From Fragmented Tools to Enterprise Infrastructure

Boston Children’s Hospital moved away from isolated, one-off AI experiments to build a unified enterprise AI layer. This secure, internal environment integrates across research, clinical, and administrative departments, allowing for rapid deployment of new capabilities. By treating AI as core infrastructure rather than a collection of standalone tools, the hospital has enabled over one-third of its workforce to utilize AI in their daily operations, significantly reducing development cycles for new workflows.

Operational Efficiency and Labor Redeployment

The hospital prioritized high-volume, repetitive administrative tasks to achieve measurable financial impact. By implementing over 50 automations—ranging from supply chain invoice processing to AI-assisted surgical scheduling based on patient acuity—the institution has captured 60,000 hours of time savings. This efficiency has resulted in more than $7 million in redeployed labor, allowing staff to focus on higher-value clinical and research activities.

Clinical Discovery and the 'Co-Pilot Geneticist'

Beyond operations, the hospital developed a specialized 'co-pilot geneticist' system to address complex diagnostic challenges. This tool synthesizes fragmented genetic data, phenotypic information, and vast bodies of medical literature to assist physicians in identifying rare diseases. This approach has successfully diagnosed more than 40 conditions that were previously considered impossible to resolve, while simultaneously identifying new gene targets and therapeutic pathways for future research.