Healthcare payers are under pressure: rising medical costs, tighter regulatory scrutiny, and members who expect a better, personalized experience. In that environment, AI is often framed as a way to remove layers of work and, with it, layers of people. My experience points the other way: payers that use AI to empower their middle management make the most progress.
Simply put, AI will re-empower the middle. Managers, analysts, and clinicians who’ve long been buried under administrative load will become AI conductors supervising digital co-workers – orchestrating agents, curating context, and elevating human judgment.
We now have ample proof that agentification can handle the bulk of claims adjudication, prior authorizations, and other deterministic decisions; I routinely see that leveraging AI can address 90–95% of this volume. The real question is what we do with the remaining 5–10% of cases where context, ambiguity, or ethics drive the outcome.
The smart move is to empower the middle layer of the organization with insight-driven agents, putting them in charge of the system to design and accelerate next-generation products and services.
Success in this next phase of AI will hinge on a few operational basics:
- Organizations need trustworthy deployment at scale, with production rollouts that run real workloads and deliver measurable outcomes—not endless pilots.
- Teams should have explainability so they can see why an agent took an action and what data drove it.
- Data lineage must be clear, with a full audit trail from source to decision.
- Agentic systems require governance, with guardrails for autonomy, defined escalation paths, and safe rollback.
- Compliance needs to keep pace by embedding controls into the workflow, so the AI is effectively invisible to end users and regulators.
How AI will redefine the roles of middle management in 2026
As AI takes on routine, rule-bound work, advantage will shift to how payers design, govern, and oversee the remaining decisions that require judgment. That shift will elevate the people who curate inputs, set thresholds, review edge cases, and override when necessary. Middle management should be accountable for how agents work together, how decisions are explained, and how exceptions are escalated. At the same time, new functions must be created to ensure payer intent is translated into safe, auditable automation. In 2026, these newly defined roles will carry that responsibility and create most of the measurable impact:
Roles that rise:
- Managers will become orchestrators: As agents automate most routine work, advantage will come from how the remaining edge cases are handled, and scale and consistency will depend on human judgment. Managers will configure agent teams, set escalation rules, review pattern-level performance, and coach on exceptions. When signals conflict, they will make the final call and update the orchestration, so similar cases resolve automatically next time.
- Analysts design the agentic logic and guard it: Payers will need custodians of evidence, thresholds, and auditability to keep automation compliant and effective. Trustworthy automation at scale will require accuracy, fairness, and continuous tuning. Empowered analysts will translate policies into rules and thresholds, validate accuracy against holdout data and real feedback, and monitor for bias and drift. They will instrument dashboards to reveal skew and adjust the logic accordingly. This is why they rise.
- Clinicians curate clinical policy inside automation: Automation will only scale when clinicians define boundaries that protect member outcomes and uphold standards of care. Clinical quality and safety will determine what can be automated and what must be reviewed. Clinicians will decide what’s auto-approved and what’s escalated, set the clinical quality bar, and audit and update criteria as medical evidence evolves.
Roles that will emerge:
- AI Interpreters will bridge the policy-to-automation gap: AI interpreters will translate payer policy into machine-executable logic, turning nuanced reimbursement guidelines into structured rules, tests, and exception paths without losing intent.
- Agentic process designers will create safe, scalable workflows: Agentic process designers will build trustworthy workflows, defining edge-case triggers, separation of duties, and controls so agents handle most cases while escalations are resolved quickly.
- AI ethicists will embed transparency across operations: AI ethicists will become a part of core operational functions to review models and clinical workflows for fairness, consent, transparency, and harm prevention, keeping member engagement and clinical operations aligned with policy and societal expectations.
Because agentification spans policy, operations, and technology, payers will need new roles to turn intent into execution and ensure safe, auditable delivery. In the coming years, we’ll see that the winning healthcare organizations won’t have eliminated their middle. They’ll have liberated it. And that liberation is where the real value emerges, not necessarily from the AI itself, but from the humans orchestrating it.
