An AI strategy reviewed once a year is a strategy that drifts. The review cadence — monthly, quarterly, annual — is what keeps the strategy tied to outcomes instead of frozen on a slide.
AI strategy isn't a document; it's a managed portfolio. Portfolios that aren't reviewed don't drift toward the goal — they drift toward whoever has the loudest opinion. A cadence is the structure that prevents that.
Process Measurement: The Monthly
The monthly review measures: did the AI work move the metrics the strategy claimed it would? If not, the work didn't ship — regardless of what was deployed. This is the review that catches the demo-versus-production gap before it costs a quarter.
- Did the metric move?
- Did the ship happen on the date?
- Is the owner still the owner?
The Quarterly: Portfolio
The quarterly review manages the portfolio: fund, watch, kill. This is where the strategy actually changes — initiatives are killed, new ones started, and the strategy stays a portfolio, not a wish list.
- Fund the ones with outcomes and owners.
- Watch the promising but unproven, with a deadline.
- Kill the ones without outcomes or past their deadline.
Sharpen the Saw: The Annual
The annual review is the rare chance to question the strategy itself — the thesis, the risk frame, the capabilities. Most teams skip it because the monthly and quarterly absorb all the time. Don't skip it — it's where the strategy gets renewed or replaced.
The Anti-Cadence: The Status Review
The status review reports without deciding. Replace it with reviews that end in decisions — keep, fix, kill — at each cadence. The cadence exists to produce decisions, not updates.
Conclusion
The AI strategy review cadence is monthly measurement, quarterly portfolio, annual thesis. Each ends in a decision, and that's what keeps the strategy tied to outcomes instead of frozen on a slide.
About FACTA
FACTA helps startups and growth-stage teams turn AI into production systems that keep running — not demos that impress once.
We design the architecture around the parts that actually break under real usage: tooling you own, credentials you control, failover, cost controls, observability. The boring infrastructure that keeps a system alive after launch.
Led by Matías Baglieri and Carolina Fogliato, we focus on one thing:
AI leadership that builds. Not just advises.
Ask us what your AI strategy review cadence is missing.
We'll tell you which decision your reviews aren't producing. See AI portfolio prioritization for the quarterly mechanic.
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