A new Genpact and HFS Research report identifies four “enterprise debts” that trap the value of health-care AI investments, estimating nearly $18 trillion in recoverable value across Global 2000 firms. The researchers argue the core barrier for payers and providers is not AI capability but legacy operating models and workflows that prevent scaling, turning promising pilots into stalled projects.
The report groups the debts into technical, data, process and governance categories — legacy systems and fragmented EHRs, poor data quality and integration, manual or misaligned workflows, and organizational/talent and compliance gaps. These obligations erode return on AI, extend deployment timelines and increase risk. Health systems must prioritize modernization, data standardization, governance frameworks, workforce reskilling and strategic vendor partnerships to unlock clinical and administrative AI benefits at scale.
