THE ENVIRONMENTAL IMPACT OF AI-DRIVEN INNOVATION: EVIDENCE FROM THEUNITED STATES
DOI:
https://doi.org/10.58225/sw.2026.1-34-43Keywords:
US, CO2 Emissions, AI-related patents, Economic Growth, Renewable Energy Generation, Sustainable DevelopmentAbstract
This study investigates how Artificial Intelligence (AI)-related patents, income, trade openness, renewable energy generation and energy intensity influence carbon dioxide (CO₂) emissions in the United States. The empirical analysis is conducted using Canonical Cointegration
Regression (CCR), Dynamic Ordinary Least Squares (DOLS), and Fully Modified Ordinary Least Squares (FMOLS) estimators. The empirical findings show that AI- related patents, income, trade openness, and energy intensity have positive and statistically significant effects on CO₂ emissions, where as renewable energy generation contributes to reducing emissions. Furthermore, the interaction term between renewable energy generation and AI-related patents is negative and statistically significant, indicating that renewable energy generation moderates the emissions increasing effect of AI-related technological innovation. This result suggests that the environmental implications of AI depend critically on the energy structure supporting its development and deployment. Accordingly, the study recommends that policymakers promote the integration of AI with renewable energy systems, reduce energy intensity in industry and transport through AIenabled efficiency improvements, prioritize energy-efficient AI projects, and strengthen trade in AIbased green technologies. These measures are essential for ensuring that AI contributes to decarbonization rather than reinforcing carbon-intensive growth
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Copyright (c) 2026 Shahriyar Mukhtarov, Mustafa Tevfik Kartal, Fatih Ayhan (Author)
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