AI and cost pressures expose a readiness gap-and a new healthcare C-suite

Health system leaders admit they're underprepared for AI and rising costs. The new playbook centers on AI-savvy roles, payer strategy, clean data, and ROI-focused execution.

Healthcare C-suites say they're underprepared for AI and cost pressure

Healthcare executives are looking at a future that will not reward old playbooks. A new report from the Healthcare Financial Management Association (HFMA) says leaders feel underprepared for challenges spanning AI deployment, payer dynamics, and cost containment. The message is direct: strategic, visionary leadership is now a requirement, not a luxury.

"My takeaway is there is strong self-awareness among C-suite leaders of where there is weakness, and that's driving much closer collaboration and interesting partnerships at the executive level," said Brad Dennison, HFMA vice president of content. "These leaders are learning they have to work together in ways that weren't necessary before."

The roles that matter next

Survey respondents ranked the most important emerging roles for the C-suite. Note the clear tilt toward AI, data, and revenue rigor.

Chief AI Innovation Officer (most important new role)
Chief AI Officer
Chief Information/Technology Officer
Chief Financial Officer
Chief Revenue Officer
Chief Executive Officer

Executives describe the future C-suite as interconnected, innovative, data-driven, and AI-savvy. That mix reflects both offensive and defensive priorities: build new capabilities while protecting margin.

Priority skill sets for the next 24 months

Top three for the full C-suite: innovation/technology, payer relations, digital technology
For CFOs (in order): innovation and transformation, payer relations, digital technology, AI competency, risk assessment

Dan Liljenquist, senior vice president and chief strategy officer at Intermountain Health, put it bluntly: "This is what it feels like when the model starts breaking down. The financial pressures are mounting, and reality is not negotiable."

What this means for strategy and finance leaders

AI is moving from pilots to production, and cost discipline is moving from incremental to structural. The organizations that win will pair AI-driven productivity with payer and revenue strategy, while rebuilding the operating model around data.

Practical moves to put on your 2026 plan

Stand up formal AI leadership: Appoint a Chief AI Innovation Officer or equivalent with clear remit, budget, and cross-functional governance.
Tie AI to ROI, not demos: Prioritize use cases in revenue cycle, denials, capacity management, and clinical documentation. Kill proof-of-concepts that don't show financial lift in 90-120 days.
Upgrade payer relations muscle: Build joint AI workstreams with payers around authorization, risk adjustment, and quality measures to shorten cycle times and reduce friction.
Fix the data plumbing: Fund data engineering and quality as a shared service. No reliable AI without clean, accessible data.
Institutionalize AI risk management: Adopt a lightweight model governance framework covering bias, safety, security, and audit trails. Consider guidance like the NIST AI RMF.
Re-skill finance and ops: Train CFO and revenue teams on prompt design, model limits, and automation handoffs. Make AI literacy part of performance plans.
Redesign cost structure: Pair automation with service-line rationalization, site-of-care shifts, and vendor consolidation. Capture savings in-year.
Make metrics unambiguous: Track cash acceleration, cost-to-collect, authorization turnaround, and throughput. Publish weekly scorecards.
Form partnerships with intent: Co-develop with health systems, payers, and tech firms where you lack depth. Structure deals around shared outcomes.

Why urgency is warranted

The HFMA survey signals a C-suite that knows where it's strong and where it's exposed. Leaders say the goal is a system focused on personalized care-and they know there's no time to waste. The report had support from healthcare services firm Healthrise.