Artificial intelligence in municipal police – Implementation perspective

Research objective: This study examines how artificial intelligence can transform the operations of municipal police forces in response to growing public safety challenges. It compares Poland with Italy, Spain, and France to identify effective and low-cost solutions by 2030. Methodology: A descriptive review of over 20 publications and reports (2022–2025); comparative analysis of operational data; chi-square and regression tests in relation to city size and available resources. Main findings: In 2023, approximately 407,000 reports were recorded in Warsaw, over 75% of which concerned minor offenses. Given existing staff shortages, this poses a serious challenge. In response, AI-based solutions such as real-time event detection, patrol route optimization, and automatic violation recognition are being increasingly implemented, significantly reducing time and resource losses. A successful example of such technology use is the 2025 pilot project in Busto Arsizio, where data analysis enabled real-time alerts. Moreover, statistical analyses revealed significant differences between countries (χ²; p < 0.001; φ ≈ 0.21) and a very strong correlation between the number of residents and the number of interventions (R² ≈ 0.97). Tools such as license plate recognition and predictive threat mapping offer relatively low-cost yet effective automation, allowing for the reallocation of some resources to community-oriented actions. At the same time, implementing AI in municipal police units must be accompanied by reinforced privacy protection, reduction of algorithmic bias, and building public trust. In line with the EU AI Act, only such an approach enables responsible and socially acceptable use of new technologies. Application of the study: A phased implementation of new technologies is recommended, beginning with AI-enhanced CCTV systems, followed by citizen-reporting chatbots, and later the use of drones for monitoring environmental offenses. The proposed solutions are adapted to the actual financial capabilities of local institutions. The comparative analysis provides a solid foundation for developing a responsible AI implementation plan that complies with legal requirements and ethical standards. Originality/Novelty of the study: This is one of the first studies in Poland combining quantitative data analysis with practical AI innovation proposals for municipal police forces. Thanks to a structured approach, unique integration scenarios were developed, addressing a gap in research on digital transformation and legislative frameworks.