AI Will Escalate Prior Authorization Battles, Not End Them

The healthcare industry's narrative around artificial intelligence and prior authorization is built on a comfortable fiction: that automation will usher in a new era of collaboration between payers and providers. According to Mika Newton, CEO of xCures, that story is dangerously wrong.

The reality is starker. Prior authorization has always been adversarial—payers controlling costs, providers seeking payment for care, patients caught between them—and AI will not change that fundamental dynamic. What it will do is amplify an imbalance that has existed for 30 years, and the consequences will fall hardest on patients who have no algorithmic defense.

The asymmetry is accelerating

Payers are deploying AI faster and at greater scale than providers, processing more prior authorization decisions in a week than most health systems see in a year. Recent litigation against major insurers over algorithmic denial practices previews what happens when the speed of automated denial outpaces the speed of human appeal. When a payer can generate a defensible-looking denial in milliseconds and the provider's appeal takes 30 days, the structural imbalance becomes industrialized.

Meanwhile, providers are being sold AI tools that promise to fight back with faster, cleaner submissions. Most will simply produce denials more efficiently. The result: an adversarial arms race that will escalate costs passed to premiums and patients, not converge on better care decisions.

The human cost is already measurable. The American Medical Association's latest physician survey found that 60% of doctors expect AI to increase prior authorization denials. More than one in four physicians report a prior authorization process has led to a serious adverse event for a patient in their care. One in three say criteria are rarely or never evidence-based. Ninety-five percent report care delays.

Why it matters

The prior authorization debate is being framed as a technology problem when it is fundamentally an evidence problem. Without shared, structured clinical records that both payers and providers must reckon with, AI will only accelerate arguments conducted from partial information—where the side with more resources wins more often, and patients lose in the gap.

The only durable solution

Today's prior authorization fights happen between parties who do not share a record. Payers have claims data and policy. Providers have notes, labs, imaging, and the patient. Nobody has a complete, structured view of what actually happened. Both sides argue from fragments, and leverage determines outcomes more than evidence.

If AI's contribution is faster denials and appeals on the same broken evidence base, the industry will have built a more efficient version of what physicians describe as moral injury. But if AI produces structured, complete, defensible clinical records that both sides must address, the calculus changes—not because the conflict ends, but because it finally happens on the merits.

That means regulators should demand AI-driven transparency: every prior authorization decision carrying its reasoning, evidence, and policy citation in auditable form. Health plans whose AI generates denials that systematically disappear under independent review should face consequences proportional to volume. And providers should invest in clinical data infrastructure that makes their case undeniable, not tools that promise to beat payer algorithms.

The future of prior authorization is not collaboration. It is contested, evidence-based, auditable adjudication conducted at software speed, with the patient's actual clinical reality finally in the room.

These details were first reported by Mika Newton writing in MedCity News.