AI rollouts that succeed do not look like big-bang launches. They look like a small pilot that becomes obviously useful, an expansion that holds up, and a hardening phase that makes the system boring. 90 days is the cadence most execs can stay engaged with.
Days 1-30 — pilot
- Pick one team, one use case, the smallest valuable agent.
- Daily standups with that team for the first two weeks.
- Weekly metrics: usage, time saved, failures, NPS from the team.
- Exec readout at day 30: ship the metrics, name what's working, name what's not.
Days 31-60 — expand
- Onboard 2-3 more teams that match the original pilot pattern.
- Move daily standups → weekly. Keep the metrics dashboard.
- First platform investment: whatever the pilot taught you was missing (usually eval infrastructure or shared tools).
- Exec readout at day 60: how the pattern is generalizing, where it's not.
Days 61-90 — harden
- Cost model is real. Cost per task is measured.
- Runbooks exist for the top failure modes.
- Governance doc has been written, ratified, and used at least once.
- Exec readout at day 90: state of the platform, proposed 12-month investment, ROI to date.
Knowledge check
0/1 answered1. Which of these is the highest-risk move in the 90-day rollout?
Discussion
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