Why AI Won’t Boost Your Denial Recoveries—And What It Should Be Doing Instead

AI companies love to promise that their tools can recover more denied revenue. But if your revenue cycle team is already effectively working and overturning all collectible denials, that promise doesn’t hold water.

Here’s the reality: when all recoverable denials are being addressed and turned into payments, AI won’t magically increase your cash. In fact, it might cost more to implement than the value it adds. The smarter move? Use AI upstream—not to chase denials after they happen, but to prevent them from happening in the first place.

The Denial Recovery Myth

Many AI vendors market “recovered revenue” through denial management automation. But more often than not, that simply means working denials that your team is already resolving. It’s not additional revenue—it’s duplicate effort with a higher price tag.

If your organization already has effective denial management processes in place, AI chasing those same denials won’t generate incremental reimbursement. In some cases, it could even increase your cost to collect.

The only time AI has real impact on denial recovery is when denials are going unworked due to resource or bandwidth constraints. If that’s not an issue for your team, AI recovery tools won’t deliver a strong ROI.

Where AI Can Add Value: Denial Prevention

The real opportunity for AI isn’t in denial management—it’s in denial avoidance. By identifying and correcting potential denial triggers before the claim goes out the door, AI can prevent revenue loss and speed up cash flow.

Here are key ways AI can improve upstream processes and reduce preventable denials:

Authorization Review

• Does the billed service require authorization?
• Is an authorization number on the claim?
• Does the authorized CPT match the billed CPT?

AI can scan for mismatches and flag missing data within days of service—allowing time for payer outreach. Most payers are more likely to issue retro authorizations or correct mismatches shortly after service, rather than post-denial weeks later.

Medical Necessity Validation

AI can compare CPT codes and diagnoses against payer-published medical necessity policies before claims are submitted. If supporting documentation is missing:

• It can trigger a record review.
• Or automatically query providers for updated diagnoses or notes.

This can also be done pre-service, allowing you to issue ABNs or notify patients of potential non-coverage in advance—avoiding downstream write-offs.

Real-Time Eligibility Checks

Coverage often changes between time of service and billing. AI can:

• Run real-time eligibility checks using payer portals right before claim submission.
• Alert teams to changes that may impact authorization requirements or claim validity.

This second layer of validation ensures issues are caught before they become denials.

Payer-Specific Billing Rules

AI can be trained to:

• Interpret and apply unique billing requirements across different payers.
• Edit claims pre-submission to meet those rules.
• Compare payer denials against their published policies to identify and challenge improper rejections.

This not only reduces preventable denials but also strengthens your ability to appeal incorrect ones.

How OS inc. Can Help You Use AI The Right Way

At OS, Inc., we don’t just implement technology for technology’s sake. We focus on practical, cost-effective ways to improve your revenue cycle. When it comes to AI, we help healthcare organizations avoid the hype and apply it where it actually creates value—in denial prevention, not redundant recovery.

Here’s how we support your success:

Revenue Cycle Assessment

We evaluate your current denial trends, workflows, and cost-to-collect to determine whether AI will deliver ROI—or simply add overhead.

Strategic AI Integration

We help you deploy AI where it works best:

• Catching authorization issues early
• Validating medical necessity before claims go out
• Running real-time eligibility rechecks
• Applying payer-specific billing edits automatically

We work with your existing platforms and processes, ensuring AI complements your current operations—not complicates them.

Data-Driven Optimization

Once AI is live, we monitor performance to:

• Track avoidable denials
• Identify new payer patterns
• Refine your workflows over time
• Deep RCM Expertise

Our team brings decades of hands-on experience in revenue cycle management. We combine operational insight with smart automation to help you collect more, faster—with less friction.

Invest in Prevention, Not Duplication

If your denials are already being worked and recovered, AI won't add much by duplicating those efforts. But used proactively, AI can reduce preventable denials, increase clean claim rates, and improve time to payment.

Want to evaluate where AI could improve your performance? Reach out to OS, Inc. We’ll help you identify smart opportunities for automation and avoid the cost traps that don’t move the needle.

References:

• https://www.os‑healthcare.com/news-and-blog/denial-rates-are-climbing-what-healthcare-revenue-cycle-leaders-should-be-watching-in-2025

•  https://www.waystar.com/blog-rev-cycle-101-healthcare-revenue-cycle-terminology-denial-prevention-glossary/

• https://etactics.com/blog/how-to-reduce-claim-denials

• https://www.mgma.com/articles/building-denial-prevention-strategies-to-boost-your-pratices-revenue-cycle

• https://accessonepay.com/articles/inside-the-payer-playbook-common-tactics-leading-to-claim-denials/

• https://www.aspirion.com/5-common-causes-of-healthcare-denials-and-how-ai-can-tackle-them/

• https://www.aao.org/practice-management/news-detail/refine-revenue-cycle-utilize-prior-authorization