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This spring, the U.S. government took an unprecedented step: It required every U.S. agency to appoint a chief AI officer. This follows companies from different industries adding similar roles to their leadership positions.
For companies looking to integrate AI, this is a step in the right direction, but alone it is not enough. Yes, every company has to become an AI company. But expecting a chief AI officer to do the job alone is short-sighted.
When companies are faced with a major technological change, their knee-jerk reaction is often to stick with what they know: put a new leader at the helm and hope they can solve everything. However, for AI to truly take hold in an organization, people at all levels of the organization must take ownership of it and start innovating, not following the orders of an executive gatekeeper.
In fact, in some cases, the quickest way to integrate AI into a company may be to skip the Chief AI Officer role altogether.
Related: The future founder’s guide to artificial intelligence
Why it might not make sense to have a Chief AI Officer
Companies that appoint a chief AI officer have good intentions as they seek to avoid disruption from technology. But they may not need this role, and any company adding it should assume it is a temporary role.
A useful comparison is the rush to appoint chief digital officers in the middle of the last decade to oversee digital transformation to the Internet and mobile technologies. In retrospect it looks quaint.
Experts described the CDO as the next big leadership title, but it often turned out to be just window dressing – especially as digital skills became a prerequisite for most employees. In recent years, companies have abandoned the role or transferred it to other jobs. This doesn’t exist at all in digitally native companies.
At Google, for example, there has never been a CDO controlling the way employees use web technology. Instead, they empowered employees to explore tools on their own through initiatives like “20% Time,” setting the stage for innovations like Gmail.
Likewise, AI-native companies do not have an executive overseeing the AI. That would be unnecessary. In companies like mine, technology is embedded throughout the organization from day one, rather than isolated to a single role.
By default we all use AI. Our marketing team uses it to better understand our customer base, our engineers use it to help write code, and our customer support relies heavily on AI agents. AI is anchored in every role, similar to how digital competence is now anchored in almost all companies. Of course, there are areas in our company where we could use AI more and better, but achieving this does not require a specific job title. It is everyone’s responsibility.
A better way to initiate an AI transformation
But I realize that not every company is built on AI from the ground up. So how can legacy companies make real progress in integrating technology?
Instead of a top-down response to organizational change, consider a bottom-up approach. For a company looking to embark on an AI transformation, the first step is to look at the roles you’re already hiring for and select a few where AI agents can do the work today.
Customer service is an obvious starting point – today’s AI agents can now solve most problems at least as well as humans. AI sales development representatives (SDRs) are also making an immediate impact, automating much of the effort involved in pursuing prospects. Another promising area is junior data analyst positions, which often involve extracting information from reports. Then there is the coding. This is where the autonomous software engineering agent Devin and OpenDevin, its open source rival, can step in.
Choosing the right technology partner to provide AI tools is equally important. For example, when it comes to customer service, companies should look for a provider whose AI agents have a proven track record of resolving most issues without human intervention. Instead of following a script, they should have some thinking skills and rely on past interactions and the current conversation to determine the best solution to each customer’s unique problem.
Then it’s important to treat your agents more like employees and not like software that’s ready to use out of the box. Onboarding, measuring, and coaching—the same steps you would take when developing new employees—are essential to getting the most out of AI tools.
The benefit is that team members who experiment with AI begin to build AI expertise within the company. For example, my company works with a financial services company where AI employee manager has become a key position. Former account managers are now teaching the AI agents there new skills that create added value throughout the company – making them an indispensable member of the team.
Companies can even make increasing productivity using AI a criterion for career advancement. To get promoted, an employee must show their manager how to use AI to deliver results for the company.
Related: How generative AI is reshaping digital transformation to transform how businesses scale
The next level: These departments become mini centers of excellence that spread AI knowledge and best practices throughout the company. Team members train the rest of the company on how to hire and coordinate AI workforce. AI is being integrated into everyday business in ways that are difficult to achieve with a purely top-down approach.
Of course, there is no one best way to lead a company through an AI transformation. For traditional industries and large companies, a tandem approach – combining top-down and bottom-up approaches – may prove more suitable.
At the very least, organizations that want to get the transformation right should think about how they can help AI bubble to the top, rather than just rushing to hire a chief AI officer just because others have made that move. Because AI is fundamentally transforming businesses, it is only a temporary solution.