Research Information System
Sustainable Development, 2026 (SSCI, Scopus)
Artificial intelligence (AI) has become one of the main driving forces of transformation in the financial sector, while simultaneously generating significant implications for environmental sustainability and sustainable development processes. This study analyzes the effects of AI investments in the financial sector on CO2 and total greenhouse gas (GHG) emissions, as well as on Sustainable Development Goal 7 (SDG 7) performance. The analysis is conducted using data from 13 countries with sufficient data availability over the period 2014–2023, compiled from the OECD AI Policy Observatory, the World Bank's World Development Indicators (WDI), and the Sustainable Development Report. The empirical analysis employs Driscoll–Kraay standard errors and the method of moments quantile regression (MMQR) approach. In addition, the robustness of the findings against potential endogeneity is tested using the two-stage least squares (2SLS) method. The results indicate that AI investments in the financial sector have a statistically significant and negative effect on CO2 and GHG emissions, with this effect being more pronounced in countries with higher emission levels. In contrast, although the impact of AI investments on SDG 7 performance remains positive across both models, the findings provide only limited empirical support. Overall, the results suggest that AI investments in the financial sector can serve as an important tool for reducing environmental pressures. Accordingly, it is recommended that policymakers design financial digitalization processes in alignment with environmental objectives and integrate AI-based financial applications with sustainability-oriented strategies.