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Managers as Gatekeepers in the Age of AI

Melbourne Institute of Applied Economic and Social Research

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Date Published
1 Apr 2026
Priority Score
3
Australian
Yes
Created
26 June 2026, 12:00 pm

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Abstract

Summary

This working paper examines the socio-technical barriers to AI adoption, identifying middle managers as critical gatekeepers who may impede the deployment of frontier AI systems. Through a randomized experiment in the US and UK, the authors demonstrate that information regarding AI's potential for labor displacement significantly reduces a manager's intention to adopt or advocate for the technology. While the focus is primarily economic, the findings highlight how human organizational dynamics can serve as a friction point against rapid AI scaling, which has implications for the pace at which potentially autonomous or high-risk systems are integrated into critical infrastructure and the workforce.

Body

Managers as Gatekeepers in the Age of AI Melbourne Institute Working Paper No. 02/26 Date: April 2026 Author(s): Cassandra Merrit Jacob Dominski Christopher Hoy Abstract Artificial intelligence (AI) is frequently cast as a transformative technology that will raise productivity while displacing human work, yet organizational adoption remains uneven and aggregate effects are mixed. We examine whether middle managers contribute to this gap by acting as gatekeepers to AI adoption. In a pre-registered survey experiment of 2,000 managers in the United States and United Kingdom, respondents were randomly assigned to view videos summarizing recent evidence on AI’s productivity benefits, its labor-displacing potential, or a placebo control. Exposure to information about labor displacement leads to a large reduction in intended AI adoption and advocacy (by 0.4–0.5 standard deviations) and a moderate reduction in staffing intentions (by 0.2 standard deviations). In contrast, information about productivity benefits has no significant average effect, although it increases advocacy among managers with low prior familiarity with AI. These findings indicate that middle managers’ responses to the information environment shape both technology adoption and employment intentions. Rather than inducing substitution away from labor and toward AI, information about AI’s labor-displacing potential leads managers to scale back both planned AI adoption and their staffing intentions. Download Paper (PDF)