Artificial intelligence, green finance, and global economic cycles: Analyzing the role of AI, BRI, and the Paris Agreement

The further development of sustainability presupposes a holistic view of the interaction of artificial intelligence (AI) and green finance (GF) to affect the results of the environment and governance. This paper examines different dynamic interdependencies between GF, AI, and Environmental, Social and Governance Uncertainty Index (ESG UCI) through a Time-Varying Parameter Vector Autoregression model with Stochastic Volatility (TVP-VAR-SV). According to the results, GF will produce a steady market through substantially lowering ESG uncertainty. On the other hand, AI has an overall negative impact on the uncertainty of ESG in the initial stages of adoption (not including 2024–2025), of which its uncertainty significantly decreases under its maturity stage. In general, AI and GF both stimulate sustainability, but the impact of AI is delayed. Outside of the COVID-19 era, the positive effects of GF on AI development lead to the strengthening of green financial development. Comparative findings indicate that the TVP-VAR-SV model is more effective in modelling dynamic structural changes and creating more vigorous insights than traditional VAR models. Other robustness tests of alternative indicators and longer-range control variables further support the conclusions. The paper provides a policy brief to enhance the synergistic contribution of AI and GF to sustainable development in the context of increasing uncertainty in the world.