Boston Children’s treats AI as infrastructure to cut costs, expand capacity and diagnose cases once thought impossible.

Boston Children’s Hospital did not pursue artificial intelligence simply to experiment with new technology. The hospital embedded AI across the organization as a core part of its clinical and operational infrastructure to improve how care is delivered to its pediatric patients, particularly those with complex and rare conditions. By integrating AI into daily workflows, the team has reduced operational costs, improved access to care, and helped diagnose more than 40 rare conditions that had previously gone unresolved.

Boston Children’s Hospital is one of the largest pediatric institutions in the world, serving patients across more than 40 specialties with close to 1 million outpatient visits each year.

Like many health systems, it operates under tight financial constraints while managing increasing administrative burden. Teams across supply chain, billing and operations handle high volumes of repetitive tasks, from processing invoices to coordinating schedules. These processes are necessary but time-intensive, pulling staff away from higher-value work.

At the same time, clinical teams face a different kind of limitation. Rare disease cases often involve fragmented genetic data, incomplete clinical histories and an overwhelming body of medical literature. Even in a leading research institution, physicians cannot synthesize all of that information fast enough to reach every diagnosis.

“The problem isn’t effort,” says John Brownstein, Chief Innovation Officer at Boston Children’s. “It’s human cognitive limits.”

Boston Children’s began with individual AI use cases, including documentation and translation tools. But those early efforts quickly exposed the limits of a fragmented approach.

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