Despite AI’s rapid progress of AI as a tool for equitable growth, little is known about how it can help to slow environmental damage. From 1996 to 2024, this study examined how the US’s ecological footprint is impacted by innovations in AI, energy use, economic development, industrialization, and growing populations. After confirming the mixed order of integration, the study applies the Autoregressive Distributed Lag (ARDL) method to evaluate short-term and long-term trends. Robustness was tested using three techniques: Canonical Cointegration Regression, Dynamic Ordinary Least Squares, and Fully Modified Ordinary Least Squares. The results show that the ecological footprint is positively affected by economic growth, increased energy consumption, industrialization, and population growth, all of which underline the environmental impacts of economic and demographic advancement. In contrast, AI innovation reduces ecological pressure, demonstrating its potential to optimize energy efficiency, encourage cleaner production, and enhance overall environmental quality. These results are consistent across both the short- and long-term calculations and robustness tests. This study contributes to the growing debate on technology and sustainability by positioning artificial intelligence as the key driver of ecological resilience. Policy implications stress the urgency of accelerating AI-driven green strategies, investing in renewable energy, and fostering sustainable industrial practices to balance economic progress with environmental preservation in the United States.
Ridwan et al. (Fri,) studied this question.