According to the Gensler Research Institute's Global Workplace Survey 2026, which surveyed 16,459 full-time office workers across 16 countries, 30 percent of employees now qualify as AI Power Users (defined as workers who regularly use AI tools in both their professional and personal lives). These workers spend 37 percent of their workweek working alone, compared to 42 percent for workers who have yet to adopt AI. They spend 1.5 times as much time learning as late adopters. And they report stronger team relationships, greater encouragement to share new ideas, and more meaningful friendships at work than their less AI-connected peers.
Here's what's actually happening: Managers have been operating under a flawed mental model of AI adoption. The dominant assumption — that AI tools would replace human interaction, isolating workers in individual productivity loops — does not match the behavior of workers who have gone deepest with the technology. AI Power Users are not working alone more. They are working alone less. The time AI frees from solo task execution is being redirected toward collaboration, learning, and relationship-building. What looks like a productivity tool is functioning, at scale, as a social reallocation mechanism.
Why it matters for you:
- Your AI-resistant employees are your most isolated ones. Late adopters in the Gensler data spend five additional percentage points of their workweek in solo work compared to Power Users. If you have team members who haven't engaged with AI tools, the risk isn't just a productivity gap — it's a connection gap. Employees working alone more are less attuned to what's happening across the organization and less likely to develop strong team relationships. Adoption resistance has social costs you aren't measuring.
- The return-to-office math just changed. Many organizations have been pushing in-person mandates partly to restore collaboration and team cohesion. The Gensler data suggests that AI adoption may be driving similar outcomes — AI Power Users report stronger team relationships despite spending more time in virtual collaboration. If your office strategy is built on the assumption that physical presence is the primary driver of connection, you're working from an outdated model.
- Learning capacity is now a workforce variable. AI Power Users spend 12 percent of their workweek on learning versus 8 percent for late adopters — a 50 percent gap. As AI tools continue to evolve, the compounding advantage of that extra learning time will widen. Workers who learn more, learn faster. Managers who treat AI enablement as an IT question rather than a workforce development question are letting their highest-potential employees drift toward late-adopter peers.
Source: Gensler Research Institute, Global Workplace Survey 2026 (16,459 respondents, 16 countries, data collected July–September 2025, published March 2026)
Watch this: The 30 percent Power User figure will not hold still. As AI tools become embedded in standard workflows, the threshold for what constitutes "regular use" will rise, and the Power User cohort will expand. Organizations that calibrate their office strategy and team development practices to the current 30 percent are building for a workforce that will look different within 18 months. The behavioral gap between adopters and late adopters will either narrow through organizational investment or widen through neglect.
The contrarian play: While competitors focus their AI strategy on productivity metrics and headcount efficiency, you can differentiate by measuring what the Gensler data actually shows matters: collaboration quality, learning time, and team relationship strength among AI adopters versus non-adopters on your own teams. If you find the same pattern — and the data suggests you will — you have a talent development case for AI enablement that is far more persuasive to skeptical employees than any efficiency argument.