AI-Enabled Climate and Environmental ESG Assurance: Digital Audit Evidence, Assurance Quality and Governance A Systematic Literature Review

Climate and environmental ESG reports have been released at a faster rate than assurance work for these reports. Review of 19 studies published from 2020 to 2025 on AI-enabled climate and environmental ESG assurance. Assurance, audit evidence, verification, quality of assurance and governance are the subjects of this paper, not general ESG disclosures or sustainable finance. The synthesis shows that AI is most impactful when altering the evidentiary architecture of assurance; satellite observations, NLP-extracted disclosures, Scope 3 value-chain data, blockchain traces, and AI-based textual diagnostics are creating new forms of digitally processable audit evidence. According to the above, the quality of assurance is determined by the 'four Cs': characteristics, competence, content and corroboration; automation is insufficient. The paper builds an Evidence-to-Assurance-to-Governance framework and links the antecedent pressures, digital audit evidence, AI-enabled assurance procedures, assurance outcomes and governance controls. It is to provide an impetus for the discussion of general AI-for-ESG in the audit and assurance field.