AI Strategy··4 min read
How to Prioritize AI Use Cases Without Guessing
Twelve ideas, budget for three. Here is a defensible way to choose, and the reason the best-scoring one is often not where you should begin.
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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··5 min read
AI Audit: How to Evaluate Your Company's AI Before It Costs You
Most companies adopted AI faster than they inspected it. An AI audit answers five questions — what's in use, what data it touches, what it costs, whether output is checked, and who's accountable. Here's the working framework.
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The AI Maturity Model: 5 Levels and How to Climb Them
Enterprise AI maturity models are built for companies with committees. This one is built for operators: five levels, honest placement criteria, and the specific work that moves a growing business up each rung.
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AI Transformation: The Executive Playbook (Without the Consulting Theater)
"AI transformation" has become a phrase that means everything and therefore nothing. Here's what it actually is, why the big-bang version fails, and the executive playbook that works for companies without transformation offices.
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How to Evaluate AI Vendors Without Getting Burned
Most AI tools demo beautifully and break in production. After evaluating vendors across 100+ implementations, here's the framework I use — including the five questions that end most sales conversations early.
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AI for Operations: Automating the Back Office
The back office isn't glamorous, which is exactly why it's where AI pays back fastest. Repetitive, high-volume, rule-based operational work is AI's sweet spot. Here's where to apply it, what to automate first, and what to leave to people.
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How to Measure AI ROI (Without Fooling Yourself)
Most companies spending money on AI can't say whether it paid off — and the ones who claim it did are often counting vanity metrics. Here's an honest framework for measuring AI ROI, including the traps that make bad investments look good.
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AI for Professional Services Firms: A Practical Guide
Professional services firms sell expertise and time — which makes AI both a huge opportunity and a genuine risk. Here's where AI creates real leverage for consultancies, agencies, and firms, and where it quietly undermines the trust you sell.
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The AI Readiness Assessment: Is Your Business Ready?
Most companies buy AI tools before they're ready to use them — which is why the tools become shelfware. Here's an honest readiness assessment across five dimensions, including the signs you should fix something else first.
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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.