Psychology’s Role in Moving Workers Forward with AI Adoption

With all the clamor around artificial intelligence (AI) in the workplace, implementation bottlenecks generally don’t boil down to the tools, but rather to human nature. That is according to a study by consulting firms Fractional Insights and Ferrazzi Greenlight. Respondents spanned industries such as healthcare, technology, finance, manufacturing, retail, education and hospitality.

“AI angst,” as the study calls it, is when employees are concerned about AI’s impact on their work and job security. Nearly 80% of the surveyed workers were strongly concerned about at least one area related to AI angst.

The surveys assessed not only AI angst but also “core beliefs” — whether employees perceived AI has business value. And, confidence in one area didn’t always translate to confidence in the other. 

“This research found that belief in AI’s value and perceived personal risk do not move together, and that split is often what causes AI adoption to stall,” said Wendy Smith, the head of research and thought leadership at Ferrazzi Greenlight. “Managers who ignore that psychology can misread compliance as commitment and usage as true buy-in.”

Leaders shouldn’t brush aside these types of nuances while trying to get their workforce on board with AI utilization, said Kevin Tamanini, the vice president of professional services and customer success at leadership consulting firm DDI.

“The speed, volume and velocity of what’s happening with AI makes people start to focus on utilization metrics alone,” he said. “But we know through a lot of research and empirical trial-and-error that if you focus exclusively on the practical side and not the personal side, it will deteriorate or fall apart.”

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• Decoding AI Beliefs and Behaviors in Four Classes of Workers

How AI Psychology Plays Out in the Workplace

Without considering the psychological elements playing into workers’ AI use or lack thereof, managers may misinterpret elevated AI utilization metrics as a success story without stopping to consider whether their teams’ tool usage is rooted in fear rather than true buy-in — a distinction that will chip away at outcomes longer-term, said Erin Eatough, a professor of organizational psychology at Michigan State University and Fractional Insights’ co-founder and chief science officer.

In fact, AI anxieties in the workplace (for instance, concerns about being replaced by someone more familiar with AI, or fear that AI may cause others to believe they don’t bring unique value to their role) can sometimes increase workers’ use of the tools — even as their resistance increases, Eatough noted.

“Fear about job loss or obsolescence can drive compliance and even heavy usage, but it doesn’t produce real innovation or commitment,” she said. “The behavior is performative rather than participatory. Dashboards look great, but [return on investment] doesn’t follow.”

Rather than overt resistance, Smith explained the manifestation of AI anxiety in the workplace is often cautious usage, guarded experimentation or defensive utilization that focuses on protecting the employee rather than transforming their work.

To tackle fears among these employees, reiterate that they’re being asked to use AI tools to deliver stronger value, not to be replaced by them — and for those who are indifferent, set pragmatic expectations for use that help them see how it can impact their results, Tamanini said.

Some additional research paints a more positive experience: A recent survey by work management platform Slingshot found 86% of surveyed employees believe AI will make their work better in some way. But when that belief is paired with a robust sense of job security, it can create issues as well, leading to unchecked use without guardrails or accountability.

“Leaders who assume high enthusiasm means everything is fine are often surprised when problems emerge downstream,” Eatough said.

Still, don’t quash those workers’ enthusiasm, Tamanini cautioned. Instead, corral that energy and offer them a view of AI’s implications beyond their role, and empower experimentation within clear parameters, he said.

The Role Leaders Play

One surprising finding Eatough noted in their study was that age, gender and years of work experience had no correlation with AI attitudes, but leadership transparency and trust did.

For example, the study by Ferrazzi Greenlight and Fractional Insights found:

• High AI angst was 60% to 70% less of a concern in transparent workplace environments.
• Workers who trusted their leadership reported 31% less AI anxiety.
• Employees who said they felt heard at work were three times more likely to see the value in AI.

“Leaders calm anxiety when they make the future role of the human more credible, create psychological safety for experimentation and openly acknowledge the real risks people feel, instead of trying to talk them out of [those risks],” Smith said.

Tamanini pointed to a “ready- fire-aim” approach many leaders take when it comes to AI — jumping in before a solid foundation is built. Bringing the human element back into the equation and explaining to team members how AI tools will augment the value they bring rather than replacing it is key, he said.

To boost AI implementation in a way that feels psychological safe, Tamanini said leaders should understand the organization’s goals and governance around AI use, and create a strategy for their team and communicate it in a way that clearly lays out expectations.

“One really important way a leader can help to dispel myths about AI — whether those myths are positive or negative — is by doing it themselves,” he said. “It can’t be a ‘do as I say, not as I do’ type of situation. They have to demonstrate the same types of things they’re asking their team to do to help build trust, build momentum and encourage it diplomatically.”

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