DAU is up. Session length is up. Engagement is up. Your AI feature is a success, right?
Maybe. Or maybe your users are spending more time in the product because they're fixing AI mistakes. Maybe engagement is up because people keep clicking "regenerate" hoping for a better result. Maybe DAU is up because the curious tried it, but retention is about to crater.
Traditional product metrics don't capture what matters for AI. You need a different measurement stack.
TRADITIONAL METRICS AI-SPECIFIC METRICS
(still useful but (the ones that actually
not sufficient) tell you if AI is working)
──────────────── ──────────────────────
DAU / MAU AI feature adoption rate
Session length Time to complete task (with vs without AI)
Engagement AI output acceptance rate
Retention AI output edit distance
NPS AI-attributed error rate
Conversion AI confidence distribution
Revenue Cost per AI interaction