Key Takeaways 

• Artificial intelligence (AI) is becoming an operational infrastructure in managed care pharmacy. Emerging evidence suggests AI may play a growing role in prior authorization (PA), utilization review, and workflow optimization, helping plans improve efficiency while preserving clinical oversight.
• Standardized real-world evidence (RWE) is strengthening payer confidence in coverage decisions. Newly developed Academy of Managed Care Pharmacy (AMCP) RWE standards aim to create consistent frameworks for evaluating real-world data, supporting more transparent and methodologically sound formulary and reimbursement determinations.
• AI-enabled RWE is advancing value-based reimbursement strategies. By enhancing the ability to measure real-world outcomes at scale, advanced analytics are supporting performance-linked contracting models and more data-driven pharmacy benefit management.

As pharmacy benefit management grows more complex, managed care organizations are increasingly relying on advanced analytical tools and RWE to guide coverage decisions, streamline utilization management, and support value-based reimbursement strategies. With specialty therapies commanding rising spend and policy shifts affecting patient access and affordability, the integration of AI and RWE is gaining traction among payers and their partners as a strategic imperative.

Stakeholders currently view these innovations not as emerging curiosities, but as core components of next-generation managed care strategy—a key theme anticipated to surface in discussions at major industry gatherings, including the Pharmaceutical Care Management Association (PCMA) 2026 Business Forum.

AI’s Growing Role in Operational Efficiency

A foundational trend expected to influence benefit design and utilization strategy is the expanding use of AI within managed care operations—particularly for PA and administrative workflows. According to a mixed-method study in the Journal of Managed Care & Specialty Pharmacy, experts predict that AI will become increasingly embedded across managed care pharmacy, driven by its potential to improve efficiency and support decision-making in areas such as utilization review and workflow automation.¹

Although core clinical judgment will still be essential, AI-enabled tools can ingest and interpret large volumes of clinical and claims data to identify patterns, predict future utilization trends, and automate labor-intensive processes such as PA. This allows clinical and pharmacy staff to devote more time to high-value tasks, enhancing operational performance without sacrificing accuracy.

Real-World Evidence Anchors Coverage Decisions

While randomized clinical trials remain the standard for regulatory approval, they often lack the breadth of outcomes observed in routine clinical practice. Managed care decision-makers are turning to RWE—evidence derived from real-world data sources such as claims, electronic health records, and registries—to fill that gap and inform coverage and reimbursement decisions with actionable insights.

The Academy of Managed Care Pharmacy (AMCP) Research Institute’s initiative to develop payer-focused RWE standards underscores the importance of structured, credible real-world evidence in decision-making. Published in JMCP, this work involved payers, pharmaceutical representatives, and research experts in crafting a framework that defines study types, endpoints, and assessment criteria tailored to payer needs, facilitating more consistent interpretation and application of RWE in coverage and formulary deliberations.²

Supporting Strategic Value-Based Contracting

The convergence of AI and RWE also plays a key role in value-based contracting (VBC), where reimbursement is linked to real-world performance outcomes rather than volume-based metrics. As health plans and pharmaceutical manufacturers explore risk-sharing arrangements tied to outcomes—such as adherence, hospitalization rates, or total cost of care—the ability to reliably measure these endpoints becomes essential.

AI enhances the scalability of RWE generation by enabling rapid analysis of large clinical and claims datasets, while payer-aligned RWE criteria help ensure that the evidence used in contracts meets expectations for relevance and rigor. Together, these tools help payers implement and evaluate VBC arrangements more confidently, aligning payment with value across patient populations.

From Evidence to Policy and Practice

Despite their promise, operationalizing AI and RWE requires careful attention to governance, transparency, and methodological consistency. Managed care organizations must balance innovation with accountability, ensuring that models are interpretable, bias is mitigated, and evidence is communicated clearly across stakeholders.

Supporting this shift, industry research continues to reinforce the role of RWE and analytics in managed care pharmacy’s future. A supplemental JMCP study on emerging trends highlights that advancements in generative AI and data-driven tools—alongside evolving drug pipelines and payment models—are among the most influential forces shaping the field over the next 5 years.³

Conclusion

As managed care pharmacy navigates a changing policy, clinical, and economic landscape, AI and RWE are emerging as essential enablers of smarter, more agile benefit design and utilization strategies. From increasing administrative efficiency to strengthening coverage confidence and supporting innovative contracting models, these tools offer payers and pharmacy benefit managers opportunities to improve outcomes while managing cost and complexity.

Given their strategic significance, AI and RWE are projected to be focal topics of discussion at PCMA 2026—reflecting broader industry momentum toward data-driven, value-oriented pharmacy benefit decision-making.

References

1. Mattingly II TJ, Happe LE, Cranston L. Emerging trends in managed care pharmacy: a mixed-method study. J Manag Care Spec Pharm. 2025;31(1-b): S2-S10. doi:10.18553/jmcp.2025.31.2-a.s2 
2. Lockhart C, Powers E, Sweet B, Gleason P, Brixner D. AMCP real-world evidence standards: overcoming barriers to using real-world evidence in US payer decision-making. J Manag Care Spec Pharm. 2025;31(12): 1230-1236. doi:10.18553/jmcp.2025.25108 
3. Sweet BT. Real-world evidence: a new era is upon us. J Manag Care Spec Pharm. 2025;31(2): 225-230. doi:10.18553/jmcp.2025.31.2.225