Workers Report Skill Atrophy Amid Heavy AI Use

According to HR Dive, a survey commissioned by IT firm GoTo of 2,500 workers and IT leaders found extensive workplace AI adoption and notable worker concern. The report found 98% of IT leaders reported their company was using AI and 82% of workers said they used AI on the job. The survey measured negative impacts on worker confidence: 39% of all workers and 46% of Generation Z respondents said reliance on AI had weakened their skill sets and made them feel less intelligent. The survey also found about 3 in 10 workers think AI is better at their jobs than they are and 28% now trust AI more than themselves. HR Dive reports that nearly one in four IT leaders said AI-related mistakes "have already affected customers, clients, or their companys bottom line."

Industry-pattern observations: widespread adoption of task-assistive AI tools commonly produces measurable cognitive offloading, where routine decision-making and retrieval tasks are delegated to tools. Peer-reviewed work (see related literature) documents that persistent offloading can reduce exercise of domain-specific mental routines and critical-thinking prompts. For practitioners, this pattern means operational monitoring should track not only model performance but user reliance and error propagation in human-machine workflows.

Industry observers note a tension visible in the survey: high approval for organizational AI investment coexists with significant worker anxiety about skills erosion. Comparable surveys and academic studies have highlighted the same duality-productivity gains versus downstream competence risk-especially among younger cohorts who report higher reliance. This dynamic raises governance questions around training, certification, and usage boundaries for workplace AI, per HR Dive's reporting on the GoTo survey.

Indicators observers and practitioners should follow include: uptake of formal AI training programs by employers; adoption of usage policies or guardrails that limit automation for high-risk tasks; incident rates where AI errors propagate to customers; and changes in role descriptions or assessment criteria that measure human judgement independent of tool outputs. Monitoring these metrics can clarify whether organizations are coupling deployment with skills maintenance.

HR Dive reports these findings from the GoTo-commissioned survey. The survey results measure perceptions and self-reported behaviors, which capture sentiment and reported incidents but do not by themselves establish long-term causality between AI use and objective skill decline.