A new report finds that while more than 90% of health systems have deployed third-party AI tools, fewer than half have the infrastructure to test and validate those systems before they are embedded into patient care. The finding highlights a governance gap between rapid procurement of AI products and the slower build-out of evaluation workflows. As hospitals scale model usage across radiology, triage, and administrative pathways, the report implies that current oversight may not sufficiently measure performance drift, subgroup accuracy, and clinical workflow integration. For biotech and digital health stakeholders, this creates both a risk-management requirement and a market opportunity: vendors that can provide auditable validation frameworks may gain faster adoption and fewer procurement delays.