The era of the healthcare AI chief executive is here. CAIOs are starting to appear in gigantic hospitals and health systems, the latest development as more providers devote resources and create strategic leadership roles to implementing AI across the enterprise, rather than relying on siloed IT departments or fragmented, ad hoc projects.
A recent study by global consulting firm Berkeley Research Group found that three-quarters of healthcare providers and pharmaceutical professionals expect AI to be widely adopted within the next three years – even though only about 40% have reviewed or plan to review regulatory guidance on AI.
While there is great optimism about the potential benefits of AI, such as improved diagnostics and reduced administrative burdens, concerns about data privacy, cybersecurity and the need for regulatory safeguards remain high in the industry.
Tom O’Neil is a managing director at BRG and knows some of the first AI executives in healthcare. He has extensive experience in the private and public sectors, and has led boards and C-suites in consumer, financial services, and healthcare. We asked O’Neil to describe what boards and C-suites should consider when including AI roles in healthcare systems.
Q. Why do you think hospitals and health systems should have a chief artificial intelligence officer or similar position?
AND. AI in healthcare presents many opportunities and challenges for life sciences companies, healthcare providers, and payers in the healthcare ecosystem. It’s no wonder that an emerging industry best practice is the appointment of a Chief AI Officer.
This role is becoming increasingly critical in the context of implementing organizational approaches that integrate AI into clinical processes, reducing physician burden, improving the quality of patient care, establishing accountability, and providing a powerful governance body for the successful implementation of AI in healthcare.
BRGs AI and the Future of Healthcare Report published earlier this year found that current models of IT and security governance for industry professionals are inadequate to manage AI development and deployment, and that IT cannot assume exclusive oversight of AI. Given the elaborate ethical and regulatory landscape surrounding AI, through effective collaboration, an AI chief executive can provide the necessary leadership and experience to aid navigate regulations and mitigate potential risks.
Q. What should a Chief AI Officer do?
AND. The Chief AI Officer provides long-term strategic vision and alignment for the organization. In addition to implementing AI projects, CAIOs also consider broader AI implications, such as changes in operations and culture. The CAIO ensures that AI systems are developed and implemented in an ethical, clear, and accountable manner.
To this end, CAIO oversees data privacy, reducing algorithmic biases and the responsible exploit of AI, protecting patient trust and maintaining the highest standards of care.
Dennis Chornenky, chief artificial intelligence officer at UC Davis Health and former general manager of the Optum business at UnitedHealth Group, says CAIO’s primary mission is to accelerate the adoption of AI capabilities while balancing security with innovation.
Q. Who should the Chief AI Officer report to and why?
AND. The brief answer is that it depends on the size and maturity level of the organization, as well as the level of resources allocated to AI within the organization.
Ideally, an AI director will report to a leader in the C-suite to implement changes that will implement a successful AI program within the organization. AI directors will most likely report to the CIO or CIO, but they may also report to the COO, CFO, CMO, or even CEO.
Q. Why should provider organizations decide whether to implement this role, and how will they engage with AI CoEs?
AND. Provider organizations should consider implementing this role as a CAIO would create accountable leadership with the expertise and strategic acumen to appropriately and timely prioritize workstreams, improve quality of care using clinical AI tools, and ultimately ensure the organization is able to compete effectively in the marketplace given the increasing criticality of AI in the healthcare industry.
Once appointed, CAIOs should establish and manage AI Centers of Excellence. These are specialized organizational units tasked with implementing AI, with significant financial resources and the skills and experience necessary to successfully implement AI.
Successful AI centers of excellence don’t just reside in an organization’s IT department. AI projects that impact clinical practice and patient care should include collaboration between individuals with expertise in technology, quality of care, legal and regulatory compliance, and business ethics.
The organization should create a multidisciplinary team with diverse socioeconomic backgrounds, including a passionate chief medical officer, operational experts, technology specialists, and legal/compliance reviewers.