A new study shows that calling AI agents "employees" or "coworkers" makes humans less careful about checking their work, not more productive. Researchers found people caught 18% fewer errors when an AI tool was labeled as an employee. As companies roll out AI agents in healthcare and government, this framing could obscure human responsibility for system failures.
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Research by Boston University professor Emma Wiles found that when AI agents are framed as "employees" rather than software tools, people catch 18% fewer errors in their work. Nearly a third of 1,261 managers surveyed said their companies already frame AI agents as employees, with some listing them on organizational charts.
Why it matters
When AI tools are labeled as coworkers, humans feel less responsible for their output and are 44% more likely to escalate questionable work to a manager instead of correcting it themselves—defeating the time-saving purpose of using the agent. As AI agents move into healthcare, warfare, education, and government, this dynamic risks creating a convenient place to blame failures that actually stem from human decisions and oversight.
What to watch
At Stanford, researchers asked 1,500 workers across 104 jobs which tasks AI could actually help with in their roles. Workers often rejected tasks that tech experts deemed most suitable for AI automation, suggesting a gap between what companies assume workers need and what workers themselves want from AI tools.
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