Performative AI Use Masks Gap in Workplace Adoption: Study

What happened

A new study from workforce analytics firm Visier finds that many employees are adopting AI tools primarily to signal compliance with leadership directives, rather than because the tools are improving how they work. According to reporting from CIO Dive and HR Dive, the research links this "performative" AI use to broader pressure employees feel as their roles shift in response to generative AI mandates from the top of their organisations.

The findings suggest a gap between how leadership frames AI adoption — as a strategic imperative tied to productivity and competitiveness — and how employees actually experience it: as an expectation to be seen using AI tools, whether or not those tools are embedded meaningfully into daily work. The reporting frames this as a symptom of top-down rollout approaches that prioritise visible usage metrics over genuine workflow integration.

Why it matters

For organisations investing heavily in generative AI rollouts, the study points to a measurement problem: usage statistics and adoption dashboards may be capturing compliance theatre rather than real behavioural change. If employees are using AI tools to be seen doing so, rather than because those tools solve a genuine problem, the return on AI investment will lag well behind the reported adoption figures — and the risk of quiet, undetected non-adoption grows.

The research also surfaces an employee-experience dimension to AI transformation that often gets overlooked. Role change driven by AI mandates creates uncertainty, and employees under that kind of pressure tend to default to visible, low-risk compliance behaviours rather than experimentation. That has direct implications for how transformation leaders design rollouts, set incentives and measure success.

The Renascence take

This is a textbook behavioural-economics problem dressed up as a technology rollout. When leadership mandates a tool without addressing the incentive structure beneath it, people will optimise for the metric being watched — not the outcome being sought.

Most organisations are measuring AI adoption the way they measure compliance training completion: logins, clicks, seat utilisation. That tells you who is performing for the dashboard, not who is actually getting value. The fix isn't a better mandate — it's redesigning the incentive so that using AI well is rewarded more visibly than using it at all. If a transformation programme can't tell the difference between genuine adoption and performative adoption, it isn't measuring the right thing, and it's about to discover that the hard way when the productivity gains fail to show up.