AI Strategy··3 min read
How to Budget for AI When You Can't Predict Usage
Usage-based pricing makes AI budgets guesswork. Here is a structure that survives the guessing.
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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.
AI Strategy Articles
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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.
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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.
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AI Adoption Metrics That Aren't Vanity
Ninety percent of staff logged in. That number is worthless. Here are four that aren't.
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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.
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Why AI Pilots Stall Before They Reach Production
The pilot worked. It is still not in production eight months later. There are five usual reasons, and four are decided before the pilot begins.
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Nine AI Vendor Red Flags Worth Walking Away From
Some warning signs are worth a question. These nine are worth ending the conversation.
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Data Readiness for AI: What Actually Has to Be True
Most companies are told they need a data platform before they can use AI. For most use cases, four narrower conditions matter far more.
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Build vs Buy AI: A Decision Most Companies Get Backwards
The build-versus-buy question is not about capability or cost. It is about whether the thing is a differentiator, and most companies answer it backwards.
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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.