Healthcare AI faces critical infrastructure challenges

Healthcare systems are struggling to integrate AI tools due to outdated electronic health record (EHR) systems, which were not designed to handle the demands of modern AI. As AI adoption accelerates, the strain on legacy infrastructure is becoming a pressing issue. OpenAI is collaborating with Epic, the largest EHR provider in the U.S., while major insurers are integrating AI solutions. However, the underlying systems are not equipped to support real-time AI queries, risking slowdowns and potential failures. A 2026 survey found that 97% of U.S. database professionals use outdated software. Effie Carlson, CEO of Watershed Health, warns that the industry must address these risks before they lead to crises. Rebuilding data architecture is costly and complex, but necessary to ensure patient safety and system reliability. Leaders must audit their infrastructure, invest in upgrades, and commit to long-term modernization plans to support AI effectively. The intersection of aging systems, rising patient needs, and rapid AI adoption is creating a critical juncture. While AI offers significant benefits, such as improved efficiency and faster documentation, the risks of overloading outdated systems remain unaddressed. Without proactive measures, healthcare systems may face unexpected failures, highlighting the urgent need for infrastructure modernization to support the AI-driven future.