Artificial intelligence is rapidly changing healthcare operations, including prior authorization (PA) processes. While the use of AI in prior authorization holds great promise for reducing administrative burdens and improving efficiency, there are several misconceptions about its role and impact on healthcare organizations and their communities.
Some fear AI will replace human decision-making, while others doubt its ability to enhance utilization management workflows. In reality, AI is a tool designed to support—not supplant—clinical expertise. For Managed Care Organizations (MCOs), understanding the nuanced role of AI in PA is critical for improving efficiency while maintaining high standards of care.
Let’s get the facts straight by debunking some of the most common myths about healthcare AI systems and consider AI’s path forward.
Myth #1: AI Replaces Clinical Judgment in Prior Authorization
One of the most pervasive myths is that AI-driven prior authorization software makes independent clinical decisions without human oversight. In reality, AI is used to streamline administrative processes and assist human reviewers, not to simply replace them.
- AI helps automate repetitive tasks, such as verifying patient eligibility and cross-referencing medical guidelines, reducing the workload for clinicians
- Clinical review remains a core component of utilization management workflows, ensuring that AI-driven recommendations are validated by licensed professionals
- AI enhances consistency by flagging cases that require deeper clinical evaluation, helping health plans allocate human resources more effectively
Despite AI’s ability to improve administrative efficiency, people still have concerns about its potential impact on clinical decision-making. AI can assist in determining prior authorization approvals, but it should never function as the final decision-maker. Regulatory efforts are increasing to ensure AI tools remain transparent and serve as clinical decision support rather than independent adjudicators.¹
By leveraging AI in prior authorization, MCOs can maintain a balance between efficiency and clinical integrity, ensuring that medical necessity remains at the forefront of every decision.
Myth #2: AI in Prior Authorization Leads to More Denials
Some stakeholders worry that AI increases denial rates by rigidly enforcing guidelines without considering patient-specific factors. When implemented correctly, AI can actually help reduce denials by:
- Identifying incomplete or inaccurate submissions before they are processed
- Providing real-time decision support to ensure documentation meets payer requirements
- Helping providers submit more accurate prior authorization requests upfront
Rather than exacerbating denial issues, AI-driven prior authorization software can reduce administrative friction and improve approval rates by making sure requests are complete and compliant from the start
There is growing concern over how AI is used by payers in ways that may limit care access. The American Medical Association (AMA) has called for stronger oversight of AI-driven prior authorization tools to ensure they do not lead to inappropriate denials.²
Myth #3: AI Creates a “Black Box” Decision-Making Process
Another common concern is that AI decision-making is opaque and difficult to challenge. While some AI models in healthcare have historically lacked transparency, modern healthcare AI systems prioritize explainability and auditability.
- AI-driven PA solutions generate clear, traceable decision pathways that allow human reviewers to understand and verify recommendations
- Many AI tools provide real-time feedback, letting providers see why a request may need additional information before submission
- Regulatory oversight is increasing to keep AI-driven prior authorization software transparent and accountable¹
Health plans that implement AI in a responsible, well-structured way can improve visibility into PA decisions rather than obscure them. In fact, recent research highlights the need for AI models to provide clear reasoning behind decisions to maintain accountability in clinical workflows. The study emphasizes that AI transparency not only aids healthcare professionals in understanding system outputs but also enhances trust and adoption among both providers and patients.3
Myth #4: AI Implementation Is Too Complex for MCOs
While AI adoption requires thoughtful integration, it does not have to be overly complex or disruptive. MCOs don’t need to build AI models from scratch. Instead, they can leverage existing prior authorization software solutions that integrate with existing utilization management workflows.
- AI technology can be implemented in phases, meaning MCOs can start with automation of administrative tasks before expanding to more advanced applications
- Many AI-powered healthcare AI systems work within existing infrastructure, minimizing the need for major system overhauls
- Technology-agnostic partners like Clearlink help MCOs select and implement the right AI solutions based on their specific needs
By adopting a strategic approach to AI, MCOs can improve prior authorization processes without causing significant operational disruption.
AI as a Tool for Smarter, More Efficient Prior Authorization
AI is not a replacement for clinical judgment, nor is it a one-size-fits-all solution. It’s a powerful tool that enhances prior authorization software by automating routine tasks, improving decision accuracy, and optimizing utilization management workflows. For MCOs, embracing AI with intention can encourage measurable improvements in administrative efficiency, provider collaboration, and patient access to care.
At Clearlink, we help health plans integrate AI responsibly so that it complements clinical expertise rather than replacing it. Whether through optimizing prior authorization workflows or streamlining appeals, our expertise in healthcare AI systems enables organizations to achieve sustainable improvements in cost, efficiency, and member outcomes.
Want to learn more about how Clearlink can help you make the most of AI and technology in prior authorization efforts? Contact us today to start the conversation.
Sources:
1. AI & Standards Aren’t Enough—Fixing Prior Authorization Will Require Something Else Entirely, Forbes
2. Oversight Needed for Payers’ Use of AI in Prior Authorization, American Medical Association
3. Could an Artificial Intelligence Approach to Prior Authorization Be More Human, JAMIA