Exploring impact of AI-robotics, energy transition, energy utilization, and economic growth on environmental degradation: Evidence from leading Asian countries by KRLS model

Compatible with the increasing common interest of countries on the environmental issues and recently increasing phenomenon of artificial intelligence (AI), the study investigates energy-related carbon dioxide emissions by considering energy transition, energy consumption (EC) sub-types, and economic growth in leading three Asian countries (namely, China, Japan, & Korea) as the countries having the highest operational stock in AI robotics. In this vein, the study employs a novel kernel regularized least squares (KRLS) model on yearly data from 2000 to 2019 to uncover the marginal impact. The results show that (i) AI robotics has only a reducing impact on the emissions at 0.25th percentile, whereas it is ineffective across remaining percentiles; (ii) energy transition, fossil EC, and economic growth are completely ineffective to ensure a reducing impact; (iii) renewable EC is beneficial at 0.25th percentile in China while it completely beneficial (ineffective) in Japan (Korea); (iv) interaction of AI with fossil (renewable) EC is beneficial for Japan at 0.25th (all) percentiles; (v) interaction of AI with energy transition is helpful for China and Japan at 0.25th percentile; (vi) KRLS model presents successful estimation results around 99.7%; (vii) the results are robust based on alternative indicator use (i.e., ecological footprint); (viii) the variables considered have varying marginal impacts across percentiles. Thus, the study suggests the inefficiency of AI robotics except for some lower percentiles, whereas renewable EC can be much more helpful to ensure a decline in emissions in the countries examined.