Worklytics

Evan Franz, MBA

65% of employees say AI is improving their productivity. Only 14% strongly agree it has transformed how work gets done. Both figures come from Gallup's research on organizations that have implemented AI. That gap tells a bigger story than another rising adoption chart. Our Worklytics team just pulled together the latest AI adoption benchmarks and a few numbers really stood out. 52% of U.S. employees use AI at work at least a few times a year. But only 30% use it a few times a week or more, and just 15% use it daily. Now look at who's actually building those habits. In late 2025, 77% of technology employees reported some AI use, compared with 33% in retail. Among job levels, 69% of leaders used AI, versus 55% of managers and 40% of individual contributors. Employees in remote-capable roles were roughly 2x as likely to use AI as those in other roles: 66% vs. 32%. These aren't simply differences in enthusiasm. They're also differences in job design, access, and opportunity. Here's another number I can't ignore. Just 25% of employees said their organization had communicated a clear plan for AI use. Think about that. We're asking people to fundamentally change how they work while many still lack a shared understanding of where AI belongs. My takeaway is that companies are confusing 3 very different milestones: access, adoption, and impact. Access means someone can use AI. Adoption means they've made it part of their workflow. Impact means the work is actually getting better. A license doesn't prove a habit. A habit doesn't prove ROI. For leaders, I'd focus on 4 things: 1. Stop treating occasional use as meaningful adoption. Separate occasional, weekly, and daily users. A 52% adoption headline tells a very different story when only 15% are using AI every day. 2. Benchmark against comparable work. Industry, role, access, and job requirements matter. Comparing engineers with frontline retail employees without accounting for how their work differs won't tell you much. 3. Make managers part of the strategy. Gallup found employees with supportive managers are nearly 2x as likely to use AI frequently. Clear guidance and practical examples matter more than another company-wide announcement. 4. Connect usage to actual outcomes. Track whether AI is improving decision speed, quality, cycle times, customer service, and rework. Productivity should be visible in the work, not just the usage dashboard. The research combines different surveys, time periods, and definitions, so the percentages aren't all directly comparable. That's part of the lesson. AI adoption isn't one number, and higher usage doesn't automatically mean better performance. The real opportunity is understanding where AI has become part of everyday work, where adoption gaps exist, and whether those investments are producing measurable business value. That's where AI measurement needs to go next. https://lnkd.in/e5mYB4pZ