A new enterprise AI adoption survey from WRITER and Workplace Intelligence found that six in ten companies plan to lay off employees who cannot or will not adopt AI tools. The study, released April 7, 2026, surveyed 2,400 knowledge workers across the US, UK, Ireland, Benelux, France, and Germany, including 1,200 C-suite executives and 1,200 employees.

The finding lands differently than the usual AI-and-jobs narrative. This is not about AI replacing roles wholesale. It is about companies deciding which employees are worth keeping in an era where a motivated AI user can do the work of several people.

The Productivity Gap Is Real and It Is Growing

The survey quantifies what many business leaders have suspected: AI super-users are in a different productivity class entirely. Workers who fully embrace AI tools save nearly nine hours per week. Those who resist save around two hours. Over a year, that is roughly 360 additional productive hours per employee — before you factor in the quality difference.

Super-users are also three times more likely to have received a raise or promotion in the past year. That tracks. If someone on your team is producing five times the output of a colleague, it eventually shows in performance reviews.

Ninety-two percent of C-suite leaders say they are actively cultivating what the survey calls an “AI elite” — a core group of employees who have fully integrated AI into their daily workflows. The intent is clear: build around the people who get it, and reduce headcount among those who do not.

The Strategy Problem Is Worse Than the Adoption Problem

Here is the part that should concern business leaders more than the layoff stat: seventy-five percent of executives admit their company’s AI strategy is, in their words, “more for show” than actual internal guidance. Companies are buying tools and announcing AI initiatives, but very few have built real frameworks for turning those tools into revenue.

Only 29% of organisations report significant ROI from generative AI, despite the individual productivity gains. The gap between what employees can do with AI and what companies are actually capturing as business value is enormous.

Fifty-four percent of C-suite leaders said AI adoption is “tearing their company apart.” Thirty-nine percent have no formal strategy for generating revenue from their AI investments.

That is a governance problem, not a technology problem.

The Shadow AI Risk Is Already Materialising

Sixty-seven percent of executives said their company had experienced a data leak or security breach because an employee used an unapproved AI tool. Workers are not waiting for official rollouts. They are finding their own tools and using them, often with company data.

At the same time, 29% of employees admit to actively sabotaging their company’s AI strategy. That number rises to 44% among Gen Z workers, who cite distrust of how the technology will be used against them as the main driver.

Companies are caught in a bind: move too slowly and competitors get ahead. Move too fast without proper strategy and governance, and you create security and cultural problems that cost more to fix than the efficiency gains were worth.

What This Means for Business

The survey is a signal, not a verdict. The companies winning with AI right now are not the ones that announced the biggest AI strategy in 2024. They are the ones that invested in making their people genuinely capable with AI tools, built governance frameworks that keep data safe, and set clear expectations for what AI-enabled performance looks like. A separate MIT study published this month puts quantitative weight on the stakes: AI can already perform the work of 11.7% of the US labor market at an acceptable standard. The gap between organisations deploying that capability and those that are not is real and growing.

The productivity gap between AI super-users and laggards will not shrink on its own. It compounds. Every week that a team member resists adoption, the gap between them and an AI-capable peer grows. At some point, that gap becomes a business decision.

For companies navigating this, the practical steps are unglamorous: identify your current AI super-users, understand what they are doing differently, and build structured programmes to replicate those behaviours across the team.

For individuals, the math is simple. The survey shows AI adopters are getting promoted faster, earning more, and making themselves harder to replace. Getting fluent with AI tools is no longer a career differentiator. It is increasingly the baseline.

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Enterprise DNA offers structured AI and data skills training for individuals and business teams through EDNA Learn. For organisations looking to build strategic AI capabilities across the business, Omni Advisory helps executive teams move from AI strategy theatre to real implementation.