BY SARAH LYNCH For INC.
Generative A.I. exploded in 2023, but business leaders might already be missing opportunities to use the technology to its full potential.
One-third of businesses use generative A.I. in at least one function, according to a new report from the global management consulting firm McKinsey & Company. This finding comes from a survey of 1,684 businesses across sizes and industries.
Even more, 40 percent of all respondents expect their organizations to increase A.I. investment thanks to advances in generative A.I. Use cases already span marketing and sales, product and service development, customer care, and more.
But the report also reveals where leaders might be overlooking–or underestimating–the power of A.I. within their organizations. Here are two mistakes that leaders might be making–and how you can avoid them.
Focusing too much on cost savings
Smaller businesses can be strapped for cash, so generative A.I. presents an attractive opportunity for leaders looking to cut costs. But the McKinsey report shows that the highest A.I. performing companies–or those that attributed at least 20 percent of earnings before interest and taxes to A.I. use–ranked “reducing costs” as the lowest priority for their generative A.I. efforts. Instead, they prioritized increasing the “value of offerings by integrating AI-based features or insights,” the report shows.
Still, it makes sense that leaders of smaller companies are looking to cut down on costs with A.I., says Michael Chui, partner at the McKinsey Global Institute. That’s not a bad thing, he adds, but leaders also shouldn’t ignore opportunities for A.I. to boost the top line.
Companies that do so may find ways to “leapfrog” over their competition, says Brian Uzzi, the Richard L. Thomas professor of leadership at the Kellogg School of Management at Northwestern University. “It becomes much more of a strategy focus in terms of building and growing markets–innovating, rather than reducing costs.”
One way leaders can increase the value of offerings with A.I. is by identifying what kind of data their organization has internally, feeding that data into an A.I. tool, and thus revealing unique insights from that internal data. “If you just use A.I. that’s built on generic data outside your company, then all your competitors can get the same results as you,” Uzzi says. Instead, leveraging internal data can help guide the business’s growth and set it apart from competitors, he says.
Leaders can also enhance their business operations by using generative A.I. to enhance, rather than replace, employees. “We spend way too much time talking about or thinking about people or computers, and not enough time thinking about people and computers,” says Thomas W. Malone, professor of management at the MIT Sloan School of Management. The companies that take the latter approach will go far, he adds, as this focus will help them produce stronger offerings and better serve customers.
Not taking the risks seriously enough
While A.I. can offer a myriad of benefits for businesses, it also comes with risks, including cybersecurity, regulatory compliance, and intellectual property infringement. Respondents ranked inaccuracy as the most relevant risk for their organization, and yet, less than half say their organization is working to mitigate that risk. In addition, just 21 percent of respondents say their organization has established a generative A.I. policy for employees’ work.
But policies and guidelines are important, Uzzi says, particularly when it comes to issues like accuracy. For instance, an organization might instruct employees to cite and report where they use data produced by ChatGPT and require that they independently confirm the information it produces, he says: “Those kinds of guidelines can go a long way [for] using ChatGPT in a way that improves accuracy and productivity at the same time.”
Leaders can stay abreast of A.I.’s potential uses and risks by using this technology themselves, Chui says. Some are already doing so: Nearly one-quarter of C-suite executives surveyed said they already personally use A.I. tools for work.
“Once you start using it, you realize, ‘I could use it for X.’ And at the same time, you can also say, ‘It really got that wrong. I need to think about how to deal with some of these risks,'” Chui says. “This stuff is really easy to get to try out, and I’d encourage people to do that.”
