AI in healthcare is growing fast but still hitting major snags.
A 2024 AMA survey shows 66% of U.S. doctors have used AI tools, up from 38% in 2023. Most of that use is for admin tasks, not for medical decisions or diagnoses. Only about 12% rely on AI for diagnostic help.
Hospitals are rolling out AI scribes that take notes during visits and chatbots handling scheduling and patient FAQs. But clinical AI tools remain mostly experimental or secondary aids. 
The issues? AI can make wrong calls due to “algorithmic drift” — systems mess up outside controlled labs. Racial and ethnic bias in training data leads to misdiagnoses, especially for underrepresented groups.
Data-sharing is a headache. AI needs massive patient info, but privacy laws like HIPAA and fears of leaks slow adoption. Plus, many AI systems work as “black boxes.” Doctors want clear reasoning, but AI vendors keep algorithms secret to protect IP.
“The lack of transparency feeds skepticism among practitioners, which then slows regulatory approval and erodes trust in AI outputs,” experts say.
“Many argue transparency is not just ethical but necessary for adoption.”
Expect AI healthcare to advance slowly. It promises to save billions and lives but won’t flip the industry overnight. Hospitals face time, budget, and training limits. AI still needs years of testing and tweaks before becoming routine.
The bottom line: AI is embedding into admin work now. Diagnosis and treatment AI will take longer due to technical, ethical, and trust hurdles. The promise is huge — but so are the challenges.
