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This spring, the U.S. government decided to take an unprecedented step: Requiring each U.S. agency to appoint a director of artificial intelligence. This comes hot on the heels companies from various industries adding similar roles to their management positions.
This is a move in the right direction for companies looking to integrate AI, but it is not enough on its own. Yes, every company must develop into an AI company. However, it is shortsighted to expect the chief AI officer to complete the task alone.
When companies face a major technological change, their knee-jerk response is often to stick with what they know: appoint a latest executive as director and hope that he or she’s going to figure things out. But for AI to truly take root in a company, people at all levels of the company need to get their hands on it and start innovating, fairly than following the orders of a gatekeeper at the executive level.
In fact, the fastest way to integrate AI into your organization is, in some cases, to bypass the role of chief AI officer altogether.
Why having a chief AI specialist won’t make sense
Companies appointing a chief artificial intelligence officer have good intentions as they seek to avoid disruption from technology. However, they might not need this role and any company that adds it should assume it is temporary.
A useful comparison is the panic that occurred in the middle of the last decade over the appointment of chief digital officers to oversee the digital transformation towards web and mobile technologies. In hindsight it looks strange.
Experts denounced CDO one other big executive title, but it often turned out to be little more than window dressing – especially as digital skills became table stakes for most staff. In recent years, companies have been abandoning the role or turn it into other jobs. This is not the case at all in digitally native companies.
For example, Google has never had a CDO that controls how employees use Internet technologies. Instead, they empowered employees to discover tools on their very own through initiatives similar to 20% of the timesetting the stage for innovations like Gmail.
Similarly, AI companies do not have a director overseeing AI. That can be unnecessary. At companies like mine, technology is embedded throughout the organization from day one, fairly than assigned to a single role.
By default, all of us use artificial intelligence. Our marketing team uses it to higher understand our customer base, our engineers deploy it to help write code, and our customer support relies heavily on AI agents. Artificial intelligence is embedded in every role, just as digital literacy is now present in just about all companies. Of course, there are areas of our business where we could use artificial intelligence more often and higher, but for this to occur, it is not obligatory to have a specific position. It’s everyone’s responsibility.
A greater way to start your AI transformation
But I realize that not every company is built from the ground up based on artificial intelligence. 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 review the positions you’re already hiring for and select a few where AI agents can do the job today.
Customer service is an obvious start line – today’s AI agents can now solve most problems at least in addition to humans. AI Sales Development Representatives (SDRs) also make an immediate impact by automating much of the lead generation work. Another promising area is junior data scientist roles, which frequently involve extracting information from reports. Then there is coding. Autonomous software engineering agent Devin AND Open Devinits open source rival may step in here.
Choosing the right technology partner to provide AI tools is equally vital. For example, when it comes to customer support, companies should look for a provider whose AI agents are experienced in solving most problems without human intervention. Instead of following a script, they need to have some reasoning ability, drawing on past interactions and ongoing conversation to determine the best solution to each customer’s unique problem.
Next, it is vital to treat your agents more like employees than like software that can work right out of the box. Onboarding, measurement, and coaching — the same steps every latest worker takes — are essential to getting the most out of AI tools.
The advantage is that team members experiment with AI and begin to build AI expertise inside the company. For example, my company works with a financial services company where AI Employee Manager became a key position. Former customer support specialists are now teaching AI agents latest skills that add value throughout the company, making them an indispensable member of the team.
Companies may even make increasing productivity through AI a criterion for profession advancement. To advance, an worker must show their manager how they are using AI to drive results for the company.
Of course, there is no single best way to guide your organization through an AI transformation. For older industries and large enterprises, a tandem approach – combining top-down and bottom-up approaches – could also be a higher solution.
Organizations that want to get the transformation right should at least consider how they will help AI rise to the top, fairly than rushing to hire a chief AI officer just because others have taken the step. As AI permanently changes businesses from top to bottom, this is only a temporary solution.