Digital and sustainable synergies: Insights into green investment, technological innovation, and low-carbon economies

Climate change and rapid depletion of the environmental resources pose critical threat to world economies, particularly to those who are heavily dependent on fossil fuels. The United States (US), as one of the leading carbon emitters, requires innovative strategies that integrate technology, policy, and investment to transition toward the sustainable low-carbon economy. Against this backdrop, this study examines how artificial intelligence (AI), carbon pricing mechanisms, and the green investment collectively influence energy transition and long-term emission reduction pathways. The study examines US time-series data from 1990 to 2022 using a combination of econometric modeling, such as the Autoregressive Distributed Lag technique and the Augmented Dickey–Fuller test, and Bayesian neural network forecasting. According to the findings, a 1% increase in the use of renewable energy lowers carbon emissions by roughly 0.033% in the short term. Long-term estimates, assuming continued investment in carbon pricing and technological advancement, imply a 15% reduction in emissions by 2040. Furthermore, it is anticipated that over the course of two decades, AI-driven research and development integration will increase renewable energy efficiency by 18%. In addition to offering evidence-based insights for policymakers looking to align economic and environmental goals through digital innovation and sustainability policy frameworks, our findings highlight the revolutionary potential of AI in strengthening climate mitigation initiatives.