The age of the healthcare chief AI officer has arrived. CAIOs are beginning to appear at major hospitals and health systems – the latest development as more and more providers devote resources and create strategic leadership roles for enterprise-wide adoption of artificial intelligence, rather than relying on siloed IT departments or scattered, ad hoc projects.

A recent survey from global consulting firm Berkeley Research Group found that three-quarters of healthcare providers and pharmaceutical professionals expect widespread AI adoption in the next three years – even as only about 40% have reviewed or plan to review AI regulatory guidance.

While optimism about AI's potential benefits, such as improving diagnostics and reducing administrative burdens, is high, concerns about data privacy, cybersecurity and the need for regulatory guardrails remain significant among industry stakeholders.

Tom O'Neil is managing director at BRG and knows some of the first chief AI officers in healthcare. He has extensive private and public sector experience and has led in boardrooms and C-suites across the consumer, financial services and healthcare sectors. We asked O'Neil to describe what boards and C-suites should consider when incorporating AI-dedicated roles into health systems.

Q. Why do you believe hospitals and health systems should have a chief AI officer, or similar title?

A. AI in the healthcare field presents many opportunities as well as challenges for life sciences firms, healthcare providers and payers in the healthcare ecosystem. Not surprisingly, an evolving best practice in the industry is the designation of a chief AI officer.

The role has become increasingly important in leading organizational approaches that integrate AI into clinical workflows, reducing burdens on physicians, improving quality of care for patients, establishing accountability, and ensuring a strong governing body for a successful implementation of AI in healthcare.

BRG's AI and the Future of Healthcare report released earlier this year found that industry professionals' current IT and security governance models are inadequate to manage AI development and deployment, and that IT cannot take on the sole oversight of AI. Given the complex ethical and regulatory landscape surrounding AI, through effective collaboration, a chief AI officer can provide the necessary leadership and experience to help navigate regulations and mitigate potential risks.

Q. What should a chief AI officer do?

A. A chief AI officer provides a long-term strategic vision and alignment for organizations. In addition to the implementation of AI projects, CAIOs also consider the broader implications of AI, such as changes to operations and culture. The CAIO ensures that AI systems are developed and deployed ethically, transparently and responsibly.

To do so, the CAIO oversees data privacy, algorithmic bias mitigation and the responsible use of AI, safeguarding patient trust and upholding the highest standards of care.

Dennis Chornenky, chief AI adviser at UC Davis Health and former CAIO for UnitedHealth Group's Optum business, says the primary responsibility of the CAIO is to accelerate the adoption of AI capabilities while ensuring a balance between safety and innovation.

Q. Who should a chief AI officer report to, and why?

A. The short answer is that it depends on the size and maturity level of the organization and the level of resources allocated to AI within the organization.

Ideally, a chief AI officer will report to a leader in the C-suite in order to bring about changes that will implement a successful AI program in the organization. Most likely, chief AI officers would report to the CIO or chief digital officer, but they could also report to the COO, CFO, CMO or even the CEO.

Q. Why should provider organizations determine whether to implement the role, and how will they interact with AI centers of excellence?

A. Provider organizations should consider implementing the role because the CAIO would establish accountable leadership with the requisite expertise and strategic acumen to appropriately and timely prioritize workstreams, improve quality of care using clinical AI tools, and ultimately, ensure that the organization is able to compete effectively in the marketplace given the growing criticality of AI in the healthcare industry.

Once appointed, CAIOs should develop and lead AI centers of excellence, which refers to a dedicated organizational unit to entrench AI, where there are considerable financial resources, and necessary skills and experience to successfully implement AI.

Successful AI centers of excellence do not just live within the organization's IT department. AI projects that impact clinical practice and patient care should involve a collaboration of individuals with expertise in technology, quality of care, compliance with legal and regulatory requirements, and business ethics.

The organization should assemble a multi-disciplinary team from diverse socioeconomic backgrounds that includes a passionate lead clinician, operational experts, technology specialists and legal/compliance reviewers.

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