29% of Workers Admit Sabotaging Their Company's AI Strategy

Nearly a third of employees—29%—admit to actively sabotaging their company's AI strategy, and among Gen Z workers the figure jumps to 44%. That's the headline finding of an April 2026 survey of 2,400 knowledge workers across the U.S., U.K. and Europe, including 1,200 C-suite executives, conducted by Writer and Workplace Intelligence and reported by Fortune.

The workplace resistance tracks a broader political shift. The 2026 midterms, as political strategist Rob Flaherty put it on the podcast Machine Gods, showed voters are "mad at" AI. "The story people are saying to themselves is, '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,'" Flaherty said. An NBC exit poll found 56% of voters called AI and data centers a "crucial or major factor" in their congressional vote.

The sentiment numbers are stark. Data tracked on Blood in the Machine shows office worker sentiment toward AI fell from 81% positive in 2019 to 43% positive—53% negative—by 2026, with "force-fed tools" cited as a major grievance. A Gallup global study reported 74% of Americans worry about AI, driven by anxiety over job obsolescence and automated layoffs.

What does this change for managers?

Plenty. Those fearful voters are the same employees being asked to "transform" their work lives with AI. Someone who voted against fast-moving AI on Tuesday isn't likely to experiment with it at scale on Wednesday. Humans carry a negative bias toward uncertainty, and the AI future is the ultimate uncertainty. The election result wasn't a call to stop AI entirely—it was a demand to pause and talk.

That means the resistance isn't a willpower problem. In Robert Kegan and Lisa Lahey's Immunity to Change framework, when we can't make a change we genuinely want, some part of us is quietly committed to the opposite. Kegan calls it a psychological immune system—one foot on the gas, one on the brake. When change feels unsafe, the brain and nervous system conspire to preserve the status quo, often run by anxiety.

AI arrived too fast, too soon, too much. In his new book Our Existential Advantage, Enrique Rubio argues every major technological revolution teaches the same lesson: things change—but the printing press took decades to spark the Renaissance and Enlightenment. AI is happening almost overnight, and the structures built on old technology can't keep up, nor can people.

The threat feels real because it is. Scholar Ziyaad Bhorat identifies three abilities worth protecting from AI: work, knowledge and understanding, and decision-making—including the right to keep skills from atrophying and being substituted by machines.

How to have the right AI conversations

On the Changing Conversations podcast, hosted by Katherine Cotter and Stig Albertsen of consultancy Implement, the case was made for conversations that acknowledge AI's fundamental paradox—we like what it does and we fear it—without needing clear next steps or defined outcomes.

Most workplace AI talk is technical: opportunity, rollout, proficiency. Many people fear that admitting hesitancy makes them look un-innovative. The irony: when you're feeling stuck, you're not as innovative.

Two questions start the process:

• "When I think of my craft, what makes me feel proud, fulfilled, purposeful?"
• "Does the implementation of AI change anything about this?"

Albertsen frames the opportunity 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?"

Further prompts for teams:

• What do I love about AI? What has surprised me?
• What parts of my job do I dislike and wish AI would take?
• What parts do I love and never want AI to touch? Why do they matter so much?
• What scares me about AI?
• What values are underneath all of that?

Practical ground rules: the leader goes first and admits their own messiness. Expect the first few minutes to feel weird. Don't attach a productivity goal. Make room for both/and, as scholar Wendy Smith would put it—the most common reaction being some version of "I love it, it helps me so much, and I'm really worried about my kids."

For employers pushing AI adoption, the message from voters and workers alike is that the conversation itself—naming the emotions, not just shipping the tools—is where transformation actually starts.