Pathways to Carbon Neutrality in the United States: Evaluating Private AI Investment, Financial Development, and Macroeconomic Forces

This study analyzes the impact of private investment in artificial intelligence (PAI) and financial development (FD) on carbon dioxide (CO₂) emissions in the United States as well as the contribution of foreign direct investment (FDI), economic growth, and population growth. The analysis uses the annual data of 1996-2022 to test the short- and long-run dynamics using the STIRPAT framework with the ARDL bounds testing technique. The ARDL methodology is confirmed through unit root analyses, which support the presence of a mixed-order integration. The findings indicate that GDP, FDI, and population growth serve as principal factors influencing CO2 emissions in both the short and long term, thereby suggesting that environmental pressures persist amidst economic and demographic progression. In contrast, PAI has a negative and statistically significant impact on emissions, which underscores the prospects of developed technologies to increase energy efficiency and contribute to environmental sustainability. FD also helps minimize emissions in the long run, which highlights the beneficial impact of financial systems in facilitating cleaner patterns of investment. Further, the results of Granger causality indicate numerous unidirectional relationships, especially between GDP, PAI, FDI, population and CO₂ emissions.