Integrating Artificial Intelligence and Data Analytics in Corporate Sustainability Reporting: A Study on Green Financial Disclosure Practices

In the present scenario of sustainable development, green financial reporting has become a crucial mechanism for communicating a firm’s environmental performance and long-term sustainability commitments. However, conventional approaches to data collection and disclosure continue to face persistent limitations including inconsistent measurement practices, lack of transparency, and significant time lags in reporting. Recent literature underscores that the integration of data analytics and artificial intelligence presents transformative potential to accept challenges and overcome them by automating data processing, improving reporting accuracy, and supporting evidence-based decision-making (Khan & Yu, 2021; Gupta et al., 2023).

AI-enabled systems are increasingly capable of analyzing large and complex datasets relating to environmental, social and governance (ESG) and helps to detect patterns, forecast sustainability risks, and enhance alignment with global frameworks such as theGlobal Reporting Initiative (GRI), Task Force on Climate related Financial Disclosures (TCFD) Task Force on Climate-related Financial Disclosures (TCFD), and the emerging IFRS Sustainability Disclosures Standards (Zhang & Li, 2022). The empirical evidence further suggests that the machine learning algorithms to enhance the reliability of green disclosures by identifying anomalies, estimating carbon footprints, and integrating real-time environmental indicators within financial reporting systems (Chakraborty & Das, 2022). Additionally, advanced data analytics supports improved stakeholder engagement through interactive dashboards and visual reporting tools, resulting in greater transparency and increased investor confidence (Rahman, 2021).

Despite significant technological progress, major challenges persist. These include the lack of standardized ESG data protocols, ethical and governance risks arising from AI implementation, heightened cyber security threats, and a substantial shortage of skilled professionals in sustainable finance related issues that are growing in emerging economies (World Bank, 2024; OECD, 2025).

This study helps to finds out that the changes with the help of technology give new dimensions to financial reporting system. The combination of data analytics with an artificial intelligence in green financial reporting it helps in assess their role in enhancing the quality, reliability, and credibility of sustainability disclosures, and identify the key obstacles to broader implementation in developing countries such as India. Using a mixed-method research approach, the study will integrate secondary data analysis of firms employing AI-driven ESG reporting solutions with financial reporting experts. The resulting insights are expected to contribute to the development of a conceptual framework for AI-enabled green reporting, providing policy recommendations and managerial guidance to advance digital sustainability within corporate finance.