AI-Driven ESG Intelligence: A Conceptual Framework for Disclosure Integrity and Financial Resilience in Indian Firms

Environmental, Social and Governance (ESG) considerations now sit at the centre of corporate strategy and regulation in India, yet disclosures under the Securities and Exchange Board of India’s Business Responsibility and Sustainability Reporting (BRSR) regime remain uneven, narrative-heavy and vulnerable to selective reporting and greenwashing, while rating methodologies diverge widely—limiting comparability and weakening the link between compliance and financial outcomes. This paper proposes a conceptual framework that integrates Artificial Intelligence—specifically machine learning and natural language processing—with ESG analytics, governance indicators and financial-performance measures within a single empirical architecture purpose-built for the Indian market, treating governance quality as a moderator of AI-enabled ESG outcomes. Synthesising the literature, the paper shows that existing work treats AI, ESG, governance and greenwashing largely in isolation and is concentrated in developed markets, leaving no integrated, BRSR-calibrated framework; it then articulates how AI can strengthen disclosure integrity, help predict firm resilience, and support the quantification of greenwashing. The framework offers a structured research agenda and a foundation for decision-support tools usable by regulators, investors, boards and assurance providers seeking transparent, evidence-based ESG assessment.