Academy Insights | The Readiness Gap: Why Health Systems Aren't Prepared for Agentic AI (Yet)
Despite the surge of investment in advanced AI across healthcare, most systems are surprisingly unprepared to safely deploy agentic AI—the autonomous, multi-step AI systems that can make decisions or take actions without human prompts. That's the key insight from a recent report in NEJM AI, conducted in partnership by THMA and Microsoft.
The promise of agentic AI is compelling, especially for things like triaging patients, managing schedules, or triggering clinical alerts autonomously. But the reality is, most health systems just aren’t set up to use these tools at scale yet. In fact, only about 4% have moved beyond pilots and actually embedded agentic AI into day-to-day workflows.
Why it matters: The reason most health systems aren’t ready for agentic AI isn’t about the tech itself. Health systems are generally capable of integrating predictive models and AI-assisted workflows into point solutions. But moving to systems capable of autonomous action with measurable operational or clinical impact requires foundational capabilities few organizations have built. This includes things like clear accountability frameworks, real-time performance monitoring, cross-functional governance, and robust ethical guardrails.
Key barriers to scale:
Governance and risk oversight aren't mature. Traditional technology governance relies on periodic review, but agentic AI demands continuous oversight, real-time monitoring, and clear escalation structures for AI-influenced decisions.
Workforce capability is both critical and challenging. Executives view workforce upskilling as essential, yet it's also their biggest implementation challenge. When 1 in 5 organizations are debating human-to-agent ratios, it’s a sign that staffing, trust, and capability — not the algorithms — are slowing things down.
Data and technology infrastructure lags behind expectations. Many health systems are still running onlegacy infrastructure that wasn’t built for real-time data or cloud-based AI. This makes scaling agentic AI hard.
360 Takeaway: Stop treating AI as a point solution. AI pilots won't move the needle unless they're embedded into enterprise strategy. with governance, infrastructure, and workforce planning as core components. Nearly half (47%) of health systems surveyed believe their AI transformation will be heavily reliant on core strategic partnerships like Epic, Microsoft, or Google. With so much AI progress depending on major platform partners, aligning strategy with those partners has become a make-or-break issue.