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Artificial Intelligence in Sustainability Reporting: A Conceptual Framework for Enhanced Transparency and Accountability

In: Embracing Technological Agility in Accounting and Business – Vol. 3

Author

Listed:
  • Wayne Moodaley

    (Graduate School of Business, University of Cape Town)

Abstract

As sustainability reporting becomes increasingly essential to corporate accountability, persistent challenges remain in ensuring transparency, consistency, and credibility across disclosures. These challenges include multiple reporting frameworks, inconsistent sustainability data quality, and the risk of greenwashing—issues that existing manual or conventional reporting systems have struggled to resolve. This chapter identifies a specific research gap in how artificial intelligence (AI) tools, particularly natural language processing and machine learning, can enhance sustainability reporting by addressing or mitigating these systemic problems. While prior research has explored digitalisation trends and some AI use cases in sustainability reporting, a comprehensive, theory-driven conceptual framework for AI integration in sustainability reporting remains absent. In response, this study adopts a conceptual research approach, grounded in stakeholder and legitimacy theory, and supported by a review of existing literature and sustainability reporting frameworks. A conceptual framework is developed to illustrate how AI can enhance sustainability reporting data collection, data analysis, report generation, and assurance. This study’s findings suggest that AI has the potential to strengthen stakeholder engagement, mitigate greenwashing risks, and enhance organisational legitimacy, provided that robust governance mechanisms are in place to ensure ethical and transparent implementation. The proposed framework contributes to the body of knowledge by bridging AI-enabled innovation with stakeholder and legitimacy theory, to offer a comprehensive conceptual model of AI integration across the sustainability reporting lifecycle. This model advances current literature by situating technological adoption within normative and relational disclosure theories, and provides practical guidance for stakeholders, firms, standard-setters, and researchers. It also sets a foundation for empirical research on sector-specific adoption, assurance integration, and stakeholder responses to AI-enabled disclosures.

Suggested Citation

  • Wayne Moodaley, 2026. "Artificial Intelligence in Sustainability Reporting: A Conceptual Framework for Enhanced Transparency and Accountability," Springer Proceedings in Business and Economics, in: Tankiso Moloi (ed.), Embracing Technological Agility in Accounting and Business – Vol. 3, pages 243-259, Springer.
    • Handle: RePEc:spr:prbchp:978-3-032-13388-5_17
    DOI: 10.1007/978-3-032-13388-5_17
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