Bill Review: How AI is Transforming the Process
By Caroline Caranante | Nov. 17, 2025 | 4 min. read
What you will find below:
- Breakdown of How AI is Reducing Manual Work, Preventing Errors, and Speeding Up the Bill Review Process
- Insights into Growing AI Billing and Coding Markets
- Examples Showing How Automation Improves Accuracy, Cash Flow, and Administrative Efficiency
Bill review has always been one of the most time-consuming and expensive parts of medical management. Manual data entry, coding complexities, and accuracy issues make the process slow and costly. But AI and automation are rapidly changing that.
Taking Over the Painful Parts of Bill Review
For years, much of the billing workflow has relied on people manually typing information into systems. Not only is that slow, it’s also where most mistakes happen.
That’s why it’s such a big deal that AI can now automate up to 60% of the medical billing process. AI isn’t taking over entire jobs; rather, it’s taking over the repetitive, error-prone parts so humans don’t have to.
By removing so much manual work, organizations are seeing real financial benefits. In fact, healthcare systems are already saving over $2 billion a year simply by using AI billing tools.
When billing processes become cleaner and more consistent, revenue improves. Some providers have seen a 20% jump in recovered revenue just by using automation to catch things they were previously missing.
Reducing Human Error in Bill Review
When it comes to bill review, human error is the silent revenue killer.
Research shows that 80% of medical billing errors come directly from manual data entry. These mistakes aren’t because the rules are unclear, but because humans are overwhelmed, distracted, or overloaded.
AI reduces that burden. Once organizations adopt AI tools, 65% of billing companies report accuracy improvements. That’s because AI is consistent. It doesn’t get tired, rush, or overlook details.
Additionally, accuracy speeds everything up. When claims are cleaner on the front end, fewer get rejected on the back end. That’s why AI leads to 50% faster claims processing, which in turn improves cash flow.
With cleaner claims and fewer administrative hassles, providers see a measurable improvement in financial stability. 70% of organizations using AI report stronger cash flow.
Cutting Costs All Around
Behind the scenes, bill review is shockingly expensive. Healthcare organizations spend 25–31% of their entire budget on administrative tasks, and two-thirds of that is tied to billing and coding alone.
That’s why reducing administrative waste is so important. AI helps by eliminating repetitive work, catching coding issues early, and routing claims more efficiently. This is how organizations are able to cut administrative costs by up to 30% when they automate key parts of bill review.
Additionally, better detection is cost-saver. AI can identify suspicious or irregular claims with 85% accuracy, making it far easier for organizations to reduce fraud, overbilling, and unnecessary spending.
Faster, Smarter, and More Accurate Coding
Coding is one of the most complex parts of bill review, and one of the best uses of AI. AI-powered coding tools can improve coding accuracy by 40%, thanks to natural language processing that can read charts, extract the right information, and recommend precise codes.
Companies like Nym Health, CodaMetrix, and Fathom are already doing this in real healthcare settings. For example, Nym’s technology can:
- Read provider notes
- Analyze the language
- Assign ICD-10 and CPT codes
- Produce audit-ready documentation
It can do all this with 96% accuracy and in a matter of seconds.
Nym is now supporting over 250 healthcare facilities, and these tools are giving coders more time to focus on difficult cases instead of routine ones.
Exploding AI Healthcare Market
The AI healthcare market is expected to reach $77.6 billion by 2026, but more importantly, the segments directly related to bill review and coding are growing even faster:
- The AI medical billing market is projected to grow from $4.49B in 2025 to $12.65B by 2030.
- The AI medical coding market will jump from $2.06B in 2022 to $7.15B by 2032.
This growth is happening because organizations are finally recognizing that fixing bill review isn’t just a tech upgrade. It’s a financial necessity.
AI isn’t replacing people, it’s replacing the parts of bill review that are inefficient, manual, and error prone. It’s helping organizations reduce cost, prevent mistakes, speed up payment cycles, and improve documentation quality from the very beginning of the process.
Want a smarter, faster medical bill review process? Talk to us today.
Check out our sources:
American Medical Association. 2022 AMA Prior Authorization Physician Survey Results. American Medical Association, 2022. https://www.ama-assn.org.
Centers for Medicare & Medicaid Services. Comprehensive Error Rate Testing (CERT) Report: 2023 Improper Payment Rate. CMS, 2023. https://www.cms.gov/research-statistics-data-systems/cert.
CodaMetrix. “AI-Driven Medical Coding Solutions.” CodaMetrix, Boston, MA. https://www.codametrix.com.
Fathom. “Automated Medical Coding with Artificial Intelligence.” Fathom Health, San Francisco, CA. https://www.fathomhealth.com.
JAMA Network. “AI, Health, and Health Care Today and Tomorrow: The JAMA Summit Report on Artificial Intelligence.” JAMA: Digital Health. https://jamanetwork.com.
Market Research Future. AI Medical Billing Market Forecast 2025–2030. Market Research Future, 2024. https://www.marketresearchfuture.com.
Nym Health. “Automated Medical Coding Accuracy and EMR Integration.” Nym Health, New York, NY. https://www.nym.health.
Smith, Jonathan, et al. “Current Applications of Artificial Intelligence in Billing Practices.” Clinical Plastic Surgery, U.S. National Library of Medicine, PMC. https://www.ncbi.nlm.nih.gov/pmc.
World Health Organization / Global Market Insights. Global Artificial Intelligence in Healthcare Market Projection to 2026. https://www.gminsights.com.