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AI Is Not a Self-Driving Car: The Skills Needed by a Chief AI Officer and Where to Find the Ideal Candidate

AI Is Not a Self-Driving Car: The Skills Needed by a Chief AI Officer and Where to Find the Ideal Candidate

March 2024


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Accenture recently published their 2024 Pulse of Change Index

This index, built on a range of key business indicators such as labor productivity and IT spending, quantifies the change companies are facing across six factors: technology, talent, economic, geopolitical, climate, and consumer and social. It then compares this data to a survey of 3,400 C-suite executives on how they view the impact of each factor on their organizations, as well as their preparedness to respond. 

As I reviewed this index, two things stood out to me, which might explain this perception gap around talent. As Accenture noted, AI has become the underlying fuel for the ascendance of technology into the No. 1 spot. However, could AI also be a major factor in contributing to the perception gap? I believe it is.  

It appears many C-suite executives have a misguided belief that AI will be a magic bullet for solving their talent issues. They believe that AI will be a driverless car that delivers greater efficiency and productivity and, in so doing, reduces people costs.  

While at its best, AI will absolutely deliver increases in efficiency and productivity, the resulting personnel shifts will undoubtedly replace lower-level skilled roles with individuals who have higher-level skills. Higher-level skilled talent generally means more expensive talent. It remains to be seen if this will increase or decrease total people costs. We may not know for quite some time.  

Regardless, what we do know is that the belief that AI can be a driverless car and automatically reduce your people expenses is incorrect. Yes, the right way to view AI is that it is a very powerful car, but it is a car that can only be driven far, fast, and safely to the right destination by putting a driver behind the wheel who is highly skilled in both broad and specific ways.  

If you think of AI as a Mercedes, then putting Lewis Hamilton behind the wheel—the driver holding the all-time record for Formula 1 wins—will get you much further, much faster, and over the finish line first than someone who is not Lewis Hamilton. Hamilton has the skills, experience, and knowledge to take the high-performance vehicle that is a Formula 1-engineered Mercedes and achieve record-breaking speeds in a variety of weather and road conditions, amidst the fiercest competitive pressures. Whereas even the best non-professional drivers, under the same conditions, would deliver less results and, at worst, crash the car.  

When this analogy is applied to AI, it speaks to what is perhaps the most important new role in the C-suite: the Chief AI Officer. However, what are those skills and experiences that constitute someone being the Lewis Hamilton of AI? 

The most forward-thinking CEOs and companies are beginning to explore what a Chief AI Officer could mean for their companies and how to define the ideal profile. And, as an aside, I am continually bombarded by emails and LinkedIn requests by individuals putting themselves forward as Chief AI Officers, most of whom are not qualified.  

Because of AI’s relatively rapid emergence as a tool that enterprises could and should use, there’s not a ready field of candidates with long and successful track records in this new role or individuals who have the skills and experiences required for the ideal Chief AI Officer.  

While there is still a shortage of data scientists, there is at least a growing group of individuals who have core data science experience and are skilled at leading teams of data engineers and data analysts. But is this the right background for someone to harness the full capabilities of AI and create and lead the development and implementation of AI initiatives across a company? 

The natural inclination of many organizations is to tap a data scientist, or CIO, to lead AI initiatives. But per the Accenture Index, that may be as big of a mistake as assuming that AI solves your talent issues.  

The ideal candidate for a Chief AI Officer is not the person writing algorithms. Rather, it is an individual who can authoritatively speak with the scientists who write algorithms. It is someone who understands the business ramifications of the data that these algorithms deliver and who can lead AI initiatives to maximum impact across the multiple functions and lines of business constituting the entire enterprise, whether that be general AI, machine learning (ML), or robotic process automation (RPA). 

The Special Skills Needed for Chief AI Officers

The role of a Chief AI Officer is much closer to that of Head of Digital Transformation than it is to the position of Chief Information Officer or Chief Data Officer.  

Digital transformation leaders do not spend their days writing code. Instead, they lead across multiple functions, communicating a vision, plotting a strategic path, and inspiring stakeholders to participate in the transformation. 

Similarly, a Chief AI Officer is a high-level, strategic job. The skills required include natural leadership and, most critically, cross-functional management experience.  

The head of an organization’s AI office must understand the fundamentals as well as the individual business units of the company and be able to navigate and think through the best uses of AI.  

This individual will whiteboard initiatives, understanding dependencies across an organization, and then implement them from a project management perspective, all the while addressing ethical and data security considerations.  

Where Chief AI Officer Candidates Might Exist

A potential Chief AI Officer could come from a variety of places within an organization, but what is essential in their background is broad, cross-functional business management experience. This is perhaps even more important than being a data scientist.  

