Artificial Intelligence and Deficit of Personnel in the Romanian Police
Artificial Intelligence and Deficit of Personnel in the Romanian Police

Summary/Abstract: The purpose of the article. Staff shortages in Romania’s Police and Border Police have reached critical levels, with vacancy rates of 15% to over 28% in several counties. These shortfalls impose direct financial burdens through overtime, standby pay, and productivity losses while also degrading service quality. This article assesses whether — and to what extent artificial intelligence can offset these gaps and reduce the related fiscal strain. Drawing on international case studies, Romanian staffing data, and recent literature on public-sector digitalization, the study argues that targeted AI deployment can shift the emphasis from a quantitative staffing model to a qualitative efficiency model. The central hypothesis is that automating administrative and surveillance tasks with AI could substitute for roughly 15–25% of current personnel vacancies in Romanian law enforcement without proportional budget increases. The article also addresses principal risks algorithmic bias, privacy concerns, and governance gaps and proposes a phased implementation framework consistent with the EU regulatory requirements. Methodology: The study uses comparative cases, Romanian staffing data, and EU – national policy analysis to assess AI’s governance and fiscal implications in policing, acknowledging its conceptual, document‑based design and lack of primary data. Results of the research: Romania’s severe police vacancies create safety and fiscal pressures, with understaffing driving overtime, reduced service quality, and declining trust. Targeted AI could offset part of the gap cost-effectively, but cannot replace human roles and requires strong governance. A phased national strategy and further empirical research remain essential for future implementation.

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