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.
Read essayVol. VII — WritingSubscribe via RSS
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.
FAQ
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.