Use AI on the Job—Or Else

On her performance review, the manager noticed a new category. Underneath “quality of work” and “productivity and efficiency” she discovered something called “technology utilization.” She was puzzled.

AI usage is swiftly making its way into performance reviews. Whether they’re calling it “technology innovation” or “technology agility,” firms are increasingly measuring employees’ use of AI, following a year in which worker access to AI grew by 50%, according to a new report. Experts say that for the most part, they smell smoke. “There’s an over-rotation here,” says Bryan Ackermann, head of AI strategy and transformation at Korn Ferry. “This isn’t a measure of learning agility.”

To some degree, AI usage as a standard employee metric makes sense, especially since companies have invested heavily in AI development in recent years—$252 billion in 2024 alone, according to figures from Stanford University. Executives are keen for these very expensive AI systems to be used, and to show demonstrable returns on investment to stakeholders, including impatient activist investors. All of that requires immediate employee adoption, and firms are using a stick rather than a carrot, by directly tying AI usage to promotions and salary increases. “It’s happening in the interest of a massive push to prove that AI investments made sense,” says Ackermann.

The trend of including AI use in performance reviews has trickled into many industries. “This is a huge initiative in tech-forward companies,” says Paul Fogel, sector leader in the Software practice at Korn Ferry. Critically, performance reviews frequently measure not just whether an employee engages AI tools during the workday, but also whether they have improved their workflows or created efficiencies—challenging metrics for workers who may not naturally think in those terms.

To be sure, firms have long tracked internal tech systems. Monitoring AI usage provides an array of employee data, from the projects and clients taking up most of their time, to the problems they’re struggling with, to their relative skill at prompting. Analyzing the data can reveal whether AI is augmenting their work or masking weaknesses. But employees are leery, because over time, AI usage can create a detailed behavioral blueprint.

Experts advise that discussion and evaluation of AI usage be continuous—rather than quarterly or annual—as part of an integrated approach to adopting the technology. The success of these initiatives will pivot not on employee ratings but on AI training: Counterintuitively, the employees least likely to use AI are often those, such as tech writers or software developers, who have spent their careers learning a particular skill or expertise. “There’s a natural reluctance there,” says Fogel. “You can’t expect people to natively adapt.”

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