Artificial Intelligence and Progress Toward SDGs 7 and 13: Evidence From BRICS Economies

ABSTRACT The BRICS economies account for about 40% of global carbon emissions owing to their fast‐paced industrialization while the importance of the role of artificial intelligence for boosting efforts made toward reaching SDG 7 and SDG 13 is not supported by sufficient empirical works in the field of emerging economies. Thus, it creates an important knowledge gap for the evidence‐based design of policies. The objective of the paper is to assess the impact of technology‐related AI capacity on both the renewable energy transition and environmental efficiency across BRICS countries from 2000 to 2024. The authors apply a balanced panel dataset for five BRICS nations and employ a multi‐stage econometric analysis based on Directed Technological Change Theory and the Environmental Kuznets Curve while controlling for cross‐sectional dependence and slope heterogeneity through the use of second‐generation unit root tests, cointegration tests, and long‐run estimation through GLS with a robustness check using PCSE. The results show that investment in R&D boosts environmental efficiency significantly, while high‐tech exports have a negative impact due to the dual nature of technological progress. As for renewable energy consumption, it is quite an important channel through which R&D affects environmental efficiency positively because renewable energy consumption exceeds R&D investment. Unidirectional causality from R&D to environmental efficiency and bi‐directional causality between GDP and environmental efficiency are found in the present research. According to the findings, AI is a powerful driver of SDG 7 and SDG 13 in the BRICS context, but success depends on policy decisions.