The rise of artificial intelligence could lead to even higher medical costs next year. A recent report from PricewaterhouseCoopers (PwC) indicates that healthcare expenses are forecasted to jump by 9% for employers and 8.5% for individuals by 2027. This increase is largely fueled by “AI-powered revenue optimization tools,” along with growing reimbursement pressures on healthcare providers and rising pharmacy costs.
Hossein Estiri, an associate professor at Harvard Medical School, noted that AI’s capability to uncover complex patterns might result in earlier diagnoses but could also lead to overdiagnosis—ultimately causing more treatments and further expenses. He pointed out that Silicon Valley’s approach assumes automating tasks will make products cheaper and reduce costs overall. However, he emphasizes that healthcare isn’t just about factory supply chains; drastically lowering clinical work costs may inadvertently inflate the market and lead to increased spending.
Estiri mentioned environmental scribes, who help clinicians by documenting information, effectively saving them around 20 minutes a day through their extensive usage. But he flagged a downside: as documentation becomes richer, visits could end up being coded more complexly and reimbursed at higher rates, even if the actual care doesn’t change. PwC’s findings suggest that around 70% of health plans surveyed see the implementation of AI tools for revenue capture as one of the main factors driving costs.
In recent years, there’s been a noticeable uptick in healthcare providers adopting AI tools. Particularly, the use of AI-powered scribes is gaining traction in the medical community, all aimed at lessening the documentation burden and reducing burnout among clinicians.
Estiri observed that while AI’s cost impact is significant, it’s relatively minor compared to other factors contributing to rising healthcare costs. He explained that healthcare resources are limited, and spending on AI that doesn’t yield better outcomes equates to wasted dollars compared to investments that do improve care.
A report from the Blue Cross and Blue Shield Association found that expanding AI use in hospital billing is leading to heightened diagnoses and severity being recorded without documented treatments, further escalating costs.
Despite some advocates asserting that AI could lower healthcare expenses, its effective deployment has potential for significant savings—estimated between $400 billion and $1.5 trillion in the U.S. For instance, Michael Cannon, director of health policy research at the Cato Institute, remarked that AI might enable less costly healthcare providers, such as nurse practitioners, to perform duties typically reserved for doctors, thus lowering overall costs.
Financial stress regarding medical expenses is rapidly intensifying. As the 2026 midterm elections loom, addressing healthcare costs remains a top concern among voters. A recent Gallup poll indicated that by 2025, an additional 2.8 million Americans could struggle to afford healthcare compared to the previous year.
Cannon elaborated on the dual nature of AI in healthcare—while it offers the promise of broadening access, regulatory pressures could hinder its market potential. Efforts by regulators to limit AI’s use serve as an instance of established providers leveraging government intervention to protect their interests, potentially damaging consumer outcomes.
