What question did this study set out to answer?

The study aims to analyze the use of artificial intelligence in investigating official offences and recommend adaptations for Ukraine.

February 2, 2026Open Access

Introduction of artificial intelligence and other innovative technologies in the process of investigating criminal offences in the field of official activity

Key Points

The study aims to analyze the use of artificial intelligence in investigating official offences and recommend adaptations for Ukraine.
Comparative analysis of AI regulation and practices in Ukraine, USA, UK, Australia, and Brazil.
Examination of technological mechanisms and legal guarantees in law enforcement activities.
Analysis of specific Ukrainian cases, including AI-supported tools and systems.
Identification of Ukraine's integrated system 'iCase' facilitating cooperation among anti-corruption bodies.
Demonstration of machine learning and blockchain in large data analysis and asset tracking.
Recognition of challenges like algorithm bias and legal gaps in relation to AI and digital assets.

Abstract

The purpose of the study was to analyse the Ukrainian and international experience of using artificial intelligence (AI) in the investigation of official offences and develop recommendations for adapting best practices to the Ukrainian legal system. The research methodology was based on a comparative analysis of the regulation and practice of AI implementation in Ukraine, the USA, Great Britain, Australia, and Brazil, with the examination of technological mechanisms of functioning, legal guarantees in law enforcement activities. The study established the specifics of the Ukrainian approach to the implementation of technologies through the creation of an integrated system “iCase”, which provided electronic interaction between the National Anti-Corruption Bureau of Ukraine, the Specialised Anti-Corruption Prosecutor’s Office, and the High Anti-Corruption Court, in contrast to the fragmented implementation in other countries. Technological solutions are systematised: machine learning for analysing large amounts of data, explanatory AI, digital forensics with nine phases of evidence processing, and blockchain analytics for tracking virtual assets. Ukrainian cases were analysed: arrest of Tether, Tron, Ethereum cryptocurrencies in Case No. 991/1512/23 of the Supreme Anti-Corruption Court, verdict in case No. 991/3227/24, risk assessment system in public procurement with 21 automatic indicators, and use of open-source intelligence techniques by the National Anti-Corruption Bureau of Ukraine. International experience has demonstrated the effectiveness of AI, in particular, in the cases of Rolls-Royce, Operation Gold Rush, the work of the European Prosecutor’s Office, and the use of the Brazilian bot ALICE. Critical challenges were identified: the problem of the “black box” of algorithms, the risks of system bias, legal gaps in relation to digital assets, and the need to harmonise with the EU AI regulation 2024/1689. The results of the study can be used by anti-corruption bodies in the implementation of AI technologies, the judicial system – to form a unified practice for evaluating digital evidence, legislative authorities – in the development of special legislation on AI, and scientific-educational institutions – to train qualified personnel in the field of digital crime investigation

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