Organizational Transmission of AI: Managerial Influence on Generative AI Adoption

Christos A. Makridis

No 12373, CESifo Working Paper Series from CESifo

Abstract: Using longitudinal data from the Gallup Panel covering more than 30,000 U.S. employees surveyed from 2023 to 2025, I document heterogeneous adoption of generative AI and its "organizational transmission" within firms. First, I show that the share of active (occasional) AI users grew from 9% to 24% (10% to 23%). I subsequently document these patterns by organizational class of work, organizational hierarchy, income, industry, and occupation. Second, I show that perceived strategic clarity is the dominant correlate of frequent adoption: employees in clear-strategy organizations are roughly 26 percentage points more likely to report frequent use. Strategic clarity itself is tightly linked to managerial communication and credibility, including meaningful feedback and trust in leadership. Third, exploiting within-person variation, income-by-time controls, and a job-switcher design, I show that the relationship between AI use and worker outcomes is strongly contingent on organizational context. Frequent AI use is associated with substantially higher engagement and job satisfaction and with markedly lower burnout when organizations communicate a clear AI strategy, while these benefits are muted or reversed in low-clarity environments. These results are consistent with the predictions from a stylized theoretical model whereby workers are more likely to adopt and experiment with AI when they experience psychological safety.

Keywords: generative AI; technology adoption; managers; trust; communication; organizational complementarities; panel data (search for similar items in EconPapers)
JEL-codes: M15 M54 O33 (search for similar items in EconPapers)
Date: 2026
New Economics Papers: this item is included in nep-ain, nep-hrm and nep-ict
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