Exploring the boundaries of AI regulatory sandboxes under the AI Act: Flexibility and real-world testing

Abstract The Artificial Intelligence (AI) Act introduces AI regulatory sandboxes and testing in real-world conditions as experimentation tools to support innovation in AI development. While regulatory sandboxes have been widely adopted across various sectors, their precise function and scope under the AI Act remain complex and multifaceted. This paper examines the legal framework governing AI regulatory sandboxes, analysing the degree of regulatory flexibility they provide and how they interact with other experimentation tools established by the AI Act. In particular, the study assesses whether these instruments enable AI systems to be tested under reduced regulatory constraints or whether they primarily serve as forums for regulatory dialogue. It then explores the differences between AI regulatory sandboxes and the testing in real-world conditions mechanism, highlighting how sandboxes focus on legal guidance, while testing in real-world conditions aims to remove legal barriers and facilitate market entry. The analysis also identifies key interpretative challenges, including the interplay between Article 57 (AI regulatory sandboxes) and Article 60 (testing in real-world conditions), the compliance requirements for each mechanism, and the role of regulatory authorities. The paper concludes that further clarification from the European Commission is necessary to address inconsistencies in the AI Act’s provisions, ensuring effective implementation of AI regulatory sandboxes and testing in real-world conditions.

Institutions

Publication Details

Journal
Cambridge Forum on AI Law and Governance
Published
2025-01-01
DOI
https://doi.org/10.1017/cfl.2025.10013
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

Exploring the boundaries of AI regulatory sandboxes under the AI Act: Flexibility and real-world testing

Cambridge Forum on AI Law and Governance
Ethics and Social Impacts of AI
article

Exploring the boundaries of AI regulatory sandboxes under the AI Act: Flexibility and real-world testing

article en

Abstract

Abstract The Artificial Intelligence (AI) Act introduces AI regulatory sandboxes and testing in real-world conditions as experimentation tools to support innovation in AI development. While regulatory sandboxes have been widely adopted across various sectors, their precise function and scope under the AI Act remain complex and multifaceted. This paper examines the legal framework governing AI regulatory sandboxes, analysing the degree of regulatory flexibility they provide and how they interact with other experimentation tools established by the AI Act. In particular, the study assesses whether these instruments enable AI systems to be tested under reduced regulatory constraints or whether they primarily serve as forums for regulatory dialogue. It then explores the differences between AI regulatory sandboxes and the testing in real-world conditions mechanism, highlighting how sandboxes focus on legal guidance, while testing in real-world conditions aims to remove legal barriers and facilitate market entry. The analysis also identifies key interpretative challenges, including the interplay between Article 57 (AI regulatory sandboxes) and Article 60 (testing in real-world conditions), the compliance requirements for each mechanism, and the role of regulatory authorities. The paper concludes that further clarification from the European Commission is necessary to address inconsistencies in the AI Act’s provisions, ensuring effective implementation of AI regulatory sandboxes and testing in real-world conditions.

Cambridge Forum on AI Law and GovernanceVol. 1
Université Libre de Bruxelles (BE), Vrije Universiteit Brussel (BE), Universidade de Brasília (BR)
Openalex Percentile: Top 87%
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.

Exploring the boundaries of AI regulatory sandboxes under the AI Act: Flexibility and real-world testing · Cambridge Forum on AI Law and Governance (2025) | TGRS Research Map | TGRS