The Speed Trap

The speed trap is what happens when organizational enthusiasm for AI adoption produces a rollout pace that exceeds the support infrastructure's capacity. The rollout moves fast. The early experiences are poor — not because the tool is poor, but because the training was thin, the champions were unprepared, and the help desk was overwhelmed. The early users — who will be the colleagues that the next wave of users consult before adopting — had bad experiences. Now the rollout has resistant veterans actively discouraging adoption instead of passive bystanders waiting to be convinced. The fastest rollout is not the most successful rollout. What "fast" means is context-dependent.

1. Define the Sustainable Pace The sustainable rollout pace is determined by: champion-to-user ratio (1:10-15), training capacity (how many people can be trained to the minimum effective threshold per week), and support infrastructure capacity (how many users can be onboarded before the help desk or champion network is overwhelmed). Calculate each constraint. The binding constraint sets the maximum sustainable pace.
2. Monitor Early Experience Quality Instrument the first two weeks of adoption for each rollout cohort: support ticket volume, user satisfaction, champion engagement requests. A cohort that generates twice the expected support volume is an early warning of insufficient preparation. Address the preparation gap before rolling out the next cohort.
3. Give Early Experiences Disproportionate Attention The early adopters in each rollout cohort will become the informal reference network for the next cohort. Their experience — positive or negative — will be transmitted through peer conversation before the next cohort's training begins. Invest disproportionately in the quality of early adoption experiences, because they multiply.