As the healthcare industry faces growing patient demand, artificial intelligence (AI) and automation are giving hospitals and health systems the opportunity to rethink how they deliver care. However, many organizations struggle with where and how to deploy these technologies.
“AI is not a hammer looking for a nail,” emphasized Dave Henriksen, Head of Value Based Care at Notable. “Organizations have problems…they need to understand how AI can help them solve their core problems.” Drawing from their experience implementing AI across leading health systems, Henriksen and Notable’s Chief Medical Officer, Aaron Neinstein, MD, shared seven tips to help your organization navigate an enterprise-wide AI strategy.
1. Define your north star
“Don’t go into AI for the sake of using AI,” Neinstein said. A healthcare organization’s AI strategy must align with its mission and long-term vision. You need a firm vision of where you want to go as an institution.
Bill Gates framed the opportunity clearly: with AI’s productivity gains, organizations can “increase the quantity of output, improve the quality of output or reduce the human labor hours that go in.” While you’ll likely see improvements across all three, determining your primary goal is crucial. Are you trying to expand access to care? Improve quality outcomes? Reduce provider burnout? Your AI strategy should accelerate progress toward these goals, not distract from them.
2. Establish clear business objectives
Move beyond the hype around using AI by defining specific, measurable goals. AI projects are more likely to fail when they start with technology instead of business problems. Whether you’re focusing on operational efficiency, patient access or quality metrics, your organization’s leaders must define what success looks like. Start with the workflow you want to improve, then determine how AI can help.
Neinstein shared a cautionary tale from a large university-affiliated health system. Because its leaders focused on implementing a specific technology rather than on articulating the business problem they wanted to solve, the health system’s initial deployment of a no-show prediction algorithm led to overbooking and did not improve outcomes.
3. Develop guiding principles
Don’t start your AI project from scratch; instead, build upon your existing privacy, security and compliance frameworks while adding AI-specific considerations. Henriksen emphasized, “Stay focused on how the patient experiences care while providing that care at a lower cost with higher quality.”
Healthcare organizations already have strong foundations in IT governance, privacy, security and user experience. While AI brings new considerations, you don’t need to reinvent the wheel. Instead, layer guidelines for the AI tool into your existing frameworks, focusing on:
● Patient experience and care quality
● Caregiver support and efficiency
● Clear rules for AI’s use in clinical settings
● Data governance and security
● Integration requirements
4. Invest in change management to drive adoption
Successful AI deployment isn’t just a technical challenge; it requires buy-in across your organization. Instead of avoiding concerns related to AI implementation, successful organizations address such concerns directly through education, storytelling and frontline engagement.
During his time at Intermountain Health, Henriksen shared that leaders would connect with employees after integrating new tools to ask what was working and what wasn’t. Many of their suggestions came from consumer experiences outside of their work in healthcare. “Through AI, we can enable those suggestions,” he explained.
The key to ensuring acceptance and use of AI tools is making staff part of the process rather than simply recipients of change. This approach isn’t unique to AI; similar strategies were used when healthcare organizations first moved from paper to electronic health records. That experience demonstrated that such an approach is essential for building trust and adoption.
5. Achieve early wins to accelerate your strategy
Rather than getting stuck in analysis paralysis, successful organizations identify focused opportunities for quick wins that build staff confidence and momentum. “Think big, start small and move fast,” Neinstein advised.
At Intermountain Healthcare, small tests of change with a subset of users proved powerful. When staff members could tell colleagues that new tools had saved them considerable time, adoption accelerated naturally. These early advocates become crucial for winning over more skeptical team members.
Leaders should remember that all the planning in the world can’t replace practical experience. One Notable partner reduced its prior authorization times from days to minutes, receiving answers while patients waited in the office. This is exactly the kind of concrete win that transforms skeptics into believers.
6. Create a strategic plan for workforce transformation
AI will change how healthcare workers do their jobs; there’s no avoiding this reality. However, successful organizations will approach this proactively and transparently, focusing on how AI can enhance, rather than replace, human work.
Consider the front desk role; by automating collection tasks, AI can free staff to focus on what matters most: patient interaction. “Stop telling front-desk staff to be good at patient experience if you’re also asking them to be payment collectors,” Henriksen advised.
Don’t let your AI strategy become a “third rail” that everyone fears discussing. Instead, involve your workforce in planning how their roles will evolve. The Medical University of South Carolina exemplifies this with its ten-year strategic plan, preparing employees for tomorrow’s opportunities rather than leaving them anxious about change.
7. Form long-lasting platform partnerships
Who you partner with matters more than what specific products you buy. “You’re not just buying today’s product — you’re buying the company and partnership,” Neinstein pointed out.
Avoid the temptation to rely solely on your electronic health record (EHR) vendor or to accumulate dozens of point solutions. EHRs are your foundation, the “load-bearing walls” of hospital operations, but transformation requires partners who can move more nimbly while maintaining enterprise-grade reliability.
Look for configurable platforms that can solve multiple problems while growing with your organization. The right partners will help you navigate AI’s rapid evolution while maintaining focus on your core mission: delivering exceptional patient care.
What’s next?
The organizations that will thrive in 2025 aren’t necessarily those with the biggest AI budgets or the most advanced technology. Success will come to those who approach AI strategically, align it with their mission and focus on solving real problems for their patients and staff.
