Aging Economies and AI Adoption: Firm-Level Evidence from the World Bank Enterprise Surveys

Ha Minh Nguyen

No 2026/176, IMF Working Papers from International Monetary Fund

Abstract: How do demographic trends shape the adoption of AI and automation technologies? This paper provides the first large-scale cross-country firm-level test of the demographic–automation hypothesis using World Bank Enterprise Surveys data covering 89,380 firms across 144 countries from 2022 to 2025. I classify adopters by applying a large language model to firms’ open-ended process innovation descriptions, identifying 1,656 AI and automation adopters (1.9 percent of the sample). A ten-percentage-point increase in the old-age dependency ratio raises process adoption probability by approximately 0.6 percentage points, after accounting for countries’ income levels, digital infrastructure, firm size and sector, and broad regional and time differences. The result is robust across specifications and supported by an instrumental variable strategy based on predetermined demographic cohort structure. Heterogeneity analysis shows the effect concentrates in manufacturing, large firms, and developing economies for the broad adoption measure; restricting to firms with explicit references to AI reverses the sector pattern, with services firms significantly more likely to adopt than manufacturing firms, pointing to distinct sectoral profiles for software-based AI and hardware-based automation. Aging also predicts firms’ development of AI-enabled products across both manufacturing and services. The results indicate that demographic aging shapes AI and automation adoption through both process and product innovation channels: firms substitute technology for increasingly scarce and costly labor in production, and separately develop AI-enabled products for labor-constrained customers.

Keywords: Aging; automation; artificial intelligence; firm-level; technology adoption; labor-saving technology; World Bank Enterprise Surveys; demographics; labor substitution (search for similar items in EconPapers)
Pages: 59
Date: 2026-08-21
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