Using AI to improve prior authorization does not have to be a fragmented black box. Learn how health plans are using NCQA's Learning Collaborative and Comparative Evaluation to apply responsible artificial intelligence to prior authorization workflows, generate real operational results, and improve experiences for providers and members.

Key Takeaways:

• Prior authorization represents a high‑impact opportunity for responsible artificial intelligence. However, without clear direction on where to start, who to partner with, or how to scale, AI implementations can quickly become fragmented, opaque, or misaligned with their intended goals and impact potential.
• NCQA has launched a Comparative Evaluation and Learning Collaborative, which delivers a cohort-based maturity model, supported by a library of best practices and a structured evaluation. This collaborative provides organizations with expert guidance, peer insights, and a clear path to align with emerging best practices and accelerate quality improvement through responsible AI adoption.
• Structured, peer‑based learning collaboratives provide the foundation for sustainable artificial intelligence adoption in healthcare by combining shared evidence, expert guidance, and comparative insight enabling organizations to move from prior authorization to other high‑impact use cases with confidence.