Perspective Chapter: The Algorithmic Regulator – AI as the Third-Party Auditor of Corporate Sustainability and ESG Compliance
Year: 2026
Type: book-chapter
Abstract: The widespread use of generative artificial intelligence (GenAI) technologies since the advent of large language models (LLMs), such as with the public release of ChatGPT in November 2022, has changed the landscape of automation, compliance, and sustainability auditing. This chapter explores the possibility of GenAI and other artificial intelligence (AI) systems serving as credible, trustworthy, and independent third-party verifiers of corporate sustainability and environmental, social, and governance (ESG) compliance. The chapter draws on algorithmic governance theory, institutional theory, and systems theory to conceptualize AI as an ‘algorithmic regulator’ system capable of analyzing large volumes of structured and unstructured ESG data, detecting greenwashing, forecasting compliance risks, and producing continuous, machine-readable sustainability assessments. The chapter presents four main scientific contributions: (1) a conceptual framework to position AI as an algorithmic regulator in ESG ecosystems, (2) a practical workflow model to operationalize AI-driven ESG auditing, (3) a synthesized benefits-challenges-risks typology based on recent empirical literature published between 2022 and 2025, and (4) a governance and ethics framework for responsible algorithmic ESG auditing. An in-depth review of recent empirical literature published between 2022 and 2025 shows that, although AI has the potential to dramatically change the nature of ESG auditing, there are several key limitations, including algorithmic opacity, poor data quality, fragmentation of ESG metrics, and the risk of bias against Global South organizations. The chapter ends with policy, corporate, and audit implications and a research agenda that focuses on algorithmic assurance. This chapter contributes to the emerging interdisciplinary literature at the intersection of AI ethics, sustainability governance, and corporate accountability.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7203678718