Bridging AI innovation and sustainable Development: The effect of AI technological progress on SDG investment performance
Federico Platania,
Celina Toscano Hernandez,
Imane El Ouadghiri and
Jonathan Peillex
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Federico Platania: DVHE - De Vinci Higher Education
Imane El Ouadghiri: EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique
Jonathan Peillex: CRIISEA - Centre de Recherche sur les Institutions, l'Industrie et les Systèmes Économiques d'Amiens - UR UPJV 3908 - UPJV - Université de Picardie Jules Verne
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Abstract:
In the age of AI-driven innovation, Artificial Intelligence (AI) has become a transformative force in financial markets, reshaping investment strategies and sustainability-driven asset allocation. This study examines the impact of AI-driven innovation on the financial performance of sustainability-focused investments by analyzing the relationship between AI patent activity and the market returns of exchange-traded funds (ETFs) aligned with the United Nations Sustainable Development Goals (SDGs). Employing a state-space framework and a Kalman Filter model, we capture the dynamic influence of AI advancements on SDG-aligned ETFs, revealing that technological progress significantly enhances excess returns, particularly in the clean energy and water resource sectors. However, our analysis also uncovers sectoral variations in AI's financial impact, indicating that the benefits of AI innovation are unevenly distributed across industries. These findings bridge the gap between sustainable finance and technological innovation, demonstrating that AI serves as both a financial accelerator and a sustainability enabler. By integrating AI-driven innovation into asset pricing models, this study provides actionable insights for investors, policymakers, and corporate strategists, emphasizing the need to incorporate AI-based metrics into investment decision-making, risk assessment frameworks, and regulatory policies to foster sustainable economic growth.
Date: 2025-08
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Published in Technovation, 2025, 146, pp.103279. ⟨10.1016/j.technovation.2025.103279⟩
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05111584
DOI: 10.1016/j.technovation.2025.103279
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