New AI Adoption Roadmap Guides Managed Care Firms
The framework helps organizations transition from initial AI pilot programs to full operational scaling.
Updated on Oct. 28, 2026 in Artificial Intelligence
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Managed care leaders presented research at the AMCP Nexus 2026 meeting in San Diego detailing a roadmap for artificial intelligence integration. The framework outlines a three-phase progression for organizations to move from initial piloting to full optimization.
Why it matters
Managed care organizations face significant hurdles in adopting AI, particularly regarding governance and ethical deployment. Establishing a structured playbook enables firms to systematically reduce administrative burdens while ensuring regulatory compliance.
The framework identifies three distinct stages of institutional AI maturity: piloting, scaling, and optimization. Most managed care organizations currently reside in the piloting phase, while firms like Cencora have progressed to scaling.
The players
Leanna Baker
An industry researcher who presented on managed care AI adoption frameworks.
Cencora
A pharmaceutical services company currently in the scaling phase of AI adoption.
The details
The adoption model requires organizations to establish rigorous governance, ethics, and key performance indicators before deploying tools. This structure is intended to manage applications including prior authorization and drug utilization review. By starting with simpler, low-risk tools, institutions create an infrastructure that supports the later, more complex scaling and optimization phases.
Timeline
October 27, 2026: Leanna Baker presented the AI adoption playbook research.
The Tech Race
This framework moves beyond conceptual AI adoption to address the practical governance required for large-scale healthcare operations. It signals a shift from speculative tool development toward the industry-wide standardization of AI workflows.
Healthcare administrators and managed care staff will see increasingly structured implementations of AI in workflows like prior authorization. While these systems aim to reduce administrative bloat, their efficacy remains tied to the specific governance models each organization chooses to implement.
The takeaway
Organizations looking to mature their AI capabilities should prioritize defined success criteria over rapid technology deployment. Observers should track which managed care firms successfully transition from Cencora-style scaling to full workflow optimization in the coming year.
Further reading
Learn more about evolving standards in our Artificial Intelligence section.
Source note: This article includes information reported by Ajmc.
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Do you trust that integrating artificial intelligence into managed care will improve your healthcare experience?
