This edited volume brings together a rich tapestry of interdisciplinary perspectives to explore the transformative potential of AI tools in the prevention, investigation, and prosecution of financial crime and money laundering. Central to this inquiry is the cross-cutting issue of illicit financial flows, which are increasingly facilitated by complex and opaque financial architectures. Across its chapters, a shared narrative emerges: the convergence of emerging technologies – particularly AI and machine learning – with globalisation and novel financial systems such as decentralised finance (DeFi) presents both unprecedented opportunities for criminal exploitation and powerful new tools for law enforcement and regulatory oversight.

A recurring theme throughout the book is the duality of promise and peril inherent in the deployment of AI systems for law enforcement purposes. This duality raises critical questions about ethics, regulation, and institutional design at both national and supranational levels. The uneven pace of regulatory adaptation to technological innovation, coupled with the challenges of crafting robust governance frameworks, forms an overarching concern across the contributions. Whether examining AI-powered policing tools, anti-money laundering (AML) mechanisms, or citizenship-by-investment (CBI) programs, the chapters underscore the importance of embedding principles such as contextuality, representativeness, transparency, fairness, accountability, and access to effective remedies into the design and deployment of AI systems.

This imperative becomes even more pressing when AI tools are integrated into public governance, where their use can pose significant risks to fundamental rights. Several chapters highlight the need for context-aware regulation, enhanced transparency requirements, and institutionalised training – particularly in law enforcement settings where AI may impact privacy, data protection, non-discrimination, the presumption of innocence, and other core defence rights. At the technical level, these risks suggest that legal safeguards must be complemented by design choices that reflect ethical, cultural, and socio-legal specificities, moving beyond mere risk management to embrace a holistic approach to responsible innovation.

The chapters focusing on financial crime detection and AML reforms articulate a broader ambition: transitioning from reactive compliance models to proactive, evidence-based systems. Proposed frameworks such as geographic risk assessments and suspicious transaction monitoring tools – based on the ‘weakest link’ methodology – challenge traditional reliance on blacklisting. Instead, they advocate for the use of verifiable secrecy scores to enhance both efficiency and transparency in AML efforts. These contributions also stress the critical importance of interoperability and cross-border cooperation. Whether addressing the technical intricacies of joint investigations or the geopolitical risks posed by fragmented AML oversight (e.g., inconsistent suspicious transaction reporting standards), the book makes a compelling case for harmonised regulatory standards, secure data-sharing infrastructures, and trust-based collaboration among stakeholders. The European Union is presented as a paradigmatic testing ground for such integrative solutions.

Beyond enforcement, the book also examines how AI is reshaping financial ecosystems more broadly. The dual-use nature of emerging technologies – especially in DeFi, blockchain, and the Internet of Things (IoT) – is not treated as an anomaly but as a defining feature of the digital age. Chapters exploring this convergence argue that the question is no longer whether AI and DeFi will transform finance, but rather how regulators, policymakers, and technologists will shape the trajectory of that transformation. One particularly provocative concept is that of embedded supervision, which raises complex questions about reconciling privacy-preserving technologies with lawful access, and the feasibility of regulators deploying AI agents to interact with DeFi protocols in real time. How these tensions are resolved will significantly influence whether financial innovation serves the public interest or evolves into opaque systems that threaten democratic governance.

The future of AI in law enforcement – whether deployed by public authorities or private institutions – hinges not only on technological advancement but also on the normative principles guiding its development, training, and use. As highlighted in chapters on AI adoption in banking and CBI programs, aligning AI deployment with values such as fairness, ethics, accountability, and transparency is essential to building trust, ensuring due diligence, and maintaining compliance across jurisdictions. This edited volume serves as a timely reminder that human agency and institutional investment are indispensable in managing the risks and realising the benefits of AI. From training law enforcement personnel to establishing AI ethics bodies, conducting fundamental rights impact assessments, and promoting transparency in AI procurement, institutions must be equipped not only with tools but also with the values and expertise necessary for responsible use – especially given the inherent power imbalances AI systems may reinforce.

Ultimately, the contributions in this book offer both a diagnosis and a roadmap. They illuminate systemic gaps in regulation, governance, and international cooperation in the realm of automated law enforcement, while also proposing actionable strategies to address these challenges. These include calls for stronger AI governance, harmonisation of cross-border investigative tools, and ethical stewardship of AI technologies. Technological progress, the book argues, is not an inevitability but a means to an end. The impact of AI on law enforcement will be shaped by the frameworks we construct, the institutions we empower, and the values we uphold. In this spirit, the book invites readers and stakeholders not merely to observe the ongoing transformation but to actively participate in shaping it through responsible innovation, interdisciplinary research, and collaborative governance.