Wharton survey: daily AI use jumps 16 points as skepticism grows

Managers and employees differ on AI training adequacy

The Wharton School of the University of Pennsylvania and research firm GBK Collective published findings from their fourth annual enterprise AI survey this week, showing that daily AI use among managers and above climbed 16 percentage points to 62% from the prior year while caution and skepticism about the technology grew within the same group. The survey polled 1,416 U.S. enterprise leaders and entry- and mid-level employees.

“You could see a very marked AI backlash over the last months,” co-author Stefano Puntoni, the Sebastian S. Kresge Professor of Marketing at the Wharton School and faculty co-director of Wharton Human-AI Research, told the WSJ Leadership Institute. “But certainly, we see that generally people are positive,” he added.

The wariness runs highest among the technology’s heaviest users. Eighty-two percent of respondents ranked vice president or higher say their focus has shifted to managing AI output. Forty-eight percent of that group said they worry their own skills or thinking are declining, compared with 32% of managers and directors.

The report also documents a gap between managers and above and entry- and mid-level employees on training. Seventy-eight percent of managers and above said employees are adequately trained on AI, but only 56% of entry- and mid-level employees agreed. Co-author Jeremy Korst, a partner at GBK Collective and a Wharton lecturer, said the middle of the organization is “where the work gets done,” and that mid-level managers and directors are now being asked to rethink workflows and function across organizational boundaries, usually without extra time or budget.

Nearly all companies report some return on their AI investments, but far fewer report substantial ones, the survey found. Eighty percent of managers and above see positive returns; 28% call them strongly positive. The difference appears tied to what companies measure. Hours saved is the most common yardstick, yet departments that judge AI by growth are far more likely to report strong returns.

“If you’re using it for growth, you have to start doing things that you were not doing,” Puntoni said. “And so it takes imagination, and I think that’s much, much harder.” His advice to executives: “Your job should not be to use this technology to automate what you’re doing today. It should be to figure out what it is that you could be automating that you’re not doing at all.”

Two-thirds of departments now use AI agents in some form, and 17% let them act without a person approving each step, the report found. Returns on AI tend to be strongest in those departments using agents. “It seems to be going very fast,” Puntoni said of agent adoption. “Those organizations that are kind of stuck in the middle, that are adopting, but not quite, they seem to be struggling.” Who answers when an agent goes wrong remains unsettled, the report noted.

Departments that reported strong returns were no more likely to reduce staff or freeze hiring than others; instead, they were more likely to have changed their management structure (64% versus 47% across the rest of the sample), significantly changed workflows (84% versus 69%), and to monitor AI use (92% versus 74%).

“This technology is not going to work by itself,” Puntoni said. “You have to figure out what to do with it.”

Leadership structure also appeared to correlate with reported returns. At organizations with a newly created chief AI officer, 58% of managers and above report strongly positive returns on AI, compared with 24% at companies that added the responsibilities to an existing executive’s duties, and 8% at those with no such role.

Puntoni cautioned that the data cannot show whether the role drives the results or whether companies that create a chief AI officer were more AI-savvy to begin with. He said he suspected it runs both ways: companies that did a good job setting up the role probably already had the culture and capabilities to exploit the technology. “But having that role hopefully will help,” he added.

The report reflects a growing maturity in expectations around AI as organizations navigate concerns over costs and increasingly autonomous agents, and as the definition of return on investment begins to shift from time saved to the creation of broader value, according to the authors.