How AI Could Transform Health Care

AI could materially reshape health care by lowering costs and improving productivity across drug discovery, care delivery and health data analytics, with the strongest long-term positions likely belonging to companies combining AI with proprietary data or specialized expertise.

• U.S. health care spending was projected at $5.7 trillion, or 18.4% of GDP, in 2025, and is expected to approach $9 trillion by 2034, nearly 58% higher, creating pressure to improve efficiency.
• Administrative costs may represent nearly 25% of U.S. health care spending, while a National Bureau of Economic Research estimate suggests AI could reduce spending by 5% to 10% through workflow automation, better decision support and improved clinical operations.
• AI could accelerate drug discovery by improving target identification, molecule design, trial recruitment and regulatory work; Insilico Medicine reportedly used AI and automated experiments to design a protein in less than a month, compared with a process that may previously have taken years.
• Drug development still typically takes 10–15 years and costs more than $2 billion per viable medicine, and AI-generated candidates must still pass clinical trials, limiting how quickly discovery improvements can reach patients.
• In care services and analytics, UnitedHealth Group is highlighting potential reductions in administrative and medical-management costs, while OpenEvidence estimated that 40% of U.S. physicians used its research tool daily in 2025.

Takeaway: Investors should look beyond technology companies toward health care businesses with differentiated datasets, validated platforms and real-world applications, while recognizing that regulation, reimbursement, clinical validation, data quality and workflow integration remain important constraints.