AI was supposed to streamline healthcare and reduce costs, but a new PwC report reveals the opposite trend. Instead of trimming waste, AI tools are making medical bills larger by documenting more granular details about diagnoses and complications. These systems capture specifics that rushed human clinicians might group into broader billing codes, creating opportunities for higher reimbursement rates.

The report identifies AI as one of five drivers pushing healthcare costs up 9% by 2027—the highest rate since 2010-11. Blue Cross Blue Shield data shows the billing code for acute posthemorrhagic anemia in new mothers jumped from 4% to 12.3% of maternity admissions between 2022 and 2025, while actual blood transfusion rates barely changed. Audits reveal fewer than 20% of these coded cases met clinical criteria for the diagnosis.

This practice of 'coding intensity' added $22 million to maternity spending across studied hospitals over three years. While AI represents a new cost pressure, traditional factors like labor and supply costs still drive most increases. The finding illustrates how technology often optimizes for revenue before efficiency—hospitals adopted AI tools primarily for billing accuracy, inadvertently finding ways to justify higher payments.

Healthcare executives acknowledge this reality, noting companies will leverage AI to advance their financial interests. Whether these tools eventually reduce administrative costs or enable earlier diagnoses remains an open question. For now, AI's most widespread healthcare application appears to be maximizing reimbursement rather than minimizing expenses.