AI Technology Intensity, Gendered Labor Structure and Gender-Inclusive Sustainable Development: A Firm–Household Model and Panel Evidence from 58 Countries

This study examines how AI development and the labor force’s gender structure jointly influence female employment and female’s economic contributions from a dual-sector firm–household perspective. Using panel data from 58 countries spanning 2000–2022, we construct a theoretical model and conduct empirical tests. Results indicate that the labor force’s gender imbalance significantly suppresses the scale of female employment and female economic contributions; at the current stage, AI generally exerts a negative impact on female employment and economic contributions, but exhibits a significant interaction with the labor force gender structure. In scenarios of severe gender imbalance, AI’s skill-restructuring effect partially mitigates these adverse impacts; AI also generates a limited “time-release effect” by reducing women’s time spent on household labor, indirectly promoting female employment. The gendered effects of AI exhibit pronounced institutional variations across different developmental stages and gender structure conditions. This study emphasizes that AI is not a gender-neutral technology; its fairness depends on institutional and structural environments. Accordingly, it proposes policy recommendations, including improving multi-tiered systems for female talent development, guiding gender-inclusive AI applications, and strengthening global gender–governance cooperation.