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.
