‘Bot vs. Bot’: How Automated Authorizations Are Fueling Healthcare Costs

Introduction: The Rise of Automated Battles in Healthcare

As artificial intelligence (AI) technologies advance, the healthcare industry is undergoing a profound transformation—not just in patient-facing diagnostics and treatment, but also in administrative processes and back-office operations. One of the most telling developments is the emergence of what’s being called the ‘bot vs. bot’ dynamic. Here, AI systems deployed by both healthcare providers and payers (insurance companies) are increasingly interacting, sometimes clashing, in a highly automated realm of prior authorizations and claims appeals.

According to Ashis Barad, chief digital and information officer at Hospital for Special Surgery (HSS) and an expert with experience on both sides of the system, this situation is escalating costs for everyone involved. Let’s dive deep into how this dynamic has emerged, why it matters, and what the broader implications could be for payers, providers, and—importantly—patients in the U.S. healthcare system.

The ‘Bot vs. Bot’ Dynamic Explained

What Are Prior Authorizations and Appeals?

Prior authorization is a required process where healthcare providers must obtain approval from payers before delivering specific treatments, medications, or procedures. It is intended as a cost-control mechanism but has long been criticized for causing administrative burden, treatment delays, and patient stress.

Historically, these authorizations were reviewed by humans. However, to handle increasing volumes and reduce processing time, both payers and providers have begun to use AI-driven automated systems—“bots”—to manage prior authorizations and appeals. On the surface, automation promised greater efficiency. But as more organizations participate, the system has become more complex and, some argue, less cost-effective.

A New Age of Bureaucratic Automation

Providers are deploying bots to auto-generate clinical documentation and submit authorizations at scale. Meanwhile, payers deploy their own bots to review submissions, flag irregularities, and even initiate denials. In some scenarios, providers’ bots quickly reformat and resubmit information to overcome payer denials, creating an endless cycle of automated interactions. Rather than streamlining workflows, this ‘bot vs. bot’ scenario creates a feedback loop of escalating administrative back-and-forth.

Financial Pressures Mount: Who Pays?

Administrative Overhead Grows

Each new phase of automation was meant to ease costs by eliminating manual labor and reducing time-to-decision. Yet, the upsurge in automated prior authorization systems has led to an administrative “arms race.” As both sides escalate their investments in technology, the overall cost of managing these processes grows rather than shrinks. Vendors, consultants, and tech integration specialists all add layers of expense as organizations race to develop the next best automation—frequently with conflicting goals.

Increased Costs for All

The additional overhead frequently gets passed on in several direct and indirect ways. Providers may need to increase staff to manage the exceptions that AI bots cannot resolve. Payers often require expensive technology upgrades to keep pace with provider innovations. Ultimately, these costs are reflected in higher insurance premiums, increased co-pays, or even reduced provider reimbursement.

For patients, this means care delays and the possibility of higher out-of-pocket expenses. The friction also contributes to physician burnout, as clinicians struggle with constantly changing protocols and resubmissions.

Personalization and Data Sharing: A Path to Real Efficiency

Barriers to Collaboration

Ashis Barad argues that the true solution isn’t another incremental automation, but genuine cooperation between payers and providers. By sharing data and collaborating to design more personalized care pathways, the industry could reduce unnecessary authorizations, minimize appeals, and streamline patient journeys.

Currently, technical incompatibilities (different data standards, EHR systems, and information silos) stand in the way. There is also a question of trust. Both sides are hesitant to share data out of fear of reprisal, fraud, or regulatory consequences. Overcoming this reluctance would require industry standards, regulatory clarity, and potentially new business models centered on shared value rather than adversarial cost-containment.

Beyond Bots: Redesigning Incentives and Workflows

True transformation might look like creating a single, integrated, rules-based system in which care protocols, coverage decisions, and clinical data are jointly reviewed in real time. In such a model, only cases that truly deviate from clinical best practices or that flag legitimate cost concerns would be routed for further investigation. This would allow automation to complement, rather than compete, improving both speed and accuracy while reducing friction and unnecessary spending.

Current Outlook: Growing Pains and Cautious Optimism

The Short-Term Reality

For now, the industry remains mired in a period of adjustment. Provider organizations and payers continue to refine their AI tools, seeking ever-greater efficiency in their respective domains. The cumulative effect, however, appears to be a stalemate: costs are growing, frustrations are increasing, and the much-promised benefits of AI-driven administration remain elusive for many organizations.

Potential for Disruption

Nonetheless, as standards emerge and regulatory attention increases, there is hope that the ‘bot vs. bot’ wars give way to a collaborative ecosystem. Pressure is mounting for both sides to align on interoperability, transparency, and patient-centric outcomes.

Industry Implications

Vendor Landscape

As payers and providers invest in competing AI solutions, a fragmented technology market has developed. Vendors that can bridge the gap—offering tools for secure, real-time data sharing and adaptive automation—stand to gain significant traction. At the same time, established EHR and claims management vendors may feel pressure to expand capabilities or face obsolescence.

Policy and Regulatory Environment

Government agencies and standards organizations are watching closely. Policy frameworks could soon require progressive disclosure of the algorithms used in authorization decisions, and there is likely to be increased scrutiny of how administrative costs factor into both insurance rates and provider reimbursement formulas. Industry groups may also look to establish new best practices for data interoperability and dispute resolution using digital tools.

Conclusion

The rapid automation of administrative processes in healthcare, while promising in theory, has produced a phenomenon where both payers and providers are participating in a ‘bot vs. bot’ arms race over prior authorizations and appeals. This dynamic, as outlined by digital health leaders such as Ashis Barad, serves as both a warning and a roadmap for stakeholders. Without deeper data collaboration and well-designed, patient-focused systems, AI risks perpetuating—if not compounding—the inefficiencies it was intended to solve. The industry’s next chapter could be shaped by those who find ways to foster trust, enable true interoperability, and redefine what cost-effective, high-value care looks like.

Source: MedCity News