AI Could Speed Up Health Insurance Approvals. Doctors Fear It Will Just Deny More Claims.

Key points

• Prior authorization is the process where a health insurer must approve a treatment before a patient can receive it.
• A 2025 American Medical Association survey found 61 percent of physicians worry AI tools will increase wrongful denials of necessary treatments.
• AI could, in theory, process straightforward approval requests far faster than human reviewers.
• Doctors already report that slow approvals cause many patients to abandon treatments their physician recommended.

Before your doctor can give you certain medications or perform certain procedures, your health insurer often has to say yes first. That process is called prior authorization, and for millions of patients it means waiting, sometimes for days or weeks, while paperwork travels between a clinic and an insurance company.

The idea behind it is reasonable. Insurers use the process to check whether a cheaper or equally effective treatment exists before they pay for something costly. In practice, though, it creates real harm. Physicians consistently report that patients give up on recommended treatments while waiting for approval, simply because the wait is too long.

Now insurers and health-tech companies are looking at artificial intelligence, the technology behind chatbots like ChatGPT, to speed things up. An AI system can read thousands of documents quickly and flag which requests clearly meet the insurer's own rules. For a straightforward, unambiguous case, that could mean same-day approval instead of a week-long delay.

But there is a serious concern attached to that speed.

The American Medical Association, the main professional body for US doctors, surveyed physicians in 2025 and found that 61 percent worry that AI tools will produce more wrongful denials, rejecting care that is genuinely necessary. The concern, as reported by Ars Technica, is that an AI system trained to find reasons to decline requests will do exactly that, efficiently and at scale.

Patients who are denied can appeal, but an appeal takes more time and energy, and many people simply cannot wait.

The technology is not inherently the problem. AI is good at pattern-matching against fixed rules. Where it struggles is with the messy, individual circumstances of real patients, the person whose condition does not fit neatly into a standard category, or whose history makes an unusual treatment the right call. A system optimised to cut costs may not weigh those nuances carefully.

What does this mean for patients right now?

For most people, nothing changes today. AI-driven prior authorization is still being piloted, not yet standard practice. What you can do is keep records. If your doctor recommends a treatment, ask for written documentation of the medical reasoning. If a claim is denied, that paperwork is your foundation for an appeal.

The debate is really about who is accountable when AI makes a call that harms a patient. Regulators and lawmakers are starting to ask that question. The answer will shape whether this technology speeds up care or quietly blocks it.