# AI isn't the problem. Your workflows are. > Hospitals are racing to deploy AI, but the real challenge is redesigning how work actually gets done. - Title: AI isn't the problem. Your workflows are. · Newsweek - Summary: Hospitals are racing to deploy AI, but the real challenge is redesigning how work actually gets done. AI adoption in healthcare requires rethinking job… - Keywords: healthcare ai, artificial intelligence, hospital operations, workflow redesign, clinical decision support, primary care, sepsis detection, tampa general hospital, md anderson cancer center, jefferson health, electronic health records, operational change - Source: Newsweek — https://newsweek.com/health-care-ai-is-exposing-an-age-old-problem-how-work-gets-done-access-health-12451801 - Published: 2026-09-16T21:17:19+00:00 - Read time: 2 min - Topics: healthcare ai, artificial intelligence, hospital operations, workflow redesign, clinical decision support, primary care, sepsis detection, tampa general hospital, md anderson cancer center, jefferson health, electronic health records, operational change ## AI is already here in hospitals At least 71 percent of U.S. hospitals now use predictive AI in their electronic health records. The question is no longer whether AI belongs in healthcare, but how to make it work with existing processes. ## Someone still has to act on AI alerts When an algorithm detects a patient becoming septic, a clinician must decide what to do. AI can flag the problem, but humans remain responsible for the decision and the outcome. ## The gap between wanting and doing A 2026 Deloitte survey found that 100 percent of health systems say transformation is a priority, but they rate themselves just 2.7 out of 5 on their ability to actually execute it at scale. ## Tampa General's practical approach The hospital runs over 110 AI applications but hasn't cut jobs. Instead, it uses AI to help the same workforce do more work, starting with sepsis care where AI alerts clinicians to check patient records. > We're not deploying AI to reduce FTEs. AI is allowing us to do more work with the same amount of people. ## Results speak louder than speed Tampa General's sepsis mortality rate is 3 percent, well below the national average of 20 percent. The CEO credits the workforce for acting effectively on AI-provided information. ## Primary care has a people problem The U.S. doesn't have enough primary care doctors to serve all Americans. AI could help existing doctors manage conditions that once required specialists, but only if the tools reach those who need them. ## Access remains unsolved Even if AI helps primary care doctors do more, patients in healthcare's gaps, those without regular access to care, still won't benefit unless the tools reach them. > Could it get us the coverage determination, the budget, the contract, and put together the electronic medical record order sets? ## Clinical trials need workflow overhaul A trial requires coverage approval, budgets, contracts, and electronic medical record setup across different departments. What takes six months could shrink to 60 days if AI connects these fragmented steps. ## Research is moving closer to patients MD Anderson is using wearables and telemedicine to bring clinical trials to patients' homes and expanding studies across multiple sites, not just the cancer center. ## Cybersecurity threats are escalating Patient records affected by healthcare data breaches jumped from 6 million in 2010 to 170 million in 2024. Hacking accounted for 91 percent of those breaches last year. ## Security patches can't wait anymore Jefferson Health stopped bundling security patches for monthly installation windows. Now it applies critical patches the same day or immediately, because the old schedule moves too slowly. ## Old questions, new urgency AI is forcing healthcare to answer timeless management questions: Who does what? In what order? Who decides? What changes when the old way breaks? These aren't technology problems, they're organizational ones. > It's not really a technology story here. ## Key takeaway AI adoption in healthcare requires rethinking job descriptions, workflows, and organizational processes, not just installing new technology.