While artificial intelligence solutions can reduce administrative burden in prior authorizations and billing, organizations are reporting increased transaction volumes and higher costs, according to a new report.
The Peterson Health Technology Institute took insights from a January 2026 workshop featuring senior leaders from a spectrum of organizations, ranging from health systems to federal agencies. Leaders discussed ways in which technology and policy can enable AI to reduce administrative costs, accelerate payment cycles and promote high-value care.
AI has the potential for organizations to execute expedited prior authorizations at reduced costs, though the report (PDF) notes there is no existing evidence that it “translates to lower average cost per claim factoring in the cost of the AI solution.”
Participants also cited increased system activity—including back-and-forth "bot wars"— as well as limited impact on complex cases and unintended consequences as potential risks for deploying AI in prior authorizations.
The report also said that real-time prior authorization at the point of care is an emerging model, though not currently scalable and that AI’s impact is limited by policy variations. Participants offered several suggestions to improve current data standardization, including requirements for electronic health record (EHR) vendors' integration of standard prior authorization APIs and extending requirements for standardized electronic transaction types to additional health plan types.
When examining AI’s role in medical billing, the report found that provider deployment is “increasing billing intensity and medical spending,” particularly AI scribes, who are increasing billing intensity in evaluation and management and in diagnostic-related groups complexity add-on codes.
“AI is accelerating growth in higher-complexity billing, which has already strained affordability in recent years,” the report said. “The result is a trajectory that payers and patients cannot continue to absorb.”
AI tools have become commonplace in healthcare organizations across the U.S. A March survey from Eliciting Insights found 75% of health systems are using at least one AI platform, up from 59% in 2025. Moreover, 50% of respondents indicated their systems use three or more AI applications.
As deployments increase, systems are reporting major barriers in implementation efforts—with 74% of respondents in a Qventus report citing EHR vendor reliance as an obstacle.
Amid increased billing intensity, the report said healthcare plans are using “across-the-board downcoding” and other reimbursement reductions. However, the impact of such reductions is currently unknown—and may “disproportionately harm” providers that have not yet adopted AI tools.
Moreover, the report said current healthcare plans are “likely not sufficient to address AI-driven medical inflation,” and urged coordinated policy to address it.
“The discussion reinforces a core reality: as currently deployed, AI in healthcare administrative processes is likely to achieve only some of its goals—such as reducing the manual effort for organizations to execute prior authorization requests and submit billing claims—while simultaneously increasing healthcare costs,” PHTI executives said in the report.
Moreover, when considering workflows, data complexity and incentives, AI “exacerbates the underlying issues,” the report said. To ultimately reduce administrative waste, researchers said deployment processes will need to be redesigned.