The pattern: enthusiasm at week one, silence at week eight
A typical AI pilot looks great in week one. The team is excited, the metrics are tracked, the vendor is attentive. By week six, attention has slipped. By week eight, half the team has stopped using it. By week twelve, the pilot quietly dies.
This isn't a technology problem. The software still works. No one is maintaining the human side: the habits, the workflows, the small daily reminders that keep the tool useful.
Why month two is the cliff
Week one runs on novelty. People try the new thing because it's new.
By week two, the routine of the work has started to compete. The QS has a deadline. The bid manager has fifteen tenders to clear. The commercial team is fielding calls across live sites. The new AI workflow needs deliberate attention to survive that.
Without someone watching adoption, removing friction, refining the workflow, the AI slides off the priority list. The team isn't sabotaging it. They're running their week.
What changes between week one and week eight
The friction shows up. Edge cases the demo didn't cover. A QS who finds the output isn't quite right for one particular client. A coordinator who finds the customer-escalation pattern misses certain calls.
No single piece of friction is fatal. Together they're an exit ramp.
The fix is small adjustments: refining the prompts, adjusting the workflow, training the team on the edge cases. None of that happens by itself.
How to budget for embedding, not just building
The mistake is treating AI as a build-and-hand-over project. The reality is build, go live, then a 90-day embedding period where the system gets refined to the way your business actually runs.
That embedding work has a cost: usually 30–40% of the build cost again, spread across the first three months. Companies that budget for it have AI systems still in use at month twelve. Companies that don't have a quiet failure.
An honest AI engagement is "build it, then stay close enough to make sure it sticks."