Why AI Adoption Stalls When Employees Feel Unsafe at Work

An April 2026 survey of 2,400 knowledge workers across the U.S., U.K. and Europe, including 1,200 C-suite executives, found that 29% of employees admitted actively sabotaging their company’s AI strategy; among Gen Z workers, the share reached 44%. Writer and Workplace Intelligence conducted the research, which Fortune reported.

An NBC exit poll found that 56% of voters said AI and data centers were a crucial or major factor in their 2026 midterm congressional vote.

Political strategist Rob Flaherty described the mood on his Machine Gods podcast: “This thing is in my backyard. It is being used to train stuff that’s gonna take my job away, and I get no say over any of this, and I’m really mad about that.”

Office-worker sentiment toward AI fell from 81% positive in 2019 to 43% positive in 2026, with 53% negative, according to Blood in the Machine; force-fed tools was a major grievance. Gallup’s global study found 74% of Americans worried about AI, driven by job obsolescence and automated layoffs.

These numbers describe a paradox, not rejection. People like how generative AI helps in daily life, yet fear what it does to work. Nobody knows what comes next, and that uncertainty drives resistance.

Many voters are also employees asked to transform their jobs with AI. On Election Day, they reclaimed agency over the technology; their employers need to hear the demand: pause and talk, not stop.

Why does AI adoption trigger resistance?

After decades as a political and advocacy consultant, I heard clients repeatedly ask why people would not vote for supportive candidates, exercise, or back policies that save money and improve health. The recurring answer: people are stuck.

Robert Kegan and Lisa Lahey’s Immunity to Change framework rejects a simple willpower explanation. When people cannot make a change they genuinely want, part of them is committed to the opposite; Kegan calls this a psychological immune system, with one foot on the accelerator and one on the brake.

When change feels unsafe, the brain, nervous system and body preserve the status quo. Anxiety often runs that protective system, turning an anticipated threat into freeze, fight or flight.

Enrique Rubio’s new book, Our Existential Advantage, argues that major technological revolutions teach the same lesson: things change. The printing press spread knowledge across Europe and helped spark the Renaissance and Enlightenment, but that took decades. AI is just as transformative, but arrives almost overnight.

AI’s speed leaves structures built for older technologies unable to keep pace, and leaves people feeling that it is inevitable and beyond their agency. Fears cover safety, livelihoods, children’s futures, values and meaning in work.

Employees have described AI as siphoning creativity and expertise or encouraging sloppiness and laziness. Money matters, but people also value agency, meaning and purpose; assigning decisions to AI raises questions about self-reliance, learning and usefulness.

Ziyaad Bhorat identifies three abilities worth protecting from AI: work, knowledge and understanding, and decision-making. Work includes the right to keep skills from atrophying or being substituted by machines.

What should leaders ask before deployment?

On the Changing Conversations podcast, hosted by Katherine Cotter and Stig Albertsen of consultancy Implement, I discussed why leaders need to make space and time for AI’s emotional paradox. The talks need no fixed outcome or immediate next step; they need to happen.

Technical conversations already cover opportunity, deployment focus, rollout and proficiency. FOMO drives the pace, while employees fear that admitting hesitation will mark them as unoriginal. When they feel stuck, they cannot innovate.

Most people are uncomfortable with emotions at work, yet those feelings shape decisions. Naming fear and uncertainty lets people process them, reduce the perceived threat and recover agency.

Start each discussion with two prompts:

• What parts of your craft make you feel proud, fulfilled and purposeful?
• Does implementing AI change any of that?

Unpacking the answers shows where AI aligns with a person’s values, threatens their craft, enhances it, or does both. It creates room to define an AI future before prescribing a rollout.

Albertsen put the human stakes this way:

AI…holds an invitation to figure out what is the uniqueness of being human, or even what is my unique gift….

Part of what I do can be handled by other means and supporting tools and technology, and that’s an invitation for me to figure out: What is it that cannot be distributed to someone else, because only I can do that with that specific flavor?

Which questions should teams work through?

Ask people which part of their craft they love most and what they are especially good at, then give them time to sit with the answer rather than rush to solve it.

Useful team questions include:

• What do you love about AI, and what has surprised you?
• Which parts of your job do you dislike and want AI to take?
• Which parts do you love and never want AI to touch, and why do they matter?
• What scares you about AI?
• What values sit underneath all of that?

The leader should go first and admit their own uncertainty. Expect awkward silences; people often look blank until the discussion reaches values or children, then something clicks. Do not attach a productivity goal, and allow both/and, as Wendy Smith puts it.

The most common admission combines genuine appreciation with fear for children. Hearing that others hold both feelings brings relief. The conversation matters most: there are no right answers, only an opening to get unstuck and move through change. Leaders who start there can turn AI adoption from a command into a conversation people can shape.