AI Can Fix Prior Authorization, but Only With Humans in the Loop

By Your Health Magazine Contributor

Your Health Magazine Contributor

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AI Can Fix Prior Authorization, but Only With Humans in the Loop

Artificial intelligence is moving quickly into prior authorization. Health plans see a way to cut backlogs and speed up approvals. Many physicians see something else: a faster way to say no.

That fear is well documented. In the 2025 AMA Prior Authorization Physician Survey, 74% of physicians said denials have increased over the past five years, and six in ten worry AI will push denial rates even higher.

The real question is not whether AI belongs in prior authorization. It is where it belongs, and where it does not.

The Real Bottleneck Is Messy Data

Most prior authorization delays do not come from hard clinical decisions. They come from paperwork.

Requests arrive as faxed forms, scanned clinical notes and loose attachments. Key details are often missing or buried on page nine of a PDF. Reviewers spend much of their time hunting for information before they can even start evaluating a case.

The burden lands on both sides. Physician practices report spending an average of 13 hours a week on prior authorization, and 40% employ staff who do nothing else. On the health plan side, nurses and pharmacists face the same pile of unstructured documents.

Where AI Earns Its Place

The most valuable uses of AI in prior authorization are operational, not clinical. Used well, it helps information move through the process faster and cleaner:

●Extracting data. AI can read clinical notes, lab results and attachments and turn them into structured, searchable information.

●Finding gaps early. It can flag missing documentation as soon as a request arrives, so providers can fix it before the clock runs down.

●Routing faster. Requests can be sorted by urgency and type and sent to the right reviewer right away.

●Summarizing for reviewers. A clear clinical summary lets a nurse or physician reviewer focus on the medical question, not the paperwork.

None of these steps make a coverage decision. They simply get a complete, organized case in front of a qualified reviewer sooner. As one industry analysis of where AI works in medical utilization management puts it, the goal is smarter workflows, not hands-free decisions.

Where Clinicians Must Stay in Charge

Prior authorization decisions involve incomplete records, policy nuance, exceptions andpatient-specific details. Those are judgment calls, and they need a human who is accountable for the outcome.

That means AI should support clinical review, never replace it:

●Clinical interpretation of a patient’s history and needs

●Policy judgment when a case does not fit neatly into written criteria

●Exception handling for complex or rare conditions

●Denial decisions, which should always rest with a qualified clinician

Trust is the deciding factor. In the same AMA survey, only 24% of physicians said reviews are consistently conducted by qualified clinicians. Health plans that use AI to strengthen their clinical teams, rather than bypass them, have a real chance to rebuild that trust.

Connected Systems and the 2027 Deadline

Even the best AI struggles inside disconnected systems. If data cannot move cleanly between providers, EHRs and health plans, automation only speeds up part of the process.

Federal rules are now forcing that connection. The CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F) applies new prior authorization requirements to Medicare Advantage, Medicaid, CHIP and certain federal exchange plans. Requirements include:

● For most impacted payers, decide expedited requests within 72 hours and standard requests within seven calendar days
● Give providers a specific reason for denied prior authorization requests
● Publicly report prior authorization metrics each year
● Support a standards-based FHIR Prior Authorization API beginning January 1, 2027

Meeting these standards at scale takes prior authorization platforms that combine automation, FHIR interoperability and clear audit trails, with clinicians still making the final call.

The Bottom Line

AI will not fix prior authorization by making decisions faster. It will fix it by removing the paperwork that slows good decisions down.

Health plans that use AI to organize data, catch gaps and route work, while keeping clinicians accountable for every determination, can meet the new federal deadlines and win back physician trust. Most importantly, these changes have the potential to reduce delays and help patients access needed care sooner.