Areas of application of artificial intelligence in law enforcement: Trends, challenges and prospects

The escalation of security challenges in the context of digital transformation highlights the need for a systematic review of current practices, risks and the potential for implementing artificial intelligence in law enforcement activities. The aim of this study was to summarise scientific approaches to the application of artificial intelligence in law enforcement, focusing on the stages of its development, key areas of research and insufficiently studied aspects. The use of methods of analysis and synthesis of scientific sources, content analysis, comparative analysis, and classification of existing approaches made it possible to assess the current state of scientific research on trends, challenges, and prospects for the use of artificial intelligence. It has been established that scientific interest in the application of artificial intelligence in law enforcement has increased significantly over the last decade. The rapid development of artificial intelligence technologies has opened up new opportunities for the automation of analytical and operational functions, prompting scientists to study the possibilities and threats of artificial intelligence. Researchers focus primarily on areas such as video analytics, crime prediction, image recognition, and big data processing. At the same time, there is a lack of in- depth interdisciplinary research that takes into account the ethical, legal, and social implications of using such technologies. A disparity in approaches to risk classification and standardisation of implementation practices has been noted. The need for the formalisation of research has been demonstrated, which will contribute to the balanced development of artificial intelligence in law enforcement activities, taking into account security, legal, and humanitarian factors. The results obtained can be used by heads of law enforcement agencies, analytical units, and digital transformation specialists to determine priority development directions and consider potential risks