📝 SummarXiv

Abstract

This study investigates the impact of artificial intelligence (AI) adoption on job loss rates using the Global AI Content Impact Dataset (2020--2025). The panel comprises 200 industry-country-year observations across Australia, China, France, Japan, and the United Kingdom in ten industries. A three-stage ordinary least squares (OLS) framework is applied. First, a full-sample regression finds no significant linear association between AI adoption rate and job loss rate ($\beta \approx -0.0026$, $p = 0.949$). Second, industry-specific regressions identify the marketing and retail sectors as closest to significance. Third, interaction-term models quantify marginal effects in those two sectors, revealing a significant retail interaction effect ($-0.138$, $p < 0.05$), showing that higher AI adoption is linked to lower job loss in retail. These findings extend empirical evidence on AI's labor market impact, emphasize AI's productivity-enhancing role in retail, and support targeted policy measures such as intelligent replenishment systems and cashierless checkout implementations.