By Mukundan Sivaraj · AIM Media House
In two months, Cigna's automated denial algorithm rejected 300,000 claims at a rate of 1.2 seconds per review. A staggering 90 percent of those denials were reversed on appeal.
The system was wrong nine times out of ten, yet payers continue this approach because volume and speed overwhelm provider capacity to challenge each decision.
This episode encapsulates the crisis confronting revenue cycle leaders: payers are deploying AI aggressively to accelerate denials, while providers lack the capability to respond at similar scale. In 2025, denial rates averaged near 12%, with many organizations experiencing even higher volumes.
By 2025, 41% of providers report that claims are denied over 10% of the time, according to Experian Health's State of Claims 2025 report. Yet the response from healthcare organizations reveals a paradox. Although 67% of providers believe AI can improve the claims process, only 14% have implemented AI tools.
Of the small group using AI, more than two-thirds (69%) say it has successfully reduced denials and/or increased the success of resubmissions. The gap between proven capability and deployment indicates something beyond skepticism. The Architecture That Actually Works The underlying problem isn't confined to healthcare.
According to McKinsey's 2025 State of AI report , 78% of organizations now use AI in at least one business function, yet fewer than 6% report generating real financial returns. Vee Healthtek, a healthcare technology company focused on revenue cycle automation, demonstrates how to solve this constraint.
The company deployed task-specialized models to address eligibility verification and denial management. Within a year, the company says it achieved a 30% reduction in eligibility-related denials at a single client, along with 15% quality improvements and 10-20% efficiency gains for staff.
Michelle Castillon, Chief Product Transformation Officer at Vee Healthtek, explains the company's approach to AIM Media House .
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