Advancing climate change resiliency through artificial intelligence: The moderating roles of resource efficiency, eco-productivity, and human capital in developed and emerging economies

Artificial Intelligence (AI) is central to the Fourth Industrial Revolution, with promising implications for various aspects of human activities. However, its potential to promote environmental sustainability through carbon emission reductions remains largely unexplored and debated. This study provides updated insights using panel data spanning 2012–2021 for 29 developed and 18 emerging economies. Empirical estimates derived from the Bayesian linear regression technique, implemented via Markov Chain Monte Carlo experiments, highlight the significant carbon emission-reducing effects of AI in both developed and emerging economies. Nevertheless, it is important to note that these effects remain tenuous in both contexts. The limited impact of AI is attributed to insufficient budgetary allocations toward carbon emission-reducing AI tools. Therefore, increased investments in these technologies are crucial to optimize their carbon mitigation potential, thereby fostering greater climate change resilience in these nations. Notably, the study reveals that AI has contributed more substantially to carbon emission reductions in developed economies compared to emerging ones. This disparity is linked to the relatively low financial commitments of emerging economies toward the deployment of carbon emission-reducing AI technologies. Additionally, the interaction of AI with resource utilization, human capital, eco-productivity, and income levels has demonstrated notable carbon emission-reducing effects. Although it is observed that these effects are more pronounced in developed countries. The study concludes by outlining specific policy recommendations to enhance the effectiveness of AI in mitigating carbon emissions across varying economic contexts. Remarkably, the inferences herein could apply to other economies.