Health Systems Must Prepare Now for AI Transformation, Says Children's Minnesota CIO
Dave Lundal, chief information officer at Children's Minnesota in Minneapolis, sees artificial intelligence as the third major era in healthcare IT-one that will dwarf the impact of hospital information systems and electronic health records combined.
Unlike previous waves of technology adoption, AI development moves too fast for traditional implementation roadmaps. Strategy can shift in months, not years.
"We have an EHR implementation underway right now," Lundal said. "This is a large and difficult project. Fundamentally, though, it is an execution issue. The path has been paved. AI is different."
The Speed Problem
Health IT leaders already juggle financial strain, staffing shortages, and regulatory complexity. AI sits above all of it as the dominant concern.
The unprecedented pace of development forces organizations to rethink infrastructure and long-term strategy. Today's cutting-edge capability may be outdated within a quarter. Tomorrow's breakthrough could arrive just as quickly.
"AI represents a vast problem to solve," Lundal said. "How do we bring this powerful technology into what we do every day?"
Three Concrete Steps
Build flexible infrastructure. Children's Minnesota is moving its data warehouse to the cloud-foundational work that allows the organization to adapt as AI capabilities mature.
Use AI to understand it. Lundal said executives and IT leaders cannot lead effectively through AI adoption without hands-on experience. He spends significant time with books, podcasts, and peer organizations to understand where the technology is headed.
"Using the technology is critical to understanding it," he said. "How can we guide and strategize if we don't understand it?"
Establish vision and governance now. A clear organizational vision provides direction in rapid change. Governance structures protect against moving too quickly without safeguards.
Defining Responsible AI
Many health systems are adopting "responsible AI" frameworks, though definitions vary. Common elements include ethical deployment, safety, inclusivity, equity, and regulatory compliance.
Without clear governance, organizations risk outcomes they didn't intend. Lundal said the time to set conditions for desired results is now, not after problems emerge.
"We must decide now how we set the conditions to ensure the outcomes we desire are what we get," he said.
Healthcare leaders tasked with implementing AI strategy should consider developing a structured approach to governance and infrastructure. AI Learning Path for CIOs offers guidance specific to information officers navigating organizational change, while AI for Healthcare covers sector-specific implementation considerations.
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