Decarbonizing the U.S. Economy through Artificial Intelligence and Information Technology: An Empirical ARDL Analysis

Climate change has become one of the most paramount threats to a sustainable world, and therefore, this requires the development of sophisticated technological and financial strategies to become carbon neutral. This research study discusses how innovations in artificial intelligence (AI), stock market development, adoption of information and communication technology (ICT), economic growth, and population dynamics have affected carbon emissions in the United States between 1990 and 2021. Using the Autoregressive Distributed Lag (ARDL) model and Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) estimators, the analysis establishes short-run and long-run associations between the variables chosen. The results of this study indicate that economic growth, capitalisation of stocks in the market, and population increase contribute greatly to carbon emissions, but the innovation of AI and diffusion of ICT decrease the emissions considerably in the long term. The diagnostics of robustness test or prove the reliability of the models, and there are no problems with serial correlation or heteroscedasticity. These results underscore the twofold nature of digitalisation and financial development in building environmental sustainability. The paper emphasizes that policies that foster AI-based energy optimisation, sustainable financial operations, and environmentally focused technological invention are needed to facilitate the American journey of achieving carbon neutrality.