Workers Report Skill Atrophy Amid Heavy AI Use
Skill atrophy and over-reliance risks are live workforce-AI governance questions for APS agencies deploying task-assistive AI tools.
Key points
- GoTo-commissioned survey of 2,500 global workers finds 39% report AI use has weakened their skill sets.
- Nearly one in four IT leaders report AI-related mistakes have already affected customers or the bottom line.
- Survey is vendor-commissioned and measures self-reported perceptions, not objective skill decline - treat with appropriate caution.
Implications for Australian agencies
- Consider APS workforce and AI governance teams could consider whether current AI deployment frameworks include mechanisms to monitor staff over-reliance and maintain human judgement independent of tool outputs.
- Monitor Agencies may want to monitor emerging research and peer-reviewed studies on cognitive offloading to supplement vendor-commissioned survey findings on this topic.
Implications are AI-generated. Starting points, not advice — see methodology for how they're framed.
View original source
Copied.
Appeared in:
Weekly digest, 18 May 2026
"Workers Report Skill Atrophy Amid Heavy AI Use"
Source: Let's Data Science – AI Governance
Published: 22 May 2026
URL: https://letsdatascience.com/news/workers-report-skill-atrophy-amid-heavy-ai-use-783735aa
A survey commissioned by IT firm GoTo of 2,500 global workers and IT leaders found 82% of workers use AI on the job, with 39% reporting that AI reliance has weakened their skills and 28% now trusting AI more than themselves. Roughly one in four IT leaders said AI-related mistakes had already affected customers or business outcomes. The findings are self-reported and vendor-commissioned, limiting causal inference, but they surface a pattern relevant to APS workforce AI governance: high adoption coexisting with measurable worker anxiety about competence erosion and documented error propagation in human-machine workflows.
Implications for Australian agencies:
- [Consider] APS workforce and AI governance teams could consider whether current AI deployment frameworks include mechanisms to monitor staff over-reliance and maintain human judgement independent of tool outputs.
- [Monitor] Agencies may want to monitor emerging research and peer-reviewed studies on cognitive offloading to supplement vendor-commissioned survey findings on this topic.
Retrieved from SIMS, 18 July 2026.