AiPhreaks ← Back to News Feed

15% of Americans say they’d be willing to work for an AI boss, according to new poll

By Jakub Antkiewicz

2026-03-31T08:59:11Z

A new Quinnipiac University poll indicates that 15% of Americans would be willing to work for an AI program as their direct supervisor, reflecting a growing, albeit still minority, acceptance of AI in management roles. The finding, published Monday, comes as companies increasingly experiment with automating supervisory and administrative tasks, moving the concept of an AI boss from a hypothetical scenario to an emerging operational reality for some workers.

The poll, which surveyed 1,397 adults in the U.S. between March 19 and 23, highlights a tangible trend in corporate strategy. While most respondents are not yet comfortable with the idea, major companies are already deploying AI to handle functions traditionally performed by human managers. For example, Amazon is using AI workflows to supplant certain middle management duties, and Workday has introduced AI agents capable of approving expense reports. These applications demonstrate how specific managerial responsibilities are being systematically automated, creating a foundation for more comprehensive AI supervision.

This tentative acceptance of AI managers exists alongside significant anxiety about the technology's effect on the labor market. The same poll found that 70% of respondents believe AI advancements will ultimately reduce the number of available jobs for people. Furthermore, 30% of currently employed Americans expressed concern that AI could make their own positions obsolete. This data points to a fundamental tension in the future of work: while some see potential efficiency in AI-led management, a much larger portion of the public remains wary of its broader consequences for their economic security.

While the 15% figure represents an early adopter segment for AI management software, the more telling statistic is the 85% who are not, highlighting that the primary barrier to adoption is not technological feasibility but workforce trust and overcoming widespread job displacement fears.