Peran Artificial Intelligence terhadap Praktik Greenwashing dalam Sustainability Report: Systematic Literature Review

Introduction/Main Objectives: The increasing demand for sustainability reports encourages companies to be more transparent in disclosing social and environmental impacts, especially for global companies in the era of digital transformation. Background Problems: The practice of greenwashing in presenting fake sustainability reports still often occurs and affects stakeholder trust. This literature review aims to provide a comprehensive overview and mapping several studies related to the role technology of Artificial Intelligence (AI) on greenwashing practices in sustainability reports. Novelty: This study conducted a literature review on Artificial Intelligence (AI) articles with Greenwashing, Technology, Sustainability Report mitigation. Research Methods: The method used in this research is a Systematic Literature Review (SLR). Data analysis by mapping 16 selected articles from 2021 to 2024 in the Scopus database. Finding/Results: The results of this research show that Artificial Intelligence (AI) technology has proven to have a significant contribution to mitigating greenwashing practices in sustainability reports. Artificial Intelligence (AI) is able to increase transparency, automatic data collection, and data analysis, increase accountability, help identify potential bias, validate sustainability claims, detects data inconsistencies, and assists in reducing Environmental, Social, and Governance (ESG) divergence. Despite its promising potential, AI still faces challenges, particularly in algorithmic ethics and infrastructure readiness. Conclusion: Practice greenwashing in sustainability reports. Artificial Intelligence (AI) can increase transparency, automated data collection, data analysis, increase accountability and transparency of sustainability reports, help identify potential bias, validate sustainability claims, identify data discrepancies and help reduce Environmental, Social, and Governance (ESG) Divergence. Although AI is promising, challenges remain, such as algorithm ethics and infrastructure readiness.