The AI Arms Race in Healthcare Appeals
As health insurance denials reach unprecedented levels, a technological battle is emerging where artificial intelligence is being deployed on both sides of the insurance approval process. While major insurers increasingly use AI algorithms to automatically reject claims, new platforms are fighting back with AI-powered appeal systems that help patients challenge these denials effectively.
The Personal Crisis That Sparked a Solution
Neal Shah’s journey into healthcare technology began during his wife’s cancer treatment, when he found himself buried in medical bills and denial notices. After calculating their total healthcare costs—including premiums, out-of-pocket expenses, and uncovered treatments—Shah made a shocking discovery: they might have been financially better off without insurance altogether.
“I went down a rabbit hole of research, trying to figure out what is going on with health insurance,” Shah explained. His frustration eventually led him to create Counterforce Health, a platform that uses AI to generate customized insurance appeal letters in minutes rather than the hours or days the process typically requires.
The Scale of the Denial Problem
Health insurance denials have become a defining feature of American healthcare. According to KFF data, 20% of all claims across Affordable Care Act marketplace plans were denied in 2023. With ACA plans covering over 20 million Americans at the start of 2025, this represents millions of denied claims annually.
Perhaps more troubling is how rarely these denials are challenged. Fewer than 1% of ACA plan denials are appealed, despite the fact that approximately 40% of appeals are successful when pursued. This suggests that many denials are potentially unjustified, but patients lack the resources or knowledge to fight them.
Insurers’ AI Systems Accelerating Denials
Major insurance companies have increasingly turned to AI tools to process claims more efficiently. A 2022 ProPublica investigation revealed that Cigna used an AI-driven algorithm to deny more than 30,000 claims in just two months, often without physician review. The following year, UnitedHealth faced a class-action lawsuit alleging its nH Predict AI tool prematurely cut off care for elderly Medicare patients.
These systems represent significant industry developments in claims processing, but critics argue they prioritize cost savings over patient care. The automation of denials has created what Shah describes as an unfair battle: “Insurers are using AI to deny claims in seconds, while patients and doctors spend hours fighting back.”
Counterforce’s AI-Powered Response
Counterforce Health’s platform allows patients or clinics to upload denial letters and relevant medical records. The system then analyzes insurance policies, reviews medical literature, and draws from successful appeals to produce a draft response. This approach represents one of many related innovations emerging at the intersection of AI and healthcare.
The technology doesn’t just generate boilerplate text—it analyzes the insurer’s rationale and creates evidence-driven appeals tailored to specific circumstances. This saves patients hundreds of hours of research and drafting while increasing their chances of overturning denials.
The Accessibility Challenge in Healthcare Appeals
Currently, effectively appealing insurance denials often requires resources that many patients lack. Hiring patient advocates can cost between $80-$150 per hour, putting professional appeal assistance out of reach for many Americans. With average out-of-pocket healthcare spending reaching $1,425 per person annually by 2022, adding hundreds more dollars for appeal assistance isn’t feasible for most families.
“Right now, appealing is really for the rich, or I would even say the ultra-rich,” Shah noted. Counterforce addresses this by remaining free for individuals, funded through grants and investments including a $2.47 million grant from PennAITech.
Broader Implications for Healthcare Technology
The emergence of AI-powered appeal systems coincides with other significant market trends in technology infrastructure. As these platforms evolve, they contribute to a growing ecosystem of healthcare technology solutions aimed at addressing systemic inefficiencies.
The development of such specialized AI applications reflects broader recent technology advancements across multiple sectors. Similar sophisticated systems are transforming everything from financial services to industrial automation, demonstrating how targeted AI solutions can address complex procedural challenges.
Privacy Considerations in Health AI
When using any service that handles sensitive health information, privacy is a critical consideration. Counterforce Health collects personal and health-related data—including insurance details, denial letters, and medical background—to generate appeals. The company states it doesn’t sell this information and uses encryption and other safeguards to protect it, sharing data only with trusted service providers under confidentiality agreements.
The Future of AI in Healthcare Advocacy
Shah envisions tools like Counterforce evolving into trusted, objective arbiters where both patients and insurers recognize appeals as valid and evidence-based. This represents a shift toward more transparent and equitable healthcare systems, similar to how other sectors are leveraging technology to create fairer processes.
These developments in healthcare AI parallel related innovations in other industries where technology is being used to rebalance power dynamics between large corporations and individual consumers. As these systems mature, they may establish new standards for how AI can serve as a tool for consumer protection rather than just corporate efficiency.
The ongoing battle between AI systems in healthcare appeals highlights a broader trend: as organizations deploy automation to reduce costs, counter-technologies emerge to protect consumer interests. This dynamic is likely to shape numerous industries as AI becomes increasingly integrated into critical decision-making processes.
This article aggregates information from publicly available sources. All trademarks and copyrights belong to their respective owners.
Note: Featured image is for illustrative purposes only and does not represent any specific product, service, or entity mentioned in this article.
