<![CDATA[Background of study: The increasing demand for sustainability and transparency has strengthened the role of sustainable accounting and Environmental, Social, and Governance (ESG) reporting in modern business practices. However, traditional reporting systems face significant challenges in managing complex, large-scale, and heterogeneous ESG data, leading to limitations in accuracy, consistency, and timeliness. Although artificial intelligence (AI) has been widely adopted in financial analysis, its application in sustainable accounting and ESG reporting remains fragmented and underexplored. Aims: This study aims to provide a comprehensive and structured analysis of the role of AI in enhancing sustainable accounting and ESG reporting. Methods: This study employs a Systematic Literature Review (SLR) using the PRISMA framework, combined with bibliometric analysis. Data were collected from the Scopus database using three keyword strategies and filtered based on predefined inclusion criteria. The dataset was cleaned using OpenRefine and analyzed using VOSviewer and Biblioshiny to explore research trends, thematic structures, and intellectual development. Result: The results show that AI technologies, particularly machine learning, natural language processing, and big data analytics, significantly improve ESG data processing, reporting efficiency, and predictive decision-making. However, ESG reporting practices remain fragmented, lack standardization, and are often implemented in isolated contexts. Conclusion: This study contributes by integrating AI, sustainable accounting, and ESG reporting into a unified perspective supported by systematic and bibliometric analysis. The findings highlight the potential of AI to enhance transparency and efficiency in sustainability reporting, while emphasizing the need for integrative frameworks and empirical validation in future research.]]>
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