Artificial Intelligence in Sustainability Assurance: Accounting Challenges, Audit Risks and a Conceptual Framework for ESG Verification

This conceptual article examines how artificial intelligence can support sustainability assurance in the transition from voluntary ESG disclosure to regulated, assurance-oriented sustainability reporting. The study is situated in the context of the Corporate Sustainability Reporting Directive, the European Sustainability Reporting Standards, ISSA 5000 and the EU Artificial Intelligence Act. It argues that AI can strengthen ESG verification by supporting disclosure identification, ESRS mapping, anomaly detection, consistency checks, greenwashing risk screening, external data triangulation and working-paper documentation. At the same time, AI introduces specific assurance risks, including data quality risk, reliability and hallucination risk, explainability risk, bias risk, overreliance risk, documentation risk, confidentiality risk, boundary and materiality risk, and accountability risk. The article develops a Responsible AI-Assisted Sustainability Assurance Framework that integrates ESG data inputs, AI analytical procedures, assurance risk assessment, human professional judgement, validation controls and documented assurance outputs. The central conclusion is that AI should be used as an analytical support layer within a human-in-the-loop assurance process, not as an autonomous source of assurance conclusions.