The integration of Artificial Intelligence (AI) in sustainable finance represents a transformative shift in how financial markets identify, evaluate, and manage green investments. With growing concerns over climate change and environmental degradation, investors, financial institutions, and policymakers are increasingly focused on promoting sustainable finance practices that support environmentally conscious initiatives. This research paper explores the role of machine learning (ML) and other AI-driven techniques in identifying green investments, which contribute to the achievement of sustainability goals, particularly in the context of the global transition towards a low-carbon economy.

The paper examines various AI tools and algorithms that facilitate the screening and evaluation of environmental, social, and governance (ESG) factors in investment decision-making. Machine learning models, including supervised and unsupervised learning, are explored for their ability to process vast datasets, uncover patterns, and predict the future performance of green investments. Furthermore, the paper highlights the application of AI in assessing companies' environmental impact, optimizing asset allocation, and detecting potential greenwashing in investment products.

Additionally, the research investigates the challenges and ethical considerations surrounding the use of AI in sustainable finance, such as data quality, transparency, and the potential for bias in algorithmic decision-making. The paper also explores regulatory frameworks and policy measures that can support the effective integration of AI technologies in green finance.

Ultimately, this paper underscores the potential of AI to revolutionize sustainable investment practices by enhancing decision-making, improving risk management, and driving long-term value creation for both investors and society. The study contributes to the growing body of literature on AI in finance, providing insights into its role in advancing sustainable investment strategies and supporting the global transition to a sustainable economy.

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