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From digital advancement to SDGs disruption: How artificial intelligence without inclusion threatens sustainable
Shunhao Mai1, Lingli Qing2, Usman Mehmood3
1School of Accounting, Guangzhou College of Technology and Business, Foshan, 528135, China.
Abstract:
Sustainable development remains a critical priority under the United Nations 2030 Agenda, and the G7 economies-Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States-play a pivotal role due to their economic influence, technological leadership, and environmental responsibility. This study investigates the long-run determinants of sustainable development in the G7 from 1995 to 2022, using the Sustainable Development Index (SDG) as the dependent variable. Six explanatory factors are considered: artificial intelligence adoption (AI), women's entrepreneurship (FEM), technological intensity (TEC), global warming (SUR), income inequality (INI), and unemployment (UNM). The empirical strategy employs Fixed Effects estimation with Driscoll-Kraay standard errors, validated through the Hausman test, and complemented with Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators for robustness against cross-sectional dependence and slope heterogeneity. The results reveal that AI exhibits a negative association with the SDG index under the baseline model, underscoring the risks of digital transformation without inclusive policies, though AMG suggests a potential positive effect under heterogeneous country conditions. Women's entrepreneurship, while positively signed, is statistically insignificant, indicating persistent structural barriers in the G7. Technological intensity consistently demonstrates a positive and significant impact, highlighting the role of advanced industrial innovation in driving sustainability. Rising surface temperatures exert a weakly negative effect, reaffirming climate change as a threat to long-term development. Income inequality remains statistically insignificant but directionally adverse. Unemployment shows a strong and positive association across all estimators, reflecting structural labor market adjustments during the transition toward greener and more sustainable sectors. This study contributes to the literature by integrating digital, social, economic, and environmental dimensions within a robust econometric framework tailored for high-income economies. Policy recommendations emphasize inclusive digital transformation, stronger support for women-led enterprises, investment in clean technologies, proactive climate action, and labor market policies that align green transitions with social equity.
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