Harnessing artificial intelligence for environmental sustainability via human capital and renewable energy

In the current era, the role of artificial intelligence is considered important in many aspects not only for environmental sustainability but also for sustainable development in general. Considering the importance of artificial intelligence, this study aims to investigate the impact of artificial intelligence on carbon emissions for a group of twenty-one panel countries by using data from 2010 to 2020. The study employed second-generation panel data econometric tests with nonparametric panel data tests for estimations. The results highlighted that the role of artificial intelligence is crucial for achieving a sustainable environment, as its coefficient is negative for all three models. Specifically, AI has a negative and significant influence on CO2 emissions in Model 1 but a nonsignificant influence in Model 2 across quantiles. A 1% change in the AIPTNTS will cause a decrease in CO2 emissions of -0.009 in Q25, -0.047% in the median quantile, -0.13% in Q75 and - 0.18% in Q90, with a high significance of 1% in Model. This finding suggests that AI largely reduces CO2 emissions in high-carbon-emitting economies. Moreover, income causes carbon emissions to increase; however, the nonlinear term of income curbs carbon emissions, confirming the environmental Kuznets curve (EKC) hypothesis. The effects of human capital, clean energy and renewable energy on carbon emissions are negative, i.e., they help to decrease carbon emissions. The interactive or joint effect of artificial intelligence and clean energy electricity output also helps to decrease carbon emissions in selected countries. In terms of policy recommendations, the study encourages investment in artificial intelligence, increasing the share of clean energy and renewable energy electricity in total energy shares and investment in human capital to achieve a sustainable environment.