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arXiv · 2610.31380

AI Risk Ontologies for the EU AI Act Compliance: AIRO, VAIR, and their Integration with DPV

Delaram Golpayegani·Harshvardhan J. Pandit·Declan O'Sullivan·Dave Lewis
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Abstract

As the use of AI, and consequently its harms, becomes more prevalent, the global discourse around AI has become increasingly risk-aware. With new risks emerging more frequently than ever, a key challenge is how to represent, document, and catalogue AI risks in an effective, interoperable, and queryable manner. Additionally, the European Union (EU) AI Act's requirements for "high-risk" AI systems to manage and document the risks creates the need for open and interoperable tools, methods, and standards that facilitate AI risk management in an ever-changing environment. In this paper, we present ontologies and taxonomies developed to assist with risk management and documentation, in line with the requirements of the EU the AI Act. We developed the AI Risk Ontology (AIRO) to specify AI use cases and their associated risks, complemented by the Vocabulary of AI Risks (VAIR), which populates AIRO with taxonomies of concepts. Key international standards on AI and risk, namely ISO/IEC 23894 on AI risk management and ISO/IEC 22989 on AI terminology informed the development of the ontologies. To promote reuse and enable multi-regulatory compliance, AIRO and VAIR have been integrated in the Data Privacy Vocabulary (DPV) through a consensus-building process, expanding DPV's scope from data to AI.

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Delaram Golpayegani, Harshvardhan J. Pandit, Declan O'Sullivan, Dave Lewis. 2026-10-22. AI Risk Ontologies for the EU AI Act Compliance: AIRO, VAIR, and their Integration with DPV. https://arxiv.org/abs/2610.31380

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