Windows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallOutdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchHealth insurers use AI and machine learning to help check claim information, automate some routine processing, flag unusual claims, recommend actions and route cases to human examiners. These systems do not all work the same way, and evidence that an insurer uses AI does not establish that AI made a particular decision—or that it made every approval or denial.
What tasks can AI perform during claims processing?
After a provider delivers care, the insurer processes the provider’s claim to determine how it should be handled under the member’s coverage and the provider’s contract. AI can be used for several administrative and review tasks within that post-service process:
As an Amazon Associate I earn from qualifying purchases.
- Organize and check claim information: analyze codes and other claim data, identify coding issues or edits, and check whether billed amounts align with contract terms.
- Automate routine work: help process claims that meet established criteria or resolve routine edits.
- Flag claims for closer attention: identify possible duplicate billing, fraud, waste or abuse, or assess risk associated with high-dollar claims.
- Support decisions and routing: offer recommendations or insights related to approval, or prioritize cases for manual examiners.
These uses can involve different kinds of technology. A predictive system may classify or estimate the risk of a claim; a generative system may produce text or summarize information. The National Association of Insurance Commissioners (NAIC) survey includes insurer-reported examples across these categories, but it does not establish that every insurer uses every tool.
How might an AI-assisted claim review work?
A typical illustration—not a universal insurer process—is that software first checks incoming claim fields and compares them with rules, contracts or patterns. Depending on the system and the insurer’s workflow, a claim could then be processed routinely, adjusted, flagged, held for more information or sent to an examiner. Some systems support recommendations; others may automate parts of a workflow.
#1 Best Overall
- Check the input: software analyzes claim data, such as codes and billed amounts, and may identify missing information or an edit that needs resolution.
- Apply comparisons or classifications: the system may compare amounts with contract terms, classify a claim, or identify patterns that merit attention.
- Choose a workflow path: the claim may continue through routine processing or be directed to a different path, such as an examiner’s queue.
- Complete the review: an insurer’s process determines the resulting claim handling. The level of human involvement varies by task and system.
This sequence explains possible roles for AI; it should not be read as a description of one insurer’s exact system or as proof that a model makes a medical-necessity determination.
How common is AI in claims adjudication?
The NAIC’s Health AI/ML Survey Report, published in May 2025, summarizes responses from 93 insurance companies in 16 participating states. The survey was conducted from November 2024 through January 2025. Respondents met premium-size or market-share criteria, so its counts describe the surveyed companies, not every health insurer in the United States.
Rank #2
In the report’s broad operational-area table, companies reported the following status for claims adjudication AI/ML:
The Tool Desk
Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →| Reported status | Companies |
|---|---|
| Already in production | 31 |
| Implementation within one year | 10 |
| Implementation within one to three years | 7 |
| Implementation beyond three years | 2 |
| Not applicable | 43 |
These are response counts from that table, not market-wide adoption percentages. The report includes deployed uses as well as plans and exploratory work; a planned or explored application should not be treated as a production system. Other survey questions use different company or market denominators, so figures from separate questions are not necessarily directly comparable.
Rank #3
Can AI deny a health insurance claim?
AI can be part of a workflow that automates processing or supports a recommendation, but the available evidence does not show that AI alone makes every approval or denial. Routing a claim to an examiner is also a documented use. An automated step does not, by itself, establish that a model independently decided whether care was medically necessary or made the final denial decision.
Nor does a denial prove AI was involved. Without information connecting a specific claim outcome to a particular system, it is not possible to infer the reason for that outcome from an insurer’s general use of AI.
Rank #4
Is prior authorization the same as claims adjudication?
No. Claims adjudication generally happens after care is delivered and concerns the provider’s claim. Prior authorization is a separate, pre-service review of whether planned care requires approval. The NAIC survey treats these as distinct operational categories, so prior-authorization activity should not be counted as post-service claims use.
Free tools Windows power users keep installed
One-click scans. No signup required.
Insurers reported AI/ML applications in prior authorization such as checking whether authorization is required, extracting information from medical records, checking document completeness, reviewing requests and routing them through approval or denial pathways. These are varied insurer-reported examples, not evidence that every insurer applies AI to authorization decisions.
Best Value
Federal rules are relevant to electronic prior authorization and data exchange, but they do not establish how an insurer’s AI makes claim decisions. CMS’s Interoperability and Prior Authorization Final Rule set deadlines for impacted payers: certain provisions were due January 1, 2026, while most API requirements are due primarily January 1, 2027.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What is known about oversight and consumer impact?
The NAIC adopted its Model Bulletin on the Use of Artificial Intelligence Systems by Insurers in December 2023. The bulletin provides guidance and expectations for responsible insurer AI use aligned with NAIC AI Principles. The NAIC also describes ongoing work on third-party data and models and an AI Systems Evaluation Tool for regulators.
AI could help speed routine work, surface errors or fraud indicators, and direct human attention to cases needing review. It can also produce opaque classifications or carry forward flawed data, potentially leading to inappropriate outcomes if a model or its use does not fit coverage rules and an individual’s circumstances.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsHealth Affairs’ analysis identifies an important limit in the available evidence: studies have not compared denial or wrongful-denial rates in reviews with and without AI. That means the evidence described here does not establish that AI itself raises or lowers denial rates. Adoption and performance are different questions; the existence of a system is not proof that its results are accurate or fair.
What can you do if a claim is denied?
Focus first on the explanation for the specific claim rather than assuming AI was involved. Review the insurer’s denial notice and explanation of benefits, identify the stated reason, and compare it with the relevant coverage information. If you believe the outcome is incorrect, follow the appeal instructions and deadlines in the notice or your plan documents, and provide supporting records relevant to the reason given.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
