Keywords
esg reporting
sustainability reporting
bibliometric analysis
How to Cite
Abstract
Purpose – This study explores the evolving role of artificial intelligence (AI) in sustainability and ESG reporting, mapping research trends, contributions, and future directions. Methodology/Approach – A two-stage methodology combining bibliometric analysis (304 SCOPUS-indexed documents from 2015–2025) with qualitative content analysis of 18 key publications was applied. Findings—AI enhances ESG reporting through automation, real-time monitoring, predictive analytics, and improved data integrity. These capabilities support organisations in aligning with international standards and responding to growing stakeholder demands for transparency and accountability. Research Implications – While conceptual frameworks are emerging, empirical validations and sectoral comparisons remain limited. Practical Implications – AI supports more efficient, transparent, and standards-aligned reporting processes, enabling better decision-making and risk mitigation. Social Implications – Ethical and inclusive design of AI systems is crucial to prevent bias and enhance stakeholder trust. Originality/Value – This study offers a comprehensive bibliometric perspective, identifies key AI-enabled advancements, and proposes future research avenues.
References
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