Integration of artificial intelligence into forensic practice: from data analysis to decision making

The article examines the use of artificial intelligence technologies in criminalistics within the framework of digital transformation of criminal proceedings and the growing role of digital evidence. The author analyzes the theoretical, legal, and practical dimensions of implementing intelligent systems in the activities of law enforcement agencies, emphasizing issues of algorithm interpretability, data reliability, and accountability for machine-generated results. Methodological distinctions between expert evaluation and algorithmic analysis are clarified, and potential risks related to fairness and the presumption of innocence are discussed. The study reviews international developments in regulating the use of artificial intelligence in criminal justice, including initiatives of the European Union, the United States, and the United Nations. Using Kazakhstan as a case study, the article highlights institutional and technological prerequisites for integrating AI into investigative practice and presents the outcomes of pilot projects by the Ministry of Internal Affairs focused on automating digital trace analysis, visual data recognition, and crime forecasting. The author concludes that transparent and verifiable standards of AI use must be legally established to ensure accountability and protection of rights. The article emphasizes the need for systematic professional training, interagency collaboration, and the creation of a unified national registry of intelligent technologies applied in investigative and forensic work.

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