According to a 2024 survey by the American Medical Association (AMA) with nearly 1,200 U.S. doctors, most (57%) said AI’s biggest help is cutting down paperwork by automating tasks. This is important because there are fewer doctors, more burnout, and more paperwork to do. Doctors said AI helps with billing codes, medical charts, visit notes, and discharge instructions. These tasks take a lot of time and keep them from spending more time with patients.
Health systems like Geisinger Health System and Ochsner Health use AI for many tasks like scheduling appointments and managing patient messages. At The Permanente Medical Group, AI tools that write notes during patient visits save doctors about one hour every day by reducing paperwork done at home. Health administrators in the U.S. see these AI tools as ways to help staff feel better and improve patient care.
Even though more doctors are interested in AI—rising from 30% in 2023 to 35% in 2024—there are still challenges. People worry about how clear AI decisions are, if AI is used properly, data safety, and who is responsible if things go wrong. These worries mean AI should be used carefully.
One main problem with AI in healthcare is that it is hard to understand how AI tools make decisions. AI systems, especially those using machine learning, work like “black boxes.” This means doctors, patients, and regulators often don’t know how the AI reached its answers. Because of this, doctors may not fully trust AI recommendations or may find it hard to explain them to patients.
AI’s complexity also makes it hard for patients to give informed consent. Patients have the right to know how AI is part of their care, but doctors may find it difficult to explain AI clearly. Some places, like countries in the European Union, require telling patients when AI is used, but U.S. rules do not always require this. This lack of clear rules can make it hard for healthcare providers to be fully open with patients.
Monitoring AI is also important. From research to using AI in clinics, rules must keep AI safe, fair, and effective. The FDA watches over AI medical devices but has a tough job keeping up with new AI technology. Hospitals and clinics need their own rules and ethics committees to check and watch AI tools.
The AMA says there should be clear rules about AI and that doctors should always have the final say in medical decisions. Medical groups must balance AI benefits with human judgment to keep care safe and right.
AI systems use large amounts of patient data from electronic health records (EHRs), manual entries, Health Information Exchanges (HIEs), and the cloud. Protecting this data is very important, especially when third-party companies provide AI software.
In the U.S., the Health Insurance Portability and Accountability Act (HIPAA) mainly controls patient data privacy and security. But AI creates new risks:
Programs like HITRUST’s AI Assurance work to handle these risks by combining rules like the National Institute of Standards and Technology’s (NIST) AI Risk Management Framework and the White House’s AI Bill of Rights. These aim to keep AI use clear, responsible, and respectful of patient privacy.
Healthcare managers must carefully check AI vendors to ensure they follow strong security rules, use encryption, control access, log actions, find weaknesses, and train their staff. Having plans to quickly respond to security problems is also very important.
Who is legally responsible when AI is used in healthcare is a tricky question. Usually, the doctor who treats the patient is responsible. AI adds new complications:
Legal steps to reduce liability include clear policies on AI use, assigning who watches over AI, educating staff about AI, and carefully adding AI to clinical work.
AI automation can be useful if carefully added to healthcare work routines. For medical offices in the U.S., AI can lower paperwork and make things run smoother so doctors and staff have more time for patients.
Examples of AI automations include:
Adding these tools needs good planning to work with existing electronic records and clinic routines. Doctors should be involved to avoid problems and help smooth changes.
Administrators should also think about ethics. Automation should help staff, not replace doctor judgment or reduce human contact needed for patient care.
Training and clear rules are important so staff know when and how to use AI properly, keeping professional responsibility while benefiting from the tools.
Ethical AI use in healthcare is based on four key ideas: respecting people’s choices, doing good, avoiding harm, and fairness. These guide many challenges about watching AI, data use, and openness.
These ethical ideas come from groups like the AMA and the American Nurses Association (ANA), as well as rules like the HITRUST AI Assurance Program, NIST AI standards, and privacy laws.
Using AI well in healthcare takes many steps focused on rules, training, and policies:
By taking these steps, healthcare administrators, practice owners, and IT managers in the U.S. can use AI tools to improve operations and patient care while keeping ethical standards, protecting patient data, and reducing legal issues. AI can help reduce paperwork that tires doctors and make care better, but careful management is needed as the technology grows.
Physicians primarily hope AI will help reduce administrative burdens, which add significant hours to their workday, thereby alleviating stress and burnout.
57% of physicians surveyed identified automation to address administrative burdens as the biggest opportunity for AI in healthcare.
Physician enthusiasm increased from 30% in 2023 to 35% in 2024, indicating growing optimism about AI’s benefits in healthcare.
Physicians believe AI can help improve work efficiency (75%), reduce stress and burnout (54%), and decrease cognitive overload (48%), all vital factors contributing to physician well-being.
Top relevant AI uses include handling billing codes, medical charts, or visit notes (80%), creating discharge instructions and care plans (72%), and generating draft responses to patient portal messages (57%).
Health systems like Geisinger and Ochsner use AI to automate tasks such as appointment notifications, message prioritization, and email scanning to free physicians’ time for patient care.
Ambient AI scribes have saved physicians approximately one hour per day by transcribing and summarizing patient encounters, significantly reducing keyboard time and post-work documentation.
At the Hattiesburg Clinic, AI adoption reduced documentation stress and after-hours work, leading to a 13-17% boost in physician job satisfaction during pilot programs.
The AMA advocates for healthcare AI oversight, transparency, generative AI policies, physician liability clarity, data privacy, cybersecurity, and ethical payer use of AI decision-making systems.
Physicians also see AI helping in diagnostics (72%), clinical outcomes (62%), care coordination (59%), patient convenience (57%), patient safety (56%), and resource allocation (56%).
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