As America’s healthcare system grapples with physician burnout, many organizations are looking to artificial intelligence as a tool to ease the non-clinical burdens surrounding care delivery.
Physician burnout is taking a toll on America’s healthcare workforce. According to the American Medical Association (AMA), more than 40% of physicians report at least one symptom of burnout, from emotional exhaustion to depersonalization, creating a crisis that endangers both doctors and patients. As hospitals and clinics grapple with mounting administrative work and persistent staffing shortages, many are looking to AI not as a futuristic cure-all, but as a workflow tool.
Applied thoughtfully, AI in healthcare can chip away at the non-clinical tasks that consume clinicians’ days, from automating documentation to reducing prior authorization friction. Health systems like Mount Sinai and Ochsner Health are putting it to work on the frontlines, and early efforts point less to disruption and more to incremental but meaningful relief.
Where burnout happens and how AI can help
When clinicians describe what drains them, it’s often the work that surrounds care: hours of after-clinic charting, inboxes that refill faster than they empty, and endless administrative tasks like prior authorizations. In fact, one of the top three reasons physicians sold their practices in 2024 was to better manage payors’ regulatory and administrative requirements.
AI offers one way to relieve these pressures. By automating administrative tasks, AI frees clinicians to focus on the aspects of care that require their expertise. Key areas where AI is already making an impact within hospitals and clinics include:
- Clinical documentation support
- Prior authorization automation
- Patient portal messaging
Physician enthusiasm reflects these opportunities. According to a recent AMA survey, enthusiasm is highest for AI tools that assist with documentation, discharge instructions, chart summaries, and workflow support across administrative tasks.
AI use cases driving physician enthusiasm
Fig 1. – AI use cases for which physicians report enthusiasm. Source: American Medical Association, Augmented Intelligence Research (February 2025).
While documentation ranks highest, other use cases are gaining traction as well. To illustrate, here are three examples where hospitals are applying AI to reduce non-clinical workload and return time to clinicians.
Clinical documentation support
Physicians spend a mean of 1.8 hours daily completing documentation outside office hours, according to research published in JAMA. This extensive administrative workload is a major contributor to burnout and drains time that could otherwise be spent with patients.
AI tools that transcribe conversations, summarize encounters, and draft clinical notes can shift that burden off clinicians’ plates. Ambient documentation systems capture patient visits in real time and generate structured draft notes, reducing manual data entry and after-hours charting, and more health systems are experimenting with the technology.
For example, Mount Sinai Health System has rolled out Microsoft Dragon Copilot to streamline documentation and automate administrative tasks for select care teams, with plans to expand system-wide in 2026. The platform combines ambient listening, advanced natural language processing, and generative AI to help clinicians document care directly within the EHR.
Similarly, The Permanente Medical Group deployed ambient AI scribes for 10,000 clinicians, supporting hundreds of thousands of patient encounters across specialties. Early results showed that most physicians using the tool saved an average of one hour per day on documentation.
Prior authorization automation
Prior authorization is one of the most frustrating administrative burdens in clinical practice. It requires documentation retrieval, payor submission, resubmission, status tracking, and often follow-up calls—all before a patient can receive care.
Physicians and their staff spend an average of 13 hours each week completing prior authorizations, handling roughly 39 requests per physician per week, and 89% say the process somewhat or significantly increases burnout, according to an AMA survey.
That strain may deepen before it improves as CMS rolls out targeted prior authorization pilots in traditional Medicare this year and finalizes rules that formalize and expand prior authorization processes for Medicare Advantage, Medicaid, and CHIP plans.
But AI tools are also stepping in to counter that pressure.
In 2025, Allegheny Health Network partnered with Humata to deploy AI-driven automation for prior authorization. The system automates the end-to-end process, from pulling clinical data and generating complete documentation to submitting it and tracking status updates. Using this method, Allegheny automates more than 200,000 prior authorizations annually, with a first-pass approval rate of 96%.
Patient portal messaging
The patient portal was designed to improve communication. For many clinicians, however, they have become a second inbox that refills faster than it empties. Messages range from medication refill requests to follow-up questions to administrative clarifications, many of which do not require physician-level decision-making but still demand attention.
AI tools can help categorize incoming messages, draft routine responses, and route administrative questions to appropriate team members. Ochsner Health, for example, has piloted AI tools to analyze and prioritize EHR inbox messages, highlighting relevant clinical details. This reduces time spent sifting through long patient messages and helps ensure important messages aren’t buried in administrative text.
Guardrails for safe AI use in clinical care
Still, AI tools come with meaningful limitations. Ambient documentation tools, for example, may mishear words, include irrelevant information, or introduce errors that require human correction, especially in noisy clinical environments or when interpreting accented speech and overlapping conversations.
Data privacy and consent are critical. Recording patient interactions and feeding patient information into AI systems demand strict safeguards to comply with HIPAA and other privacy regulations. Hospitals must remain transparent with patients and protect sensitive health information from unauthorized access.
It’s no surprise, then, that another AMA survey found physicians ranked increased regulatory oversight as the number one action needed to build trust in AI tools. AI adoption will depend as much on governance and accountability as on technical capability.
Physicians say trust in AI hinges on regulatory oversight
Fig 2. – Regulatory actions that would increase trust in AI and the likelihood physicians would adopt AI. Source: American Medical Association, Augmented Intelligence Research (February 2025).
What healthcare leaders should consider
AI can help ease clinician burnout, but only if organizations treat it as a priority. Leaders should focus on:
- Investing in the heaviest administrative burdens: Target tools for documentation, creation of discharge notes, prior authorizations, patient messaging, or other specific use cases based on your organization’s needs.
- Building strong guardrails: Ensure accuracy, privacy, and HIPAA compliance; protect sensitive patient information.
- Integrate thoughtfully: Train staff, monitor performance, and embed AI into workflows, so it complements, not complicates, care.
Trust is built incrementally. Starting with simpler tasks can allow health systems to demonstrate safety and reliability before expanding into more complex domains.
Restoring medicine to medicine
Technology alone will not fix burnout, but thoughtfully deployed AI can reduce administrative drag and give clinicians back something increasingly scarce: time. The real opportunity is to restore bandwidth, and with it, the practice of medicine itself.
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