Regulatory sandboxes emerged as prominent tools for fostering financial innovation, particularly in jurisdictions where regulatory rigidity may hinder technological advancements. This article examines the Brazilian Central Bank’s experience with regulatory sandboxes between 2021 and 2024, analyzing their role in balancing market modernization with institutional oversight. While often presented as a panacea for regulatory challenges in emerging markets, the effectiveness of these frameworks remains a subject of debate. By situating its approach within broader discussions on regulatory experimentalism, this study explores whether sandboxes serve merely as deregulatory mechanisms or can function as state-led instruments for fostering financial innovation. Drawing from the concept of the entrepreneurial state, the article investigates how specialized regulatory agencies can collaborate with private actors to drive technological development in financial markets. The findings suggest that, while the BCB’s regulatory sandbox challenges the traditional dichotomy between regulation and innovation, offering a model where legal oversight and market experimentation coexist, it also raises concerns about regulatory capture, market concentration, and the potential erosion of consumer protections. Although sandboxes can stimulate innovation, their long-term success depends on mitigating these risks and ensuring that financial experimentation does not come at the expense of broader public interest objectives.

This paper provides a comprehensive case study of Israel’s emerging regulatory sandbox frameworks for AI applications. Drawing from policy white papers, legislative materials, and implemented frameworks, it documents how Israel is adopting sector-specific regulatory sandboxes as experimental mechanisms to balance innovation with public interest concerns. The paper maps the growing appeal of regulatory sandboxes across Israeli AI policy documents since 2018 and provides a detailed analysis of three key implementations: autonomous vehicles, fintech, and general legislative guidelines. It examines Israel’s pioneering AV regulatory sandbox, which grants specific exemptions from traffic regulations (including steering wheel control requirements and international standards compliance) while maintaining safety oversight through control centers and incident reporting. The paper analyzes the proposed fintech sandbox’s multi-regulator committee structure and dual-track system for licensing and oversight relief. It also evaluates the recently published general regulatory sandbox legislative guidelines that establish a technology-neutral four-phase lifecycle framework. The analysis reveals Israel’s preference for adapting existing regulatory structures rather than creating comprehensive AI-specific governance mechanisms. While this sector-specific approach facilitates targeted innovation, it may inadequately address broader AI governance concerns such as algorithmic accountability and human oversight. The paper critically examines institutional design challenges, including inter-agency coordination difficulties in the fintech framework and the tension between innovation facilitation and consumer protection. It concludes that Israel’s approach represents a pragmatic response to technological uncertainty, though questions remain about implementation effectiveness and the adequacy of sector-specific frameworks for comprehensive AI governance. The study contributes to comparative regulatory literature by documenting an understudied jurisdiction’s approach to regulatory experimentation.

The establishment of artificial intelligence regulatory sandboxes (AIRSs) poses both policy and technical challenges, especially in how to reconcile support for innovation with regulatory oversight. AIRSs are based on dynamic regulatory feedback mechanisms that allow for a deeper examination of legal norms with a view to their future evolution. These structures facilitate engagement between regulators and innovators, enabling business learning and regulatory adaptation. However, their proliferation across the European Union under the Artificial Intelligence Act (AI Act) may raise issues of coordination between competent authorities, cross-border regulatory alignment and consistency with overlapping (sectoral) rules. In view of these potential complexities, this paper makes two distinct recommendations. First, AIRSs would benefit from cross-border cooperation – efforts should therefore be made to pursue the establishment of joint AIRSs among different Member States in order to reduce regulatory fragmentation, lower the risk of forum shopping, and optimise administrative resources. Second, integrating AI and cybersecurity compliance within the same sandbox environment would be beneficial in terms of providing clearer and more structured compliance pathways. A well-designed regulatory sandbox regime would make regulation more effective, encourage responsible AI development and secure Europe’s leadership in digital regulation.

Artificial intelligence (AI) presents unique regulatory challenges due to its rapid evolution and broad societal impact. Traditional ex ante regulatory approaches struggle to keep pace with AI development, exacerbating the “pacing problem” and the Collingridge dilemma. In response, experimentalist governance–particularly through regulatory sandboxes (RSs)–has emerged as a potential solution. This paper examines AI RSs within the European Union’s Artificial Intelligence Act (AI Act) from a law and economics perspective, investigating their capacity to address market and government failures and enhance regulatory efficiency compared to traditional command-and-control mechanisms. Applying an economic analysis of law framework, the paper evaluates how RSs can mitigate information asymmetries, reduce negative externalities, and facilitate iterative regulatory learning while promoting responsible AI innovation. It further analyses how RSs may correct specific government failures, including regulatory capture, rent-seeking, and knowledge gaps. Drawing comparative insights from FinTech, the paper identifies the institutional design features necessary to ensure their effectiveness and resilience. While RSs offer a flexible and innovation-friendly governance model, their success ultimately depends on sound institutional safeguards, proportionality, and alignment with broader policy objectives. The paper contributes to ongoing debates on experimentalism in AI governance by proposing design principles for effective, accountable, and adaptive sandboxes.

