There's a particular kind of AI project that everyone is excited about for six weeks and nobody mentions again after three months. It worked in the demo. It impressed the room. And then it quietly disappeared, never making it into the daily work of a single team.

These pilots don't fail because the technology is weak. They fail because they were designed to be demonstrated, not deployed.

Pick a number before you build

The first question isn't "what can AI do here?" It's "what number should move, and by how much?" Hours saved per week, tickets resolved without a human, percentage of leads qualified automatically. A pilot tied to a specific, measurable business number has a reason to exist after the excitement fades. A pilot tied to "exploring AI" has nowhere to land.

If you can't name the metric, you're not scoping a pilot. You're funding a science project.

Narrow is a feature

The instinct is to make the pilot broad so it proves the whole vision. That's exactly what kills it. A narrow pilot, one workflow, one team, one clear outcome, is faster to build, easier to measure, and far more likely to actually run. You can always expand something that works. You can't rescue something that tried to do everything and did none of it well.

Plan the handover on day one

The quiet death usually happens at handover. The build is finished, the people who made it move on, and nobody on the inside knows how to run it or fix it. Documentation, a short training session, and a clear owner aren't afterthoughts. They're the difference between a tool your team uses and a tool that breaks the first time something changes.

A good pilot is small, measured, and built to be handed over from the start. It doesn't try to impress. It tries to survive contact with real work, because that's the only test that matters.