A survey by the Pew Research Center in December 2022 asked 11,004 adults in the U.S. about AI used in healthcare. The answers were mixed. About 60% said they would feel uncomfortable if their doctor used AI to diagnose diseases or recommend treatments. Only 39% said they would feel comfortable.
People had different views about AI depending on what it was used for. For example, 65% were willing to use AI for skin cancer screening. They trusted it to find skin problems quickly and accurately. AI can look at many images fast and may help find cancer early, which is important.
On the other hand, only 40% wanted AI to help with robotic surgery. Even fewer—about 31%—liked the idea of AI managing pain after surgery.
Many who were unsure about surgery robots and pain management worried about how reliable AI is, missing the human part of care, and possible mistakes. AI chatbots for mental health were the least accepted. Around 79% did not want to use AI chatbots and preferred traditional therapy.
These numbers show that while some people trust AI, many still worry about fully automated medical decisions, especially when human care seems important.
The Pew Research Center also found that 57% of Americans think AI in diagnosis and treatment would make relationships with doctors worse. Only 13% thought AI would improve these relationships. Many worry that too much technology can reduce empathy and communication with patients.
For healthcare managers and IT staff, this means AI should support doctors, not replace their care. AI should help doctors spend more time and have better information to connect with patients.
Keeping patient data safe is a big concern. About 37% of people fear AI might make it easier for hackers to access health records. They worry about data being shared without permission or used wrongly. Only 22% think AI might improve security by better monitoring and encryption.
Healthcare organizations need strong cybersecurity and must follow HIPAA rules. They should also clearly explain to patients how their data is used and protected.
Among people who see bias in healthcare, 51% think AI could help reduce racial and ethnic unfairness. But 15% believe AI might make these problems worse. AI can give fairer care if it is trained with good data and closely watched.
If bias is not handled well, trust from minority groups may go down, and unfair treatment may increase. Responsible use of AI means testing it carefully and keeping an eye on its performance.
Skin cancer is the most common cancer in the U.S. This makes screening very important. Patients seem to accept AI in this area; 65% support its use, and 55% think AI makes diagnoses more accurate.
AI tools in dermatology use pattern recognition and machine learning to study photos of skin spots. They help find signs of cancer faster and more reliably than usual methods. These tools can lower the workload for doctors and help focus on patients who need urgent care. They may also reduce missed cancer cases.
Hospital leaders can use AI to improve how clinics run and see more patients. Still, it is important to teach patients about AI and explain the final diagnosis will always come from a doctor.
Robotic surgery with AI helps surgeons by making their movements more precise and showing better views inside the body. About 40% of Americans are okay with having AI-assisted surgery, but 59% are unsure or against it.
For example, AI systems like Johnson & Johnson’s CARTO™ 3 help doctors make detailed 3D maps of the heart. This helps patients with heart surgery. Another system, VirtuGuide™, cuts down surgery prep time for complex bone fixes from weeks to days.
Healthcare leaders must think about costs, training, and patient comfort when buying AI surgical robots. Educating patients and letting doctors practice with the tools can help increase trust. It is also important to explain clearly that surgeons stay in control, and AI only assists them.
AI use for managing pain after surgery is the least popular. Only about 31% of people support it. Pain is a personal feeling linked to emotions, which makes it harder for AI to handle alone.
AI can be used to predict which patients might have strong pain or develop opioid problems. It can also help set up personalized pain medicine plans. While these tools can reduce mistakes and help treatment, most patients want human judgment and support during pain management.
Healthcare providers should combine AI with human care, where AI helps doctors but does not replace face-to-face support.
Besides patient views and ethics, AI helps automate clinic tasks. This saves time, cuts mistakes, and uses resources better. AI can answer phones, schedule appointments, and manage patient data. This is useful for healthcare managers.
For example, Simbo AI uses AI to answer calls automatically. This cuts down staff work, reduces wait times, and improves scheduling.
Using AI automation is important in busy clinics where staff may be stretched thin. IT managers and clinic owners can benefit from AI systems that keep data safe and let patients get care faster.
AI tools also help keep medical records accurate and help doctors with decisions, working alongside surgical robots and diagnostic AI.
Trust is still a big challenge for AI in U.S. healthcare. Men, younger people, and those with more education tend to accept AI more, but even they can feel uneasy. Knowing more about AI usually means people trust it more. This shows the need for education about what AI can and cannot do.
Healthcare managers should focus on being clear and open with patients. They need to train staff well so AI is used properly and fairly. Patients need to know AI helps doctors, not replaces them.
Clinic IT managers must make sure AI follows data security rules, protects privacy, and works reliably. This helps keep patient trust in AI-supported care.
AI tools in skin cancer screening, robotic surgery, and pain management have promise but face mixed patient acceptance and ethical questions. Healthcare leaders in the U.S. should focus on careful use of AI, clear communication with patients, keeping data safe, and showing that AI supports human care instead of replacing it.
AI automation in front-office tasks, like phone answering, also helps clinics run better. This makes healthcare more available, quicker, and smoother for patients and staff alike.
60% of U.S. adults report feeling uncomfortable if their healthcare provider used AI for diagnosis and treatment recommendations, while 39% said they would be comfortable.
Only 38% believe AI would improve health outcomes by diagnosing diseases and recommending treatments, 33% think it would worsen outcomes, and 27% see little to no difference.
40% of Americans think AI use in healthcare would reduce mistakes made by providers, whereas 27% believe it would increase mistakes, and 31% expect no significant change.
Among those who recognize racial and ethnic bias as an issue, 51% believe AI would help reduce this bias, 15% think it would worsen it, and about one-third expect no change.
A majority, 57%, believe AI would deteriorate the personal connection between patients and providers, whereas only 13% think it would improve this relationship.
Men, younger adults, and individuals with higher education levels are more open to AI in healthcare, but even among these groups, around half or more still express discomfort.
Most Americans (65%) would want AI used for skin cancer screening, viewing it as a medical advance, while fewer are comfortable with AI-driven surgery robots, pain management AI, or mental health chatbots.
About 40% would want AI robots used in their surgery, 59% would not; those familiar with these robots largely see them as a medical advance, whereas lack of familiarity leads to greater rejection.
79% of U.S. adults would not want to use AI chatbots for mental health support, with concerns about their standalone effectiveness; 46% say these chatbots should only supplement therapist care.
37% believe AI use in health and medicine would worsen health record security, while 22% think it would improve security, indicating significant public concern about data privacy in AI applications.
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