Artificial Intelligence as an Emerging Risk Dimension in Corporate Sustainability Reporting: A Legal and Governance Perspective

(1) Background: As digital technologies become integral to business operations, risks associated with artificial intelligence (AI), data governance, and cybersecurity are emerging as material concerns in the context of corporate sustainability. This article examines the extent to which current sustainability reporting standards (CSRD/ESRS, GRI, ISSB, and SASB) address risks associated with AI and broader digital transitions. (2) Methods: This study employs a qualitative content analysis of twenty corporate sustainability reports across digitally intensive sectors, complemented by a doctrinal legal analysis of the relevant normative instruments governing sustainability and digital risk reporting. (3) Results: This study finds that while references to AI risks are increasingly present, they often lack depth, standardisation, and connection to legal accountability mechanisms. Key gaps include underreporting human rights impacts linked to algorithmic decision-making and limited disclosure on internal AI governance structures. (4) Conclusions: The article argues that to uphold the principles of transparency, due diligence, and stakeholder accountability, sustainability reporting frameworks must evolve to capture the risks associated with AI transitions explicitly. The findings call for regulatory and standard-setting bodies to establish more explicit guidance on AI risk disclosures, and for corporate directors to integrate these dimensions into their risk governance and reporting duties.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2026-02-27
DOI
https://doi.org/10.3390/su18052278
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence as an Emerging Risk Dimension in Corporate Sustainability Reporting: A Legal and Governance Perspective

Andreja Primec, Matic Čufar, Jernej Belak
Sustainability
Ethics and Social Impacts of AI
article

Artificial Intelligence as an Emerging Risk Dimension in Corporate Sustainability Reporting: A Legal and Governance Perspective

Andreja Primec, Matic Čufar, Jernej Belak
article en

Abstract

(1) Background: As digital technologies become integral to business operations, risks associated with artificial intelligence (AI), data governance, and cybersecurity are emerging as material concerns in the context of corporate sustainability. This article examines the extent to which current sustainability reporting standards (CSRD/ESRS, GRI, ISSB, and SASB) address risks associated with AI and broader digital transitions. (2) Methods: This study employs a qualitative content analysis of twenty corporate sustainability reports across digitally intensive sectors, complemented by a doctrinal legal analysis of the relevant normative instruments governing sustainability and digital risk reporting. (3) Results: This study finds that while references to AI risks are increasingly present, they often lack depth, standardisation, and connection to legal accountability mechanisms. Key gaps include underreporting human rights impacts linked to algorithmic decision-making and limited disclosure on internal AI governance structures. (4) Conclusions: The article argues that to uphold the principles of transparency, due diligence, and stakeholder accountability, sustainability reporting frameworks must evolve to capture the risks associated with AI transitions explicitly. The findings call for regulatory and standard-setting bodies to establish more explicit guidance on AI risk disclosures, and for corporate directors to integrate these dimensions into their risk governance and reporting duties.

SustainabilityVol. 18(5)
University of Maribor (SI)
Openalex Percentile: Top 45%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.