Algorithms Now Argue Over Your Medical Bill

Artificial intelligence is moving into the financial mechanics of healthcare payments, and the stakes are measured in billions. Hospitals are deploying the technology to maximize reimbursement, while insurers use their own AI systems to audit claims and challenge charges, turning a decades-old conflict over medical billing into an algorithm-driven contest over how care is priced and paid for.

The numbers on both sides reflect the amount at play. UnitedHealth Group projects AI could save it nearly $1 billion in 2026, while HCA Healthcare expects roughly $400 million in AI-driven cost savings, partly from automating revenue management, according to Reuters. On the other side of that ledger, Blue Cross Blue Shield has released an analysis suggesting that AI-enabled coding practices may be responsible for more than $2 billion in additional claims spending nationwide.

Hospitals Use AI to Optimize Billing

Hospitals are turning to AI to automate clinical documentation and medical coding, the process of translating care into standardized billing codes submitted to insurers. These tools use ambient listening technology to capture clinical interactions in real time, then analyze physician notes and lab reports to automatically assign billing codes, a workflow that proponents say reduces paperwork and physician burnout.

But the Blue Cross Blue Shield Association analysis of de-identified claims data found patterns that raise questions about accuracy. Researchers tracked a sharp rise in diagnoses of acute posthemorrhagic anemia at hospitals that had publicly disclosed AI adoption. In many of these cases, patients coded with the condition never received blood transfusions, a treatment typically associated with it. That diagnosis spike alone added $22 million to maternity admission costs in one year.

Looking across all facilities, the analysis attributed about $663 million in inpatient spending and at least $1.67 billion in outpatient spending to AI-powered coding practices.

Federal data shows 7 in 10 U.S. hospitals used predictive AI in 2024, with AI use for billing jumping 25% year over year, according to U.S. News and World Report.

Insurers Use Their Own Algorithms

As hospitals automate revenue capture, insurers are deploying AI to audit claims and deny coverage at scale. The share of provider claims denied more than 10% of the time has risen from 30% three years ago to 41% today, according to Experian. Insurers on Affordable Care Act marketplaces denied nearly 1 in 5 in-network claims in 2023, up from 17% in 2021, according to KFF.

UnitedHealth Group has faced scrutiny from federal lawmakers over its use of algorithms to deny care to seniors enrolled in Medicare Advantage, according to industry news site Stat. Humana and other insurers face lawsuits and regulatory investigations over similar practices, said Revenue Cycle Coding Strategies. The industry argues AI improves efficiency and reduces costs by processing high volumes of claims data that would otherwise require extensive manual review.

Patients are beginning to arm themselves with AI tools as well, according to North Carolina Health News. Startups, including Sheer Health and the nonprofit Counterforce Health, have built tools that help patients analyze denial letters, cross-reference their insurance policies and draft appeals. Historically, fewer than 1% of denied claims are appealed, and patients lose more than half of those appeals.

Consumer AI tools are designed to shift that math, though Carmel Shachar, assistant clinical professor of law and the faculty director of the Health Law and Policy Clinic at Harvard Law School, warned that it can be difficult for a layperson to understand when AI is doing good work and when it is hallucinating or giving something that isn’t quite accurate, according to North Carolina Health News.

Regulation Meets Rapidly Scaling Problem

The speed of AI deployment on both sides of the healthcare billing divide is outpacing regulatory frameworks. The site said more than a dozen states passed laws regulating AI in healthcare in 2025, with Arizona, Maryland, Nebraska and Texas among those banning AI as the sole decision-maker in prior authorization denials. Broader federal standards have not kept pace.

The concern for regulators is not simply that AI speeds up billing disputes. It is that automated systems on both sides risk optimizing for financial outcomes rather than clinical accuracy, with patients caught between competing algorithms.