Why are workers so worried about AI? Listen to how tech leaders talk

The widespread fear among workers of being replaced by AI now or in the future has been well documented. Recent headlines about Block and Oracle and layoffs only amp up the worry among workers being asked to learn this new technology. And while some of the concerns about machines pushing humans out of their jobs might be a bit overstated, the anxiety is real.

This is why one of the biggest tasks facing technology leaders today is to address the fears and create effective strategies for getting employees to use AI tools despite whatever worries they might have about them.

“AI-related fear is persisting, and in many organizations, it’s intensifying, even as AI adoption accelerates,” said Jamie Shapiro, founder and CEO of Connected EC, a leadership coaching firm. “What’s amplifying AI fear is not what the technology can do, but how leaders frame its purpose and impact.”

When AI is consistently discussed in terms of cost savings, efficiency, doing more with less, or headcount reduction, employees don’t hear opportunity, they hear threat, Shapiro said. “That framing pushes people into survival mode, which undermines trust and shuts down curiosity, experimentation, and learning,” she said.

One of the most common fears Shapiro hears about is job displacement and expendability. “Not just ‘will my job change?’ but ‘will I still have a place here?'” she said. Others include loss of relevance or expertise; falling behind peers who adopt AI faster; evaluations on AI usage without training or clarity; and erosion of trust in organizations that value efficiency more than people.

The Future of Work and Employee Experience report from research firm International Data Corp. indicates that employee fears about AI are persisting but not uniformly worsening, said Amy Loomis, group vice president, workplace solutions at IDC. Concern about outright job loss remains a minority view and the larger anxiety is how work will change in an already uncertain macroeconomic environment, according to the report.

“Employee fears are far more complex than simply ‘AI will take my job,'” Loomis said. “Most expect AI to reshape their work rather than replace them entirely, and worries about job loss are often tied to broader economic pressures and hiring slowdowns rather than AI alone.”

As these types of concerns strike fear in employees, chief information officers, chief technology officers, and other technology executives need to take steps to address them.

One path is to directly address the impact of AI on roles and jobs. “Explain, by role, how AI is expected to reshape specific tasks over the next 12 to 24 months, and distinguish between automation, augmentation, and new work being created,” Loomis said. “Make concrete commitments on reskilling and internal mobility so employees see a path forward, not just risk.”

For example, tech leaders could publish role-based “AI impact briefs” summarizing which tasks are likely to be automated, which will be augmented, and what training and career pathways are available for each role, Loomis said.

Leaders can also demonstrate the tangible value of AI in everyday work. “Prioritize early AI use cases that clearly reduce low-value or repetitive work, so employees quickly experience benefits,” Loomis said. “Share simple before and after metrics and stories that show time saved and quality improved, positioning AI as a tool that makes the workday easier rather than a hidden performance test.”

It’s also vital to provide continuous upskilling and learning, Loomis said. “Move from ad-hoc, self-driven learning to structured AI upskilling embedded in the flow of work, with tailored paths for different roles and generations,” she said. “Provide microlearning, hands-on labs, and peer support so people can practice on real tasks without fear of failing in front of customers or senior leaders.”

CIOs and CTOs need to involve employees in co-designing AI-enabled workflows, pilots, and feedback loops to create a sense of shared ownership and reduce the sense that AI is being “done to employees,” Loomis said.

It’s also wise to reframe AI from being a potential eliminator of jobs to providing a pathway to new capabilities and opportunities. “Stop leading with efficiency and cost reduction,” Shapiro said. “Start with capacity and focus. When AI is positioned as taking low-value, repetitive work off people’s plates, employees stay in learning mode rather than defense mode. When leaders frame AI as a way to expand people rather than replace them, fear drops and real adoption begins.”

Consider starting slowly when adopting new AI-based products, despite whatever pressure there might be from senior executives to move quickly.

“Let people use AI before asking them to strategize about it,” Shapiro said. “Hands-on experience needs to come before [a] big-picture AI strategy. People can’t embrace or innovate with something they only understand abstractly. Personal use turns AI from a threat into a practical support.”

Finally, technology leaders also need to make AI accessible to a broad spectrum of users, not just limited to certain groups. “AI adoption stalls when tools are limited to IT, operations, or special innovation teams,” Shapiro said. “Broad access reduces fear, signals trust and normalizes experimentation.”