This spring, the US Govt took an unprecedented step: requires every US agency to appoint a chief AI officer. This follows on the heels of companies in various industries adding similar roles to their leadership ranks.

This is a move in the right direction for companies looking to integrate it, but it is not enough on its own. Yes, every company should become an AI company. But expecting an AI boss to do the job alone is short-sighted.

When businesses face a major technological change, often their knee-jerk reaction is to stick with what they know: Putting a new executive in charge and hoping they can sort things out. But for AI to take root in a company, people at all levels of the business need to embrace it and start innovating, not following the orders of a C-suite gatekeeper.

In fact, the fastest way to integrate AI into a company is, in some cases, perhaps to bypass the role of the chief AI officer altogether.

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Why having an AI boss might not make sense

Companies that appoint a chief AI officer have good intentions as they seek to avoid disruption by technology. But they may not need the role, and any business that adds it should assume it's temporary.

A useful comparison is the scramble in the middle of the last decade to appoint chief digital officers to oversee digital transformation in Internet and mobile technologies. In hindsight, this seems strange.

Experts pronounced ALL the next big executive title, but it often turned out to be little more than window dressing—especially when digital skills became table stakes for most employees. In recent years, companies have been giving up the role or folding it into other jobs. In digital native businesses, it doesn't exist at all.

Google, for example, never had a CDO directing how employees use Internet technology. Instead, they empowered employees to explore their tools through initiatives like 20% timesetting the stage for innovations like Gmail.

Likewise, domestic AI companies do not have an executive overseeing AI. That would be too much. In companies like mine, technology is embedded from day one throughout the organization rather than in a single role.

By default, we all use AI. our marketing team I use 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 written into every role, just as digital literacy is now in almost all companies. Of course, there are areas of our business where we can use AI more and better, but doing so doesn't require a specific job title. It is everyone's responsibility.

A better way to bring about an AI transformation

But I understand that not every company is built from the ground up on AI. So how can legacy companies make real strides in technology integration?

Instead of a top-down response to organizational change, consider a bottom-up approach. For a company that wants to create a The transformation of AIthe first step is to look at the roles you're already hiring for and pick a few where AI agents can do the job today.

Customer service is an obvious place to start – today's AI agents can now handle most issues at least as well as humans. AI sales development representatives (SDRs) are also making an immediate impact, automating much of the labor involved in prospect follow-up. Another promising area – new data analyst roles, which often consist of extracting information from reports. Then there is the coding. Autonomous software engineering agent Devin AND OpenDevinits open source rival, can come in here.

Choosing the right technology partner to deliver AI tools is just as important. When it comes to customer service, for example, companies should look for a vendor whose AI agents have a track record of resolving most issues without human intervention. Rather than following a script, they must have some ability to reason, drawing on past interactions and the conversation at hand to determine the best solution to each customer's unique problem.

Then, it's important to treat your agents more like employees than like a piece of software that will work right away. Onboarding, measurement and coaching — the same steps you'll take to develop any new hire — are essential to getting the most out of AI tools.

The upside here is that having team members experiment with AI starts to build AI expertise within the company. For example, my company works with a financial services firm where AI employee manager it has become a key position. Former customer support specialists there now teach AI agents new skills that add value to the entire business – making themselves an indispensable member of the team.

Companies can even make increasing productivity through AI a criterion for career advancement. To be promoted, an employee must show their manager how they are applying AI to deliver results for the business.

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Next phase: These departments grow into mini centers of excellence that spread AI knowledge and best practices across the organization. Team members educate the rest of the business on how to hire and coordinate AI work. AI is integrated into daily business operations in a way that is difficult to achieve with an exclusively top-down approach.

Of course, there is no better way to take a company through an AI transformation. For legacy industries and large enterprises, a dual approach—combining top-down and bottom-up—may be more appropriate.

At the very least, organizations that want to make the right transformation need to think about how they can help AI grow through the ranks, rather than just rushing to hire a chief AI officer simply because others have taken that step. While AI is forever changing companies from top to bottom, this is only a temporary solution.