When Cleveland Clinic appointed Ben Shahshahani, PhD, as chief AI officer in July 2024, the job description was still evolving across the healthcare industry, and so were expectations for what the role could realistically deliver.
Dr. Shahshahani joined the Cleveland Clinic in 2024 from SiriusXM and Pandora, where he served as senior vice president of science, machine learning and product analytics beginning in 2021. But after entering healthcare, he said the most striking lesson wasn’t about AI’s potential. It was about where the fastest value actually sits.
In a conversation with Becker’s, Dr. Shahshahani shared what surprised him most about AI in healthcare and what leaders should and shouldn’t expect from a chief AI officer in the first year.
Question: When you stepped into that chief AI role, what did you think would define success in the first year? And how did that change once you were actually in the position?
Dr. Ben Shahshahani: It’s a new role, and there wasn’t a clear, uniform definition of job responsibilities across healthcare organizations. We had to define that. At its core, it’s about developing a strategy and enabling implementation of AI technology in support of our mission.
What surprised me coming into healthcare was where the biggest opportunities were. There’s tremendous potential on the clinical side, but so much of the opportunity is in what you might call “mundane” areas: back office, revenue cycle management and documentation quality. I didn’t realize how much inefficiency exists in healthcare overall.
And in an industry where margins are low, removing friction is critical to sustaining operations and continuing to serve patients.
When I arrived, I came up with three pillars for this work. One is technology enablement. That means making sure the technology organization is AI-ready. There are foundational steps, like building out data platforms, developing team skills and bringing in tools that allow for internal innovation and partnerships.
The second pillar is process. How do you govern AI use? How do you apply oversight that balances innovation with responsible governance?
The third, which is still a work in progress, is literacy. Do we have enough AI literacy to help different employee groups understand what this technology means for them? In healthcare, the workforce is extremely diverse. It includes surgeons, physicians, nurses, administrative staff, cafeteria workers and many more. Everyone has questions about what AI means to them. We’ve started integrating AI topics into annual training, but there is much more to do, especially given how quickly the field evolves.
Q: From your seat, with all the friction healthcare has, what leadership skill did you feel like you had to develop the fastest once you became chief AI officer?
BS: A lot of it is relationships. You need to make sure stakeholders across the organization understand the technology and how it can help. You also have to build those internal connections.
It also extends externally. We’re not a technology company, so we need to build a foundation for internal innovation. But we also have to partner with other companies. Building that external network and aligning it with internal needs is key.
AI is a hot topic. We have around 80,000 employees, and people across the organization have ideas. The challenge is building a process where people feel heard while also ensuring top-down strategy aligns with bottom-up use cases.
Q: If a health system appoints a chief AI officer tomorrow, what should they not expect that role to solve in just one year?
BS: I don’t think there is a magic bullet. Don’t expect to walk in with a lot of technology, apply it, and suddenly everyone is happy and everything works.
It takes a lot of work to implement AI in a way that people will actually adopt. That’s especially true for tools aimed at doctors and nurses. Since AI is not perfect, there always has to be a human in the loop. In fact, we haven’t implemented any AI applications, especially clinical ones, that don’t involve a human being.
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