The current widespread use of artificial intelligence (AI) in law enforcement represents a paradigm shift towards intelligence-led, predictive and data-driven criminal management, resulting in unprecedented advances in operational efficiency and strategic decision making globally. While these developments characterise AI policing in some world nations, their use in resource-constrained, post-conflict situations such as the Sierra Leone Police (SLP) is unclear. Using the medium-sized criminal investigation department (CID) of the SLP, the study on which this paper is based examined the effect of AI on the operational performance of the SLP, considering the mediating and moderating effect of green management (GM). A survey research design was employed, following a quantitative and deductive approach. A total of 181 out of 196 staff members at the CID headquarters were sampled. Primary data was collected using a structured and validated questionnaire and analysed using inferential statistics, with Smart PLS-SEM as the analytical tool. The findings revealed a statistically significant positive effect of AI on the operational performance (OP) (β = 0.356, t = 4.054, p < 0.001) of the SLP CID while the moderating interacting effect (AI*GM) on OP is negative and statistically significant (β = –0.221, t = 2.517, p = 0.012). On the other hand, the indirect effect (mediating role) of AI on OP through GM is positive but insignificant (β = 0.067, t = 1.906, p = 0.057). The study concluded that deliberate investment in AI and conscious consideration of GM will be a strategic tool for boosting policing and small and medium-sized establishments. Therefore, this paper recommends deliberate investment, proper implementation and constant monitoring of the usage of AI tools alongside GM, which will boost the general OP of police establishments and specifically bring them up to speed in meeting the demand for global practices. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
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Oluwajuwon Gabriel Ariyo
Edafe Bawa Dogo
Temitayo A. Joshua
Journal of AI, robotics & workplace automation.
Redeemer's University
RED Consulting (Norway)
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Ariyo et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69a75c7ec6e9836116a256a4 — DOI: https://doi.org/10.69554/krjs3546