AI is cutting medical billing denials and admin time, saving practices thousands per provider each year.
A 2025 EY report found that private practices using AI in medical billing reduced claim denials by 25% and saved an average of $15,000 per provider annually. That's a number that demands attention. But Brandon is equally clear about the risks: AI in billing is only as good as the data you feed it — and right now, much of that data is neither clean nor complete. As William Gibson said: the future is already here, it's just not evenly distributed.
Brandon's honest estimate: AI currently replaces roughly 50% of medical billing functions — and that number is growing. The strongest current applications include real-time claim error detection, NCCI edit flagging, denial prediction based on historical payer patterns, and automation of repetitive tasks like eligibility verification and payment posting. Platforms built into clearinghouses like Change Healthcare are leading the charge. But the biggest barrier remains data quality — insurers deliberately withhold clean data, limiting how accurately AI can navigate payer rules. Until that changes, AI is a powerful tool that still requires expert human oversight.
No matter how sophisticated your AI tools become, Brandon's rule is non-negotiable: get audited. Have a human expert review what the AI is doing. The practices that get burned are the ones that hand their billing entirely to an EMR's AI promise and assume accuracy. Use AI as a second set of eyes — not as a replacement for genuine billing expertise. Don't give away the keys to your castle.
