Managers as Gatekeepers in the Age of AI
Melbourne Institute of Applied Economic and Social Research
ENRICHED
Details
- Date Published
- 1 Apr 2026
- Priority Score
- 3
- Australian
- Yes
- Created
- 26 June 2026, 12:00 pm
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)