The 2026 AMCP annual conference brought together more than 4,000 managed care pharmacy professionals, offering a unique lens into the challenges and priorities that are top-of-mind for payers and pharmacy benefit managers (PBMs).
It was clear that health plans and PBMs are actively reexamining jobs to be done, not just what tools they buy, to address a number of pressing needs.
Throughout the conference, evidence and data were central to the momentum shaping new and improved workflows. Rather than dwelling on high-level theory, discussions drilled into actionable strategies to help payers respond to the convergence of care complexity, cost pressures, and accountability requirements.
Five key topics came up repeatedly:
- AI
- Analytics and real-world evidence
- Data governance
- Interoperability
- Clinical complexity of care (particularly as it relates to specialty drugs)
Throughout discussions, these five keystones went hand-in-hand in various combinations, as payers sought ways to leverage the overlapping potential in all of them.
1. AI isn’t the headline anymore: On to the next phase of governance and trust
Last year was all about exploring how to apply AI beyond the call center and chatbots.
This year, payers were past the novelty and excitement of new AI-enabled solutions and instead focused on understanding and uncovering the efficiencies, insights, and scalability that AI is supposed to unlock.
Many payers and PBMs are farther along on the technology curve than other stakeholders in the healthcare ecosystem. In an instant poll on AI maturity taken at the AI preconference, well over 70% of audience members rated themselves in the middle ranges of AI usage — beyond basic “help me write my emails” tasks. They are more seriously exploring ways to use AI in concert with data and analytics to drive activities like prior authorization and utilization management.
But payers need more than efficiency from their AI-powered solutions. They are being asked to explain how decisions are made. This requires prioritizing technologies built on transparent logic and rigorously reviewed clinical and medication knowledge, rather than relying on black-box or one-off AI implementations that are hard to defend.