AI in Sustainable Investing

Abstract

A systematic literature review (SLR) of 120 peer-reviewed articles published between 2010 and 2024, examining the role of advanced technologies in sustainable investing. Using grounded theory's coding techniques, the analysis identifies five key themes: I. Enhanced Data Processing and Predictive Analytics, II. Algorithmic Bias and Ethical Challenges, III. Market Volatility and Systemic Risks, IV. Regulatory and Transparency Gaps, and V. Stakeholder Collaboration and Trust. The chapter highlights the transformative potential of these technologies in improving efficiency and predictive capabilities within sustainable investing. However, it also underscores the ethical, systemic, and regulatory risks associated with their implementation. To address these challenges, the chapter advocates for hybrid governance frameworks that combine human oversight with technological precision, prioritize ethical design principles, and establish agile regulatory approaches. This balanced approach aims to leverage technological advancements as a positive force for achieving sustainable outcomes.