Drivers of AI–Sustainability: The Roles of Financial Wealth, Human Capital, and Renewable Energy
Year: 2025
Type: article
Abstract: Artificial Intelligence (AI) is increasingly central to sustainable development, yet its advancement varies across G7 economies. This study employs Method of Moments Quantile Regression (MMQR) to examine how Financial Technology (FinTech), Economic Growth (EG), Human Capital (HC), and Renewable Energy Consumption (RENC) influence AI development in G7 countries from 2000 to 2022. By analyzing heterogeneous effects across quantiles, the study captures stage-specific drivers often overlooked in average-based models. Results indicate that FinTech and human capital significantly promote AI adoption in lower and middle quantiles, enhancing digital inclusion and innovation capacity, while RENC becomes relevant primarily at advanced stages of AI adoption. Economic growth exhibits negative or inconsistent effects, suggesting that GDP expansion alone is insufficient for technological transformation without alignment to supportive policies and institutional contexts. The lack of long-run cointegration further highlights the dominance of short- and medium-term dynamics in shaping the AI–sustainability nexus. These findings provide actionable insights for policymakers, emphasizing targeted FinTech development, skill-building initiatives, and renewable-powered AI solutions to foster sustainable and inclusive AI adoption. Overall, the study demonstrates how financial, human, and environmental factors jointly drive AI development, offering a mechanism-based perspective on technology-driven sustainable development in advanced economies.
Source: Sustainability
DOI: 10.3390/su17219920
Authors: Guangpeng Chen, Anthony David
Institutions: University of California, Berkeley, Siena Heights University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4415991334