Risk-based approach to EU AI act: benefits and challenges of co-regulation

The regulation of artificial intelligence (AI) is an important policy area in which a risk-based approach is increasingly being pursued. This article examines co-regulation, a hybrid regulatory model where public and private sectors collaborate to manage AI risks within a risk-based framework. Drawing on an analysis of the EU AI Act, the article identifies the significant benefits and challenges of these public-private partnerships. It argues that, to achieve the societal goals of safety, health, and fundamental rights, the EU’s framework should mandate data sharing mechanisms between private and public actors to build the necessary regulatory capacity. Moreover, the framework needs to be flexible enough to adapt to evolving risks and industry developments, ensuring that public oversight of AI remains risk-based, transparent, and free from industry capture. This is particularly important for promoting compliance and establishing a truly effective regulatory framework.

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Publication Details

Journal
Policy Design and Practice
Published
2026-01-02
DOI
https://doi.org/10.1080/25741292.2025.2610869
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Risk-based approach to EU AI act: benefits and challenges of co-regulation

Ronit Justo-Hanani
Policy Design and Practice
Ethics and Social Impacts of AI
article

Risk-based approach to EU AI act: benefits and challenges of co-regulation

Ronit Justo-Hanani
article en

Abstract

The regulation of artificial intelligence (AI) is an important policy area in which a risk-based approach is increasingly being pursued. This article examines co-regulation, a hybrid regulatory model where public and private sectors collaborate to manage AI risks within a risk-based framework. Drawing on an analysis of the EU AI Act, the article identifies the significant benefits and challenges of these public-private partnerships. It argues that, to achieve the societal goals of safety, health, and fundamental rights, the EU’s framework should mandate data sharing mechanisms between private and public actors to build the necessary regulatory capacity. Moreover, the framework needs to be flexible enough to adapt to evolving risks and industry developments, ensuring that public oversight of AI remains risk-based, transparent, and free from industry capture. This is particularly important for promoting compliance and establishing a truly effective regulatory framework.

Policy Design and Practice
American Museum of Natural History (US)
Partnerships for the goals
Openalex Percentile: Top 99%
Ethics and Social Impacts of AI
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