Modernizing back-office operations
Back-office operations are among the earliest and most common areas of focus for agentic AI transformation. Insights from our focus group discussions (figure 3) show how agentic AI can reshape back-office functions from manual and episodic activities to more autonomous, continuous resolutions.
As one health plan executive from our focus group discussions mentioned: “Agentic AI monitors expiring licenses, verifies credentials against authoritative sources, proactively updates payer databases, and escalates exceptions for human review only when needed. This leads to a shift from static forms to intelligent orchestration, manual checklists to automated verification, and chronic bottlenecks to proactive, self-correcting systems.”
Key outcomes of transforming back-office operations with agentic AI could include fewer manual handoffs between systems, faster process cycle times, and more robust and resilient operations. Together, these improvements can help enable autonomous follow-through, end-to-end orchestration across systems, and the redeployment of staff to higher-skill work.
For example, Mayo Clinic is deploying and exploring AI agent approaches to streamline provider and payer administrative workflows. These efforts support processes such as eligibility and benefit verification, prior authorization and utilization management, claims-related clinical information exchange, and prescription support.7
Transforming payment processes
Payment process modernization is a priority area for transformation because payment workflows are inherently complex and multistep—exactly the type of challenge agentic AI is designed to address, according to focus group leaders. Whereas traditional AI is largely focused on analysis rather than decision-making, agentic AI can support and eventually execute sophisticated end-to-end sequences of actions.8 This capability enables a shift from manual, potentially error-prone claims processing and reactive corrections to proactive, zero-touch adjudication with built-in denial prevention.
Agentic AI can help reduce error rates and resolve issues faster by enabling real-time problem-solving and proactive claims management. In turn, it can reduce denial rates, accelerate and optimize provider reimbursement, lower days in accounts receivable, and improve both member and staff satisfaction by shifting effort to higher-value work. As one health system tech executive who participated in the focus group discussions said, “Agentic AI can validate codes against payer rules in real time, auto-correct errors, and communicate with payers directly, thereby reducing denials, accelerating claim resolution, and freeing staff to focus on complex cases.”
An example is MUSC Health deploying AI agents to complete 40% of prior authorizations without human involvement, which has helped MUSC significantly reduce manual work.9
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