Generative AI in ESG Reporting: Navigating the Dual Role of Efficiency Enabler and Greenwashing Facilitator in the Indonesian Context

Abstract

The integration of generative artificial intelligence (AI) into Environmental, Social, and Governance (ESG) reporting represents a transformative yet double-edged development in corporate sustainability practice. This conceptual paper examines the dual role of generative AI—specifically large language models (LLMs)—as both an efficiency enabler and a potential facilitator of greenwashing in ESG disclosure. Grounded in Legitimacy Theory and the ESG Disclosure Framework, this study critically analyses how AI-generated content can streamline sustainability reporting processes while simultaneously introducing risks of biased, misleading, or unverified disclosures. Drawing on recent empirical and theoretical literature from 2022 to 2025, the paper maps the trajectory of AI adoption in ESG reporting, identifies key greenwashing mechanisms enabled by generative AI, and evaluates regulatory responses—including Indonesia's tightened ESG disclosure requirements under Otoritas Jasa Keuangan (OJK). Findings suggest that while generative AI significantly reduces reporting burdens, enhances data synthesis, and improves stakeholder accessibility of sustainability reports, it also creates new pathways for impression management and selective disclosure that undermine the credibility of ESG information. The paper proposes a governance framework for responsible AI-assisted ESG reporting, incorporating human oversight, algorithmic transparency, and regulatory auditing mechanisms tailored for the Indonesian context. This study contributes a novel perspective to the intersection of accounting, sustainability, and artificial intelligence, filling a critical gap in the literature from developing country standpoints.