Reducing the number of required AI queries for employees actually led to a 7% increase in total sales.
Lowering mandated AI usage targets from 200 to 100 per month stopped workers from gaming the system to meet quotas. When employees were forced to use AI more often, the quality of their work degraded and financial returns dropped. Managers frequently assume that more technology usage always translates to higher productivity and better results. This experiment proves that forced adoption creates a bottleneck that prevents humans from using their own judgment effectively. Allowing workers to use AI selectively produces better outcomes than forcing them to use it for every task.
When Less Is More: Managing AI Adoption with Usage Targets
SSRN · 6709842
Usage mandates can accelerate AI adoption, but they also risk turning adoption into a metric to be gamed. We study a medical-device company that required roughly 5,000 employees to submit 200 AI queries per month, then reduced the target to 100 through a staggered branch rollout. Complete query logs show that the mandate increased first-time adoption, but 32% of queries are either repeated or non-work queries under the 200-query target. Lowering the target reduced query volume by 30%, improved q