DIP: 18.02.S25/20251004 
DOI: 10.25215/2455/1004S25 
Abstract
Artificial intelligence (AI) is reshaping sustainable finance by accelerating Environmental, Social, and Governance (ESG) assessments, climate-risk modelling, and sustainability reporting. However, the rapid adoption of AI has outpaced the development of governance mechanisms, raising concerns related to transparency, bias, explainability, data integrity, and regulatory readiness. This conceptual review examines how AI is applied within sustainable finance, evaluates the effectiveness of regulatory frameworks such as the Sustainable Finance Disclosure Regulation (SFDR), Corporate Sustainability Reporting Directive (CSRD), and the proposed EU AI Act, and identifies governance gaps that hinder responsible deployment. Findings indicate that while AI enhances analytical efficiency and enables deeper sustainability insights, fragmented ESG data, algorithmic opacity and inconsistent reporting standards continue to undermine the reliability of AI-generated outcomes. Current sustainability regulations do not sufficiently address AI-specific risks including explainability, data lineage, lifecycle accountability (the oversight of AI systems across design, deployment, monitoring and retirement) and algorithmic bias. To address these limitations, the study proposes a unified governance approach that aligns responsible-AI principles with sustainability regulations. Recommendations emphasise global ESG-data standardisation, enhanced transparency requirements for AI systems, ethics-based oversight structures and organisational capacity-building. The study contributes to emerging scholarship by presenting an integrated framework connecting regulatory, ethical and technical dimensions of AI use in sustainable finance.
The author(s) appreciates all those who participated in the study and helped to facilitate the research process. 
The author(s) declared no conflict of interest. 
ISSN 2455-670X