Most teenagers are familiar with the ruse: Mom asks if you’ve cleaned your room. You reply, “yes,” because you did, indeed, toss some of your dirty laundry in the basket before logging onto Xbox. But it’s not the full truth; it’s mostly false, but to a teen, it feels like enough of the truth.

American workers have employed a similar tactic when it comes to AI use, according to new research from Visier.

The survey of 1,000 full-time US employees found that 48% exaggerate their AI usage or expertise to colleagues or company leadership at least some of the time. Visier has identified this as “performative AI”: overstating and overplaying AI use in order to meet employer expectations.

“Something I wanted to understand: How often do people actually feel they have to use AI because of all these mandates?” said Andrea Derler, Visier’s principal researcher and author of the report. “We discovered that almost half of employees actually do feel that pressure to use it for basically all their workflows, whether they make sense or whether they don’t make sense.”

This group of employees are participating, going through the motions, but they’re not meaningfully incorporating AI into their workflows, or they don’t understand how, she said. The findings articulate a potentially expensive problem for organizations working to extract productivity gains from the AI tools they’re investing in and developing.

“I don’t want to blame the employee here. That’s really important to me…That’s not the point. We all need to have a certain degree of impression management in our jobs. Everybody has to,” she said. “But in this case, because we have to learn so much, because it’s so critical that we get this right, because it’s so expensive not to get it right, that’s why it really matters.”

AI use as a measure of progress amid the AI transformation, may be more akin to the concept of tokenmaxxing as an indicator that employees were deeply engaged in working with the technology…meaning they’re actually not. AI adoption may simply measure adherence to a company’s AI-use mandate, rather than their engagement with the tool.

“We miss really important opportunities and learning opportunities and value creation opportunities if we give a goal like tokenmaxxing or in usage of AI, rather than investigation and critical thinking about where it could be helpful where it can’t, and that is not a convenient message,” she said.

Many leaders missed an opportunity to learn at the jump how their teams would be using AI and what they should be learning in order to best make use of the technology, she said, and workers are losing confidence even that their leaders and managers can lead on AI.

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