happens.
- Where should I start?
- If you are new to the topic, start with what a fractional Chief AI Officer does and why most AI projects fail. If you are already spending on AI, the posts on AI audits and measuring ROI will be more immediately useful.