AI’s promise to improve healthcare efficiency is being challenged as new industry data links the technology to higher costs for patients and insurers.
A report from PricewaterhouseCoopers projects that commercial healthcare costs will continue to rise across employer-sponsored and individual insurance markets through 2027. While the report identifies several factors driving medical inflation, health insurers surveyed said the growing use of AI-assisted clinical documentation and coding tools is emerging as one contributor to rising medical spending.
The report says AI-powered billing and documentation tools have helped providers capture more revenue and reduce administrative inefficiencies. However, according to health insurers, those operational gains have not translated into lower costs for payers or patients.
Instead, insurers argue that AI-assisted documentation allows providers to capture more complete clinical information, which can support higher reimbursement under existing billing rules.
The cost analysis is based on medical cost trend estimates drawn from surveys and interviews with actuaries from 27 U.S. health plans. PwC also incorporated claims data, healthcare market trends and external industry research to identify the factors expected to influence medical spending through 2027.
Nearly Two-Thirds Of Insurance Leaders Say AI Tools Are Driving Medical Inflation
Health insurance executives surveyed pointed to AI-enabled clinical documentation tools as a top driver of rising healthcare costs.
According to the report, hospitals and clinics are increasingly using AI-powered documentation and coding tools that insurers say are contributing to higher claims costs by increasing coding intensity rather than changing the care patients receive.
Tools such as autonomous AI scribes can listen to doctor-patient encounters and generate comprehensive clinical notes. AI documentation tools capture more clinical details than traditional note-taking. Coders or AI-assisted coding systems can then use the notes to assign more complex, higher-severity billing codes.
Providers argue this improves documentation accuracy, while insurers contend it can also increase reimbursement even when the underlying intensity of care has not changed proportionately.
Some health Insurers believe the AI tools are not changing the underlying care patients receive. Rather, they believe the tools mainly change how providers document, code and receive reimbursement for care.
The report details that in many practices using AI coding and billing tools, coding intensity increased but underlying treatment intensity did increase proportionately.
AI Adoption In Clinics A Core Focus
While healthcare organizations have embraced AI scribes to streamline documentation, patients, clinicians and regulators are debating how medical professions should use the technology.
Hospitals and health systems have defended the continued rollout of these tools, arguing they improve efficiency, reduce administrative burden and allow clinicians to spend more time with patients.
Insurers, however, have raised concerns about AI-assisted documentation. Some clinicians and patient advocates worry about unintended behavioral effects.
Experts caution that patients may become less forthcoming during appointments if they know AI is recording their conversations, particularly when discussing sensitive health concerns.
Despite those concerns, many healthcare technology leaders argue the benefits of AI scribes outweigh the potential risks. Nzinga Lowe, Chief Executive Officer and Founder of Pygmalion Health, said AI tools such as clinical scribes and predictive analytics are “essential for improving patient-doctor interactions and reducing clinician burnout.”
“The AI scribe makes a big impact because it keeps the physician’s eyes off the note-taking and back on the patient,” Lowe said. “It supports clinical workflows that aren’t sexy but are instrumental to the care journey. It can ensure the right codes are connected. If a patient mentions food insecurity and the AI picks it up, it can connect those codes so the patient can be reached by a community health worker or care navigator with resources.”
Health Insurers Tighten Payment Reviews As Costs Rise
In response, insurers are expected to adapt their review and payment systems to account for AI use in clinical settings.
Some industry experts warn that algorithmic friction may ultimately pass through higher costs to health plans. Insurers have communicated potential costs sharing impact to patients, including higher monthly premiums and increased out-of-pocket deductibles.
The PwC report recommends that health plans take a more targeted approach to payment integrity. Rather than increasing reviews across all claims, the firm recommends focusing prepayment reviews on specific claims. They suggest looking at those with the highest risk of billing errors, unusual coding patterns or significant financial impact.
The report identifies several areas where insurers may increase scrutiny. These areas include expensive inpatient hospital stays, patients assigned to higher-paying diagnosis-related groups (DRGs), duplicate claims and services that appear to have been improperly unbundled.
The report also flags high-cost services such as genetic testing, durable medical equipment, and medical implants for closer scrutiny.
Beyond reviewing individual claims, PwC recommends that health plans modernize their payment integrity systems. The firms suggest they do this by integrating contract requirements, clinical policies and claims-editing rules into centralized platforms. These systems could help insurers identify billing patterns that require additional review while reducing unnecessary administrative work.
It also suggests tracking changes in how providers code patient visits over time. These shifts may reflect billing behavior rather than true changes in how sick patients are. The report says this could help keep overall medical spending trends in check.
AI Scribes Raise Privacy Scrutiny
Despite ongoing debate, U.S. hospitals using Epic EHR systems have widely adopted ambient AI medical scribes. Hospitals and health systems are pushing ahead with deployment, citing reduced administrative burden and improved documentation quality.
A study found that nearly two-thirds of U.S. hospitals in Epic network use AI listening tools. The widespread adoption has not been without resistance.
Still, lawsuits and regulatory scrutiny underscore unresolved questions around consent and data handling. Earlier this year, a firm filed a class action lawsuit over recorded patient-clinician visits.
The lawsuit alleges that Sutter and Memorial Healthcare Services used AI ambient documentation tools to record patients and clinician conversations. It also alleges the audio was sent to external servers for transcription and note generation.
Plaintiffs say providers did not inform them that their medical conversations were being recorded during their visits. They allege the recordings were transmitted to third-party systems.
According to the lawsuit, the ambient listening tools violated state privacy laws and processed sensitive health information without patient consent. The rapid adoption of ambient AI scribes highlights a rapidly evolving regulatory landscape.
As adoption accelerates, regulators, payers, and providers will need to balance the benefits of better documentation and workflow efficiency. They will also need to weigh transparency, trust, and affordability in care delivery.
