The rapid adoption of Environmental, Social, and Governance (ESG) frameworks has positioned sustainability reporting as a critical mechanism for corporate accountability, particularly in emerging markets. However, the voluntary nature of disclosures, fragmented assurance standards, and increasing reputational pressures have contributed to the growing phenomenon of greenwashing where firms selectively present misleading or exaggerated sustainability claims. In this context, Artificial Intelligence (AI) is emerging as a transformative tool for strengthening ESG assurance and detecting greenwashing practices through data-driven, real-time, and scalable solutions. This study examines the role of AI-driven technologies in enhancing the credibility, transparency, and reliability of ESG disclosures in emerging economies. Using a mixed-method approach, the research synthesizes existing literature, regulatory developments, and empirical evidence from emerging markets to assess how machine learning algorithms, natural language processing, sentiment analysis, and big data analytics are being applied to ESG verification and greenwashing detection. The paper identifies key AI-enabled mechanisms such as anomaly detection in ESG metrics, textual inconsistency analysis in sustainability reports, and cross-validation of corporate disclosures with third-party environmental and social data sources. The findings highlight that AI-driven assurance systems significantly reduce information asymmetry, improve stakeholder trust, and strengthen regulatory oversight, while also revealing challenges related to data quality, algorithmic bias, regulatory readiness, and ethical governance. The study contributes to the ESG literature by proposing a conceptual framework for AI-enabled ESG assurance tailored to emerging markets and outlining future research and policy directions. It underscores the need for collaborative governance involving regulators, corporations, auditors, and technology providers to ensure responsible and effective deployment of AI in sustainability assurance.