Having said that, this individual would ideally have a base level of data science experience and knowledge that allows them to converse with data scientists, resulting in a level of respect within the data science ranks. For example, at a manufacturing company, a CAIO candidate might be found in a GM who thoroughly understands operations, product development, process, finance, and go-to-market strategy while also understanding data science.  

Two other areas that could yield promising candidates for a Chief AI Officer are product management and digital transformation. Successful product managers and digital transformation heads excel at managing through influence. They deliver results with 100% accountability and 0% responsibility (in terms of direct line management) by earning the trust of stakeholders they do not supervise.  

Promising CAIO candidates might also be found in the consulting world. Effective consultants are experienced in driving initiatives and working across multiple functions. And many of them have been drop-shipped to their clients to lead strategic cross-functional and line-of-business initiatives that emphasize digital transformation.  

There are also many senior professional services consultants who have client-side business operations experience between tenures in consulting. These individuals have the additional benefit of having lived what they have preached, not just advising and leaving.  

Another possibility for an organization seeking a CAIO candidate is to look at more of an elder statesperson, a recently retired president, CEO, COO, or general manager, who has also immersed themselves in AI. If from the same vertical sector, this individual intimately knows how complex organizations work within a company’s industry and is comfortable driving cross-functional and cross-business strategic initiatives. And based on past success, it will be clear the degree to which a potential candidate excelled at aligning a diverse workforce on strategic goals and rallying the troops to take actions that are disruptive and different from ‘how things have always been done’—the same skillsets needed for a successful Chief AI Officer. 

What About Data-Driven Candidates?

Many CEOs are understandably making the mistake of only looking for their AI lead among their data scientists. A successful Chief Data Scientist might be running a team of 15 or more data scientists. But do they have business and domain understanding across the organization? Have they thought beyond specific applications to consider what AI might mean to their company beyond solving specific data science problems? Do they know how to inspire and motivate others outside of their department? While having functional experience and understanding of data science, have they also grown into business leaders? These are critical questions.  

Another popular choice for a Chief AI Officer is an organization’s existing Chief Information Officer. But again, many of them may lack the cross-functional experience and knowledge that is so vital to the Chief AI Officer role. In addition, many—not all, but many—are natural introverts who are most comfortable interacting within the IT stack and are not as comfortable in non-technical interactions and, most importantly, driving initiatives that require managing others through influence.  

What if an organization has identified an individual with the broad, cross-functional experience and leadership traits to serve as Chief AI Officer—but they are light on AI knowledge? There are a growing number of resources, such as, that offer training and certification to get promising leaders up to speed quickly. 

The AI-Talent Perception Gap and Defining the Ideal Chief AI Officer

As the data show, there is a perception gap amongst C-Suite executives that AI solves talent issues. This perception gap is rooted in thinking that AI functions much like a self-driving car. It does not.  

Astute CEOs and boards will resist the urge to only look at a data scientist or CIO for this role without evaluating whether the individual possesses the business knowledge, people management experience spanning cross-functions and lines of business, and the requisite leadership capabilities. They will refrain from appointing a Chief AI Officer whose primary skill set is writing complex algorithms and instead look for an individual who can both motivate and successfully communicate with those who write the algorithms while also conveying the business impact of the AI initiatives they are driving to the board, investors, and marketplace.  

Intentional employers will expand their search for this pivotal new position and look for leaders both within and outside of the IT ranks who are accustomed to managing through influence across multiple functions and, if not data scientists themselves, have ideally demonstrated a base level of knowledge in AI and data science.  

There is a race underway for organizations to thoughtfully adopt and implement AI initiatives, which will have maximum impact across every area of their business. The most powerful AI initiatives are led by a driver who understands both the business and the organization, in addition to possessing leadership skills. This, coupled with just-deep enough understanding of data science to formulate and successfully lead AI strategies, is a winning combination. And while it is important to have the right car, the winning team also needs the right driver to win the race. In the AI race, this is the Chief AI Officer. 

About the Author 

Greg Selker is a Managing Director at Stanton Chase, the Regional Sector Leader for Technology in North America, and the Global Subsector Leader for Growth Equity. He has been conducting retained executive searches for 33+ years in technology, completing numerous searches for CEOs and their direct reports at the CXO level, with a focus on fast growth companies, often backed by leading mid-market private equity firms such as Great Hill Partners and JMI Equity. He has also conducted leadership development sessions with more than 50 executives from companies such as BMC Software, Katzenbach Partners, NetSuite, Pfizer, SolarWinds, Symantec, TRW, and VeriSign.    

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