Hospitals are increasingly turning to agentic AI to automate workflows and reduce staff burden. But according to a recent MedCity News analysis, the common strategy of launching multiple pilots at once often backfires. Organizations quickly descend into what the article calls "pilot sprawl," where they can no longer even identify which agents remain in active use.
The problem is not the technology itself but how it is deployed. When hospitals try to automate as many tasks as possible simultaneously, oversight breaks down and the intended time savings are lost. The analysis suggests that agentic AI works best when stripped down to a narrower set of well-defined functions, allowing staff to actually track and benefit from the automation.
Rather than treating AI as a broad tool for every process, the piece implies that hospitals should start small, evaluate what works, and scale only those agents that prove their value. This runs counter to the enthusiasm for wide-scale experimentation, but the evidence of sprawl suggests a more disciplined path is needed.