Artificial intelligence investment and renewable energy for environmental sustainability in ASEAN-5 under the foreign direct investment threshold

This study examines the nonlinear and regime-dependent interactions among economic growth, artificial intelligence investment, renewable energy consumption, and environmental degradation in the ASEAN-5 nations, with foreign direct investment (FDI) acting as a pivotal transition variable. The application of a Panel Smooth Transition Regression (PSTR) paradigm yields compelling evidence against linearity and endorses a single-threshold specification across many environmental variables, such as carbon emissions, carbon intensity, and greenhouse gas emissions. The results indicate that the environmental effects of economic and technological factors differ markedly among FDI regimes. Under low-FDI conditions, economic expansion is associated with greater environmental deterioration, whereas the impacts of investment in artificial intelligence and renewable energy are minimal and statistically insignificant. Conversely, when foreign direct investment surpasses a certain threshold, the dynamics change significantly. Economic growth increasingly harms the environment, whilst investment in technology and renewable energy begins to significantly alleviate environmental damage. These results underscore the dual function of FDI as both a catalyst that exacerbates the environmental costs of economic growth and a driver of green technologies and innovation. This study elucidates threshold-driven nonlinearities, thereby advancing the existing literature on sustainable development and offering significant policy insights for emerging economies striving to reconcile economic growth with environmental sustainability.