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This spring, the U.S. government took the unprecedented step of requiring all U.S. government agencies to appoint a chief AI officer. This follows companies across industries adding similar roles to their leadership ranks.
While this is a move in the right direction for companies looking to integrate AI, it is not enough. Yes, every company needs to become an AI company. But it would be short-sighted to expect the AI chief executive to be able to do the job alone.
When companies are faced with major technology changes, their knee-jerk reaction is often to stick with what they know. That means putting new management in charge and expecting them to figure everything out. But for AI to truly take hold in the enterprise, people at all levels of the business need to get their hands on AI and start innovating, rather than following the orders of executive gatekeepers.
In fact, in some cases, the quickest way to integrate AI into your enterprise may be to skip the chief AI officer role altogether.
Related: A Founder's Guide to Future Artificial Intelligence
Why having an AI chief executive doesn’t make sense
Companies that appoint AI chief executives have good intentions to avoid technology disruption. However, this role may not be needed, and companies adding this role should assume it is temporary.
An instructive point is the mid-decade rush to appoint chief digital officers to oversee the digital transformation to internet and mobile technologies. In hindsight, it seems strange.
Experts have declared CDO to be the next big C-suite title, but it may be little more than window dressing, especially as digital skills become a key element for most employees. It often turned out. In recent years, companies have eliminated this role or incorporated it into other jobs. In digitally native businesses, that just doesn't exist.
For example, Google didn't have a CDO to dictate how employees used web technologies. Instead, we empowered employees to explore tools on their own through initiatives like 20% Time and set the stage for innovations like Gmail.
Similarly, AI-native companies don't have executives overseeing AI. That would be redundant. At companies like mine, technology is embedded throughout the organization from day one, rather than being siled into a single role.
By default, we all rely on AI. Our marketing team uses it to better understand our customer base, our engineers deploy it to help write code, and our customers rely heavily on their AI agents for support. doing. Just as digital literacy is now ubiquitous in almost every company, AI is now embedded in every role. Of course, there are areas of our business that could use more AI, but you don't need a specific job title to make that happen. It's everyone's responsibility.
A better way to lead AI transformation
But I recognize that not all companies are built from the ground up on AI. So how can legacy companies make real progress in technology integration?
Instead of a top-down response to organizational change, consider a bottom-up approach. The first step for companies that want to lead an AI transformation is to look at the roles they're already hiring for and select a few that AI agents can fill immediately.
Customer service is an obvious place to start. Today's AI agents can now handle 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 lead generation. Another promising area is the junior data analyst role, which often consists of pulling information from reports. Next is coding. Autonomous software engineering agent She Devin and its open source rival She OpenDevin may intervene here.
Choosing the right technology partner to provide AI tools is equally important. For example, when it comes to customer service, companies should look for vendors whose AI agents have a track record of solving most problems without human intervention. Rather than following a script, you must have some reasoning ability, drawing from past interactions and the conversation at hand to determine the best solution to each customer's unique problem.
Second, it's important to treat agents like employees, not like software that works out of the box. Onboarding, measuring, and coaching (the same steps you use to develop new employees) are essential to getting the most out of your AI tools.
The benefit here is that team members start experimenting with AI and building AI expertise internally. For example, my company partners with a financial services company where her AI employee manager is a key position. The former customer support specialist is now teaching the AI agents new skills that add value across the business, making them an integral part of the team.
Companies can also use AI-powered productivity improvements as a basis for career advancement. To get promoted, an employee must show managers how she is applying AI to drive results for the business.
Related: How generative AI is redefining digital transformation and rescaling your business
Next step: These departments will grow into mini-centers of excellence that spread AI knowledge and best practices throughout the organization. Team members will educate other companies on how to hire and align with AI workers. AI will be integrated into day-to-day business operations in ways that are difficult to achieve with an exclusively top-down approach.
Of course, there is no best way to lead a company to AI transformation. For legacy industries and large companies, a tandem approach that combines top-down and bottom-up approaches may be more appropriate.
At the very least, organizations that want to get their transformation right should think about how they can support AI growth, rather than rushing to hire a chief AI officer just because other companies have taken that step. there is. It’s only a temporary solution because AI will permanently change businesses from top to bottom.
