AI Integration Demands Strategic Rethinking of Labor and Leadership, Says Monument Health CIO

Monument Health, a regional system serving five states in the Upper Midwest, is navigating AI with a deliberate strategy grounded in community care and clinical realities. At the center of that effort is Patrick Woodard, MD, Chief Information Officer, who believes AI is not merely an enhancement of existing tools, but an opportunity to fundamentally rethink healthcare labor and leadership.

Based in western South Dakota, Monument Health provides the only major health services for many communities across five states, from eastern Wyoming to western Nebraska. For Woodard, the stakes are clear: getting digital transformation right can make the difference between care and crisis.



“We’re the only one in the region,” he said. “If you aren’t coming here, you’ve got to go six hours out of your way. For some people, that might mean a life-or-death scenario.”

From Digitization to Transformation

Health systems, Woodard argued, have long focused on digitizing processes—often simply moving paper-based tasks into electronic workflows. The rise of AI, and in particular the availability of large language models (LLMs), invites a different type of leadership.



“I think now there’s an opportunity for us to move away from this digitization mode and into a transformation mode,” he said. “That really requires us to ask the question: do we really need this at all?”

By his estimation, much of a clinician’s time is consumed by low-value or redundant tasks, often driven by billing or compliance needs. Rather than finding someone else to perform those duties, Woodard sees a new model emerging—one where they are automated entirely, or eliminated.

This shift redefines the conversation around “working at the top of one’s license,” a phrase Woodard believes has become nearly meaningless without the structural ability to reduce unnecessary labor.

Strategic Use of AI Tools

The conversation around AI in healthcare tends to be dominated by high-visibility use cases such as ambient documentation tools. While these tools offer immediate and meaningful benefits—physicians can spend more time with patients and less time on paperwork—they do not yet fundamentally change the labor equation. “You still need a doctor in the room,” Woodard said.

The next frontier, he argued, lies in exploring how different AI tools—whether predictive models or generative agents—can be strategically deployed across various aspects of care delivery and operations. That requires IT leaders to stop viewing AI as a single tool and instead approach it as a diverse and evolving toolbox.

“If you think of AI as a tool chest, and there is a screwdriver and there is a hammer,” he said. “There’s no such thing as the AI. There are many different AIs out there.”

That diversity, however, also introduces complexity. Integration challenges will multiply as health systems expand their AI footprints. Ensuring that technologies align with strategic objectives—and deliver value to individuals, not just institutions—will be critical to long-term success.

Frontline Alignment and Governance

Woodard’s approach to implementation is grounded in frontline observation and end-user value. At Monument Health, initiatives that demonstrate clear and immediate value tend to succeed—particularly when users can see direct improvements to their day-to-day responsibilities.

“Our ambient solution sold itself,” he said. “It truly did because it’s an immediate value to the clinicians who are using it.”

By contrast, tools that serve administrative or financial objectives often face resistance unless they’re carefully mapped to personal benefits. That reality underlines the importance of storytelling in IT strategy—explaining not just what a tool does, but why it matters to the nurse, doctor, or staff member using it.

Governance also plays a central role. Upon arriving at Monument Health,