Most employees are using AI at work, but companies have failed to explain why. A new study from Culture Amp, surveying about 112,000 employees across more than 100 companies, found that 85% of workers are actively encouraged to experiment with AI tools. Yet only 58% said their leaders communicated the reasons behind AI implementation, and just 60% said managers shared concrete examples of how AI supports their work.
The gap between adoption and direction signals a leadership problem. Amy Lavoie, vice president of people science at Culture Amp, put it bluntly: "Employees are telling us they understand the risks, they are using the tools, and they feel more productive. That is not a workforce resisting change. That is a workforce that has done its part and is waiting on leadership to do theirs."
The productivity paradox
AI tools make workers feel more capable. The report found that 71% of all employees and 93% of heavy AI users said the technology made them feel more productive. But that feeling does not match measurable output. When asked about their actual workloads, 69% of nonusers and 72% of heavy AI users reported having reasonable workloads - numbers that are essentially identical. This suggests a disconnect between perceived capacity and real results.
Lavoie said companies paying for AI need to reexamine their return on investment. "The organizations that see a genuine return on AI over the next twelve months won't be the ones with the highest adoption rates. They'll be the ones that decided, explicitly, what they were going to stop doing with the time it gave back."
For HR leaders and executives building workforce strategy, structured training can help bridge the gap between tool access and purposeful use. AI VP HR Courses offer frameworks for aligning AI adoption with measurable business outcomes, rather than treating usage metrics as the goal itself.
Power users are motivated, not just metrics
Heavy AI users represent more than a data point on an adoption dashboard. The report found this group is actively finding ways to use AI and feels more motivated to contribute. Treating them as simply another measure of AI usage risks overlooking what makes these employees different. Companies that understand what drives power users can replicate those conditions across the broader workforce.
Risk awareness also tracks with usage. Overall, 86% of employees said they understand the risks of using AI. That figure climbs from 67% for nonusers to 95% for power users, suggesting hands-on experience builds practical judgment about the technology's limits and dangers.
Career uncertainty is rising
Employees are growing less certain about their futures. The report found that understanding of internal career opportunities dropped 10 percentage points since July 2025 - the largest single-year change in the data set. Career development satisfaction has stayed flat at 66% since 2021. Workers know AI is reshaping roles, but they do not know what that means for their own paths.
Lavoie addressed the leadership silence that often follows uncertainty. "Leaders are being asked to explain a future none of us can see clearly yet. We do not know with certainty which roles AI reshapes, which skills hold their value, or what a career path looks like three years out. As a result, leaders may go quiet, because saying nothing feels safer than saying something that turns out to be wrong. The most useful thing a leader can do right now is admit the plan is unfinished, and then keep talking anyway. Certainty is not what employees need from you right now. Candor is."
Managers face their own measurement challenges. A separate report from talent management firm Talogy found that 78% of people struggle to assess AI skills because current frameworks offer insufficient guidance. AI for Managers Courses can equip leaders with the evaluation tools they currently lack.
Why this matters for executives and HR leaders
Adoption numbers look good on a dashboard, but they hide a strategic vacuum. When most of your workforce uses AI without understanding why, you are funding experimentation without direction. The immediate priority is not driving usage higher - it is defining what work stops. If AI gives time back and nobody reallocates it, the ROI equation collapses. Leaders who communicate candidly about an unfinished plan will retain more trust than those who say nothing while waiting for certainty that will not arrive.
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