In the past five years or more, we have seen the rise of artificial intelligence and machine learning in healthcare. These new technologies are being employed to improve patient care, create operational efficiencies, spur translational research and identify cost savings. At the most recent American Medical Informatics Association (AMIA) annual symposium in San Diego, AI and ML were perhaps the hottest topics of discussion. Clearly, they represent the next wave of innovation in healthcare.
Currently, however, uses of AI and ML are decentralized and mostly ad hoc, with some projects overseen by the CIO and digital leaders, others by the chief data officer, and still others by research and biomedical informatics leaders. A few fundamental applications of AI include everything from triaging of patients, to rudimentary chat bots, to embedded predictive analytics in the EHR and to more advanced population health initiatives based on social determinants of health data. The key moving forward will be integration and strategic alignment of these disparate projects, which will require the creation of a dedicated executive position – the Chief AI Officer.
We are beginning to see some organizations adopting Chief AI Officer roles and championing enterprise AI/ML strategies. This trend has just started, and my colleagues and I expect AI Officers to multiply in the next several years.
What will this evolving role look like? For this article, I conducted informal surveys of AI executives and other innovative health IT leaders across the industry to get their ideas on what AI leadership looks like today, and how it will evolve. What are the key prerequisites for the role, and what will its responsibilities be from one organization to the next? One thing is for certain – AI Officers will play a key role in shaping healthcare's future. As Children's Hospital of Orange County Chief Intelligence and Innovation Officer, Anthony Chang, M.D., noted during our discussion, Chief AI Officers will be the leaders that help determine where best to implement AI in a health system and how to manage the business transformation that comes along with it. Robert Donnell, M.D., Chief Medical Informatics Officer and AI leader for the University of Florida, commented, "The AI Officer has to be a leader who is capable of educating the healthcare community, bringing back the right inputs to the team, leading the development of algorithms and also how to interpret them. This is a leader bringing their community through a very complex change process. Early on, the Chief AI Officer has to be the chief trust officer, the chief learning officer and the chief knowledge officer on what AI can do and how to get it there."
Defining the role
What will a Chief AI Officer do? This is a question that many organizations are still asking. For progressive organizations, this is going to be the leader who focuses on continuing to integrate AI and ML into workflows, technologies and business processes to improve outcomes, increase efficiencies and help to improve the bottom line of a health system. Regardless of whether an organization decides to pursue a more centralized or decentralized strategy, the Chief AI Officer will be the executive responsible for aligning efforts across the organization and ultimately ensuring its use is a net positive for the clinical community, staff and patients. As health systems' use of data has grown exponentially in recent years, the Chief AI Officer can ensure the appropriate resources and structures are in place for successful AI implementations.
A common example of early AI adoption in healthcare is the increased use of chatbots as a first line of service for patients to help schedule appointments with the right specialty. A Chief AI Officer will be responsible for making sure the changes in employee workflows caused by the new technology are correct, that the specialty groups are trained on the tool and that the algorithm is continually refined to improve its accuracy and effectiveness. This will require significant influence within the organization to get the approvals and resources needed to move ahead with projects, the ability to communicate and collaborate with disparate groups, and the analytical skills to show that the technology is working and bringing ROI to the organization.
One AI leader told me that, while there may be an ebb and flow of centralized or de-centralized AI teams, there will always be a need for a Chief AI Officer who can manage the complexities of numerous ongoing clinical and operational projects. A different AI leader made note of the importance of AI to reflect the mission of health systems and that any project needs to focus on the patient first and to build out from there.
An essential position?
Another question that many organizations will ask is, do I really need a leader focused on AI? The short answer is yes. While we expect titles to vary in the coming years as the role rises in prominence, the need for a cohesive, connected AI strategy will be essential as health systems look to increasingly utilize systems in the space. It will be important to align data definitions as well as the added complexity of business processes. The level of complexity required to successfully implement AI in a variety of settings is why there must be a dedicated leader in the space.
The potential for bias in the data, large disruptions to the workforce and other areas of consternation for AI are very real possibilities. During one conversation with a Chief AI Officer, they discussed the importance of utilizing the Agile methodology for design development and implementation to make sure health system teams can constantly provide feedback and make sure what is developed will improve patient lives and operations. Health systems will need a leader solely focused on seeing these programs implemented and refined over time from both a technology and business process perspective.
Background for the role
What exactly is the background of a Chief AI Officer? In other industries it has often fallen to data scientists to move into the formal leadership role of a Chief AI Officer. In healthcare this will remain true, but with some important nuance. In healthcare, we will see Chief Analytics Officers, physician leaders, informatics leaders and, potentially, some Chief Information Officers take on the role as an evolution of their current work and skill set. For many, it will require a willingness to get additional formal education in AI and Machine Learning and applying that to their already mature leadership skill set. For some more clinically focused leaders, there are increasing opportunities through education programs being built at academic medical centers or through organizations like the American Board of Artificial Intelligence in Medicine to jumpstart their careers in the space. The importance of AI has become apparent as even the Association of American Medical Colleges makes a push for more AI focused curricula in medical schools.
Beyond health systems, we are seeing medical schools and universities with the greatest foresight expand their departments of biomedical informatics to include AI into formal programs or leadership roles within their structure. This is while some academic health institutions are creating entirely new departments and centers focused on AI and pursuing science related to building out that pipeline of leaders and researchers.
Reporting relationship
The AI Officer's reporting relationship will be critical in ensuring the role's success. Most likely, they would report to the Chief Information Officer or Chief Digital Officer. Given the need for the Chief AI Officer to have broad visibility across the entire technology stack, the CIO or CDO as a Chief AI Officer's supervisor will allow for the change management needed to successfully implement these transformational systems. Reporting through technology leadership provides an opportunity for the Chief AI Officer to work with their fellow technology peers to integrate AI into the technology workflow and ensures they are not working on their own island. Other possibilities of executives to whom the Chief AI Officer might report include the CMO or even possibly the CEO for particularly progressive organizations. Regardless of their direct report, the Chief AI Officer will need to be a visible leader working with the COO, CFO, clinical department chairs and many others to bring about the cultural change that will allow AI to succeed.
AI is already here for health systems across the country, whether embedded in the EHR, the ERP, population health tools or other ancillary systems. The health systems that will take the lead are those that recognize the need for dedicated leadership in a space that will cause significant transformations across healthcare in the coming decade. On the importance of the Chief AI Officer, Dr. Donnell shared, "When you look at the entire world's investment in AI, medicine and healthcare are the single largest holder of development dollars for AI. Who is managing those dollars to the right outcome? We need AI leaders who are capable of installing in healthcare's complex environment or we risk having it misapplied."
Zachary Durst is a consultant in WittKieffer's Information Technology Practice.
