<scp>AI</scp> Adoption and Sustainable Development in Advancing <scp>SDG</scp> 9 and <scp>SDG</scp> 13 in Emerging Economies: Evidence From the <scp>E7</scp>

ABSTRACT Artificial intelligence (AI) adoption is increasingly viewed as a driver of productivity and competitiveness, yet its sustainability implications remain underexplored, particularly in emerging economies where environmental constraints and digital gaps persist. This study examines how supply chain digitization (SCD), globalization, environmental pressures, green technologies, and energy structure jointly shape AI adoption in the E7 economies over the period 2000–2022. Using Method of Moments Quantile Regression as the baseline model, the analysis captures heterogeneous effects across different adoption levels, while robustness is ensured through alternative quantile specifications. The results reveal that SCD consistently promotes AI adoption, whereas carbon emissions hinder adoption at lower quantiles. Environment‐related technologies and cleaner energy structures mitigate these constraints, enabling more sustainable diffusion of AI. Globalization contributes positively only when absorptive capacity is sufficiently developed. These findings suggest that AI strategies in emerging economies must be aligned with green technology investment, clean energy transitions, and digital infrastructure development, directly supporting Sustainable Development Goals 9 and 13.