In this episode

How can health systems looking to invest in AI move beyond buzzwords and create a meaningful strategy? Anika Gardenhire, RN, CHICO , Chief Digital Information Officer at Ardent Health, discusses strategic investment in AI and digital transformation in healthcare. She emphasizes the importance of applying AI to real-world problems rather than chasing hype cycles and ensuring practical implementation at scale. She said that to meaningfully invest in AI:

• AI investments must be strategic and purpose-driven, not follow the hype cycle.
• AI should enhance workflows, not create disruption.
• Leadership is critical in AI transformation.

“We need to be really honest about where AI technology is on the hype cycle. Is it super early? Do we actually understand it?  Or is it really well understood, but we didn’t have what we needed to roll it out at scale, and now we do?”

– Anika Gardenhire, RN, CHICO

 

Key takeaways

Gardenhire emphasized that by focusing on real-world applications, avoiding hype-driven investments, and ensuring scalable AI implementation, healthcare organizations can drive meaningful innovation and efficiency.

AI investments must be strategic and purpose-driven.

Gardenhire stressed that organizations should not adopt AI simply because it’s trending. Instead, they should ensure AI aligns with long-term goals and creates real, measurable value. Purpose-driven innovation leads to sustainable impact rather than short-term gains. She warns against falling for “shiny objects,” where companies chase the latest AI trends without clear use cases or defined outcomes. Instead, leaders should focus on AI solutions that address genuine business needs, improve efficiencies, and enhance patient or customer experiences.

AI should enhance workflows, not create disruption.

Rather than implementing AI for the sake of novelty, organizations should integrate it in ways that support existing processes and improve efficiencies. AI should solve real problems and streamline operations instead of adding unnecessary complexity. Gardenhire emphasized that automation and AI should free up time for employees to focus on higher-value tasks rather than creating additional layers of work.

“Design matters, and you’ve got to make it easy to use, and it shouldn’t be overcomplicated,” she said.  She warned organizations to be cautious of AI systems that overcomplicate workflows or require extensive retraining without clear benefits.

Leadership is critical in AI transformation.

Successful AI adoption requires leaders who grasp both the technological and human factors. “We’ve gotten great reviews around the work that we’ve been doing, when we apply novel technologies, but it’s not necessarily magic… it’s a partnership,” Gardenhire emphasized.

Leadership must guide teams through change and ensure AI adoption is meaningful. CIOs and other executives should foster a culture of innovation while also addressing employee concerns about AI, such as job displacement or skill gaps. Strong leadership ensures AI is implemented in a way that complements human expertise rather than replacing it.

Ethical AI implementation is a priority.

Organizations must be mindful of responsible AI use, ensuring transparency, fairness, and accountability in decision-making. Ethical considerations should be at the core of AI strategies to avoid bias and unintended consequences. Gardenhire highlights the importance of explainability in AI models, ensuring that decision-making processes are clear and understandable. She also stresses that AI should be deployed with equity in mind, avoiding biases that disproportionately affect certain groups.

“I hope that we’re going to take a step back in the broader lens of health equity and think to ourselves, ‘If we’re developing direct-to-consumer products, which populations are we missing by not thinking about how we apply our technology’?” she said.