Regulatory sandboxes for Artificial Intelligence (AI) are designed to address challenges of rapid technological change. AI innovations create an acute need for learning about what regulation is suitable for enabling innovation while dealing with technological risks. This article argues that regulatory sandboxes should be analyzed primarily as mechanisms for enhancing policymakers’ understanding of technologies such as AI, rather than solely as spaces for experimentation that promote innovation. It discusses the role of regulatory sandboxes in facilitating policy learning that can complement the long-term learning processes of the traditional policy cycle. Six case studies serve to illustrate sandbox elements for enabling collaborative experiential learning in contexts in which the absence of AI regulation makes accelerated policy learning particularly valuable. Looking at the design and governance of regulatory sandboxes from Brazil, Colombia, Mauritius, Mexico, Rwanda, and Thailand, learning elements related to the technology and consequences for closing legal lags emerge as critical components.

The article analyzes whether regulatory sandboxes are a legally intended and useful instrument to create pathways for law enforcement agencies using cutting-edge AI systems in compliance with fundamental rights. It takes a deeper look at the provisions of the EU AI Act for regulatory sandboxes and testing under real-world conditions in contexts relevant to law enforcement. Using a legislative process in Germany as a case study, the article shows the imminent tension of innovative AI systems between modern investigation tools in the digital age, as well as potential pathways towards disproportionate surveillance of citizens. The author suggests taking the extra mile through regulatory sandboxes instead of crafting legal foundations quickly under the influence of current political pressure: On the long run this can save tax money, avoid dependencies to tech companies and pave a European way of AI systems that respect digital human rights in an appropriate manner.

Modern Elections can be conceived as a socio-technical system, as the electoral process in many ways relies on technological solutions: voter information, identification and registration, collecting, verifying and counting the votes – in some countries these steps are conducted by using innovative technologies. But how do those devices and processes actually become part of the official legislation and can finally deployed during this sensitive and important democratic procedure? Over time, the State of California has developed a robust regulatory ecosystem for integrating innovative technology into the electoral process and is also able to change and modernize its rules and regulations. Although technologies currently used are more static, hardware-based and usually do not include algorithmic systems, the overall structure of the process may also function as a blueprint for regulating more dynamic algorithm-based or even AI-based technologies.

How can existing experiences of regulatory experimentation inform AI sandbox design in Europe? This paper explores the ‘responsible AI’ sandbox of the Norwegian Data Protection Agency (DPA), a GDPR-oriented regulatory experiment created in 2020 with four projects per annum. Through an interpretive policy analysis of documents (exit reports and workshop transcripts) and semi-structured interviews with officials, we explore how the Norwegian DPA approached its mandate of ‘helping with responsible innovation’, where it identified role conflicts, and what scope conditions and challenges it perceived around sandbox work. Sandboxing represented a ‘new way of working’ for the regulatory authority: in an idea-based intervention mode, the DPA moves from rule-based interventions as a watchdog to becoming a dialogue-oriented partner in solution-finding, a concretiser of ambiguous GDPR rules, and a keen learner from sectoral and technical experts. Critical engagement with our data suggests that sandbox design should not be reduced to technical and procedural questions. It requires regulators’ critical reflexivity on their ambivalent role and power relations in the regulatory experiment: how to strategically select relevant projects and issues, how to navigate budgetary constraints and the lack of follow-ups, and how sandboxing affects more interventionist regulatory duties.

Against the backdrop of the European Union (EU)’s objective that artificial intelligence (AI) regulatory sandboxes under the EU AI Act should both foster innovation and assist with compliance, considerable challenges are identified for Member States around capacity-building and the design and operationalisation of regulatory sandboxes. The article charts Member States’ early-stage preparations for implementing AI regulatory sandboxes and contends that there is a risk that differing approaches being taken by individual national sandboxes could lead to fragmentation and jeopardise a uniform interpretation of the AI Act in practice. This could also motivate innovators to play sandbox arbitrage. With sandbox participation being voluntary, the possibility that AI regulatory sandboxes may prove unattractive to innovators on their compliance journey is also explored. Confidentiality concerns, the inability to relax legal rules during the sandbox and the inability of AI regulatory sandboxes to deliver a presumption of conformity with the AI Act are identified as pertinent concerns for innovators contemplating applying to AI regulatory sandboxes as compared with other direct pre-market compliance routes provided to them in the form of application of harmonised standards and conformity assessment procedures.

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.