AI pilots have a remarkably consistent failure pattern: initial enthusiasm, 60 days of building, demo to leadership, then nothing. The pilot did not "fail" — it just never became operational. Here is why this happens and what to do.
Month 1-2: A small team builds something promising. Demo to leadership. Excitement.
Month 3: "Let us pilot it more broadly." Vague next steps. The team that built it moves to other work.
Month 4-6: Nothing happens. No production rollout. No measurement. No decision to kill or scale.
Month 7+: The pilot is referenced occasionally but never operational. Eventually forgotten.
1. No production owner. The team that built the pilot was not accountable for production deployment. Once they returned to their day jobs, no one owned the next phase.
2. No measurement framework. The pilot showed it COULD do the work. Nobody defined what success looked like for production. Without that, no one can decide to scale.
3. No integration with operational workflows. The pilot lived in a separate tool, separate from how the team actually worked. Integration was treated as "phase 2" and never funded.
1. Assign one named production owner. Single accountable person, with budget authority. Without this, no movement.
2. Define operational success in measurable terms. Not "improves productivity." Specific: "Tier 1 ticket deflection rate of 35% within 90 days, measured weekly."
3. Force the integration question first. "What workflow does this become part of?" Before building more pilots, integrate the existing one.
4. Kill pilots that cannot be integrated. A pilot that cannot become production is not a "we are still evaluating" — it is a no. Free the team to work on things that will deploy.