Explainable Artificial Intelligence for ESG Performance Assessment and Sustainability Reporting

  • Authors

    • N. Seshagiri Information Technology Pioneer, National Informatics Centre, India. Author

    DOI:

    https://doi.org/10.67228/30715636/IJETMR-2024PII9T5R

    Published 12-04-2024

  • Explainable Artificial Intelligence (XAI), Environmental Social Governance (ESG), Sustainability Reporting, Explainable Machine Learning, ESG Analytics, Responsible Artificial Intelligence, Corporate Sustainability, Decision Support Systems, Sustainable Finance, Feature Attribution, ESG Scoring, Regulatory Compliance

    Issue

    Vol. 7 No. 2 (2024)

    Section

    Articles

    How to Cite

    [1]
    S. N, “Explainable Artificial Intelligence for ESG Performance Assessment and Sustainability Reporting”, IJETMR, vol. 7, no. 2, pp. 01–16, Dec. 2024, doi: 10.67228/30715636/IJETMR-2024PII9T5R.

  • Abstract

    Environmental, Social, and Governance (ESG) performance assessment evaluates an organization's sustainability by measuring its environmental responsibility, social impact, and governance practices. Environmental indicators include carbon emissions, energy efficiency, water conservation, waste management, and biodiversity protection. Social assessment focuses on employee welfare, diversity, human rights, customer satisfaction, and community engagement, while governance evaluates board accountability, ethical conduct, transparency, compliance, risk management, and anti-corruption measures. ESG reporting enables organizations to communicate their sustainability performance to investors, regulators, customers, and other stakeholders using globally recognized reporting frameworks. These reports improve transparency, accountability, regulatory compliance, and support responsible investment decisions. With the rapid growth of digital data from ERP systems, IoT devices, supply chains, environmental monitoring, and financial systems, organizations face challenges in data integration and analysis. To overcome these challenges, businesses increasingly adopt Artificial Intelligence (AI), Machine Learning (ML), and data analytics to automate ESG assessment, improve reporting accuracy, enhance decision-making, and strengthen long-term sustainable business growth and corporate governance.

  • References

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