Almost every enterprise AI deployment in 2025 and 2026 has started the same way: executives sign off on the investment, the tools get provisioned, and the announcement goes out. What happens after that is a different story.
A survey of 1,200 employees and 1,200 C-suite executives by Writer and Workplace Intelligence found that 29% of enterprise employees admit to actively sabotaging their company’s AI strategy, rising to 44% among Gen Z. Workers enter proprietary data into public AI tools, deliberately generate poor outputs to discredit the technology, and refuse to engage with mandated platforms.
The generational angle has drawn the most attention. But the same report contains a finding that reframes the whole picture: 75% of executives admit their company’s AI strategy is “more for show” than a meaningful guide to outcomes. Which raises an obvious question about who is actually responsible for the mess.
The strategy problem starts at the top
The report identifies executive fear, not executive vision, as the primary driver of AI deployment right now. 73% of CEOs report anxiety about their organisation’s AI transition, and 64% fear losing their job if it fails. That pressure produces activity rather than strategy. Tools get deployed while the workforce is left to figure out what it all means in practice.
80% of enterprise workers avoid or actively reject AI mandates. In the past 30 days, 54% reverted to manual work. Another 33% have never touched the tools. 48% of executives describe their own AI adoption as a “massive disappointment”. Only 29% report significant ROI from generative AI, despite 97% of those same executives saying they have already deployed agents across their organisation.
Read more:
- Why AI Productivity Deployments Stall and How to Succeed Instead
- Forrester: Why Your AI Tools Might Be Making Things Worse
- Are AI Copilots Failing to Deliver Real Productivity?
Workers aren’t anti AI. They’re anti bad rollout.
One of the more revealing details in the report is that 80% of Gen Z workers say they trust AI more than they trust their managers. The generation most associated with resistance to enterprise AI has the highest confidence in the technology itself. What they lack confidence in is the way their organisations handle it.
That distinction matters. Tech friction now costs employees 51 working days per year, up 42% year-on-year. Active users report productivity gains of around 40-60 minutes per day. Poorly integrated tools, unclear governance, and what the report labels “workslop” consume most of that before it reaches any business metric. Workslop refers to AI-generated errors that require significant human effort to catch and fix. Gartner identifies it as organisations’ top productivity drain in its 2026 Future of Work Trends, with employees spending close to two hours resolving each incident.
When approved tools fail to meet user needs, workers find alternatives. MIT’s 2025 State of AI in Business report found personal AI accounts in use at more than 90% of companies. Only 40% of those companies hold official enterprise subscriptions for equivalent tools. The Writer survey adds that 67% of executives believe unapproved tool use has already caused a data breach at their organisation. That is not a workforce discipline problem. It is a procurement and strategy problem.
The super user gap is widening
None of this means AI is not delivering value. It means the value concentrates among a small group. According to the Writer survey, workers with genuine AI proficiency save nine hours per week, are five times more productive than their peers, and are three times more likely to be promoted. 92% of C-suite respondents say they actively cultivate an “AI elite” within their organisations, and the gap between that group and everyone else is growing.
Only 36% of workers say their employer gave them proper AI training. Just 26% understand even the basics of prompt engineering. PwC Global Workforce Leader Pete Brown made the implications clear in the firm’s 2025 Workforce Hopes and Fears Survey:
“Employees using AI every day are reaping the rewards. But to scale these benefits, businesses must go beyond training. Work itself needs to be redesigned.”
FOBO is real, but it’s not the whole story
FOBO, or Fear of Becoming Obsolete, is the anxiety driving many workers to resist AI adoption. It is grounded in real events. Challenger, Gray & Christmas recorded more than 165,000 tech layoffs in the past year. AI was the leading cause of cuts in March 2026, the first time that has happened since tracking began. 69% of executives in the Writer survey plan AI-related headcount reductions. Workers watching that happen are not being irrational.
But 26% of those who admitted to sabotage cited poor AI strategy as their reason, not job anxiety. They make judgement calls about the quality of what their organisations give them.
The Writer survey found 54% of executives say AI is “tearing their company apart”, next to the 97% who say they have already deployed AI agents. The tools are there. The strategy, by leadership’s own admission, largely is not. Until that changes, the resistance will continue, and it will be entirely rational.
