Law enforcement agencies increasingly leverage AI across critical functions, from predictive policing, surveillance and facial recognition to automated report writing and forensic analysis, to expand their capacity and improve case outcomes.

In predictive policing, AI models analyse historical crime patterns, demographics and environmental factors to forecast crime hotspots. However, this enables pre-emptive deployment of officers and more efficient resource allocation.

Facial recognition technology matches images from CCTV, body cameras or telescopic data against criminal databases. Meanwhile, NLP supports faster incident reporting, body-cam transcriptions and keyword scanning of digital evidence.

Despite clear benefits, risks persist. Algorithmic bias may unfairly target specific groups. Privacy concerns grow where systems flag individuals without oversight.

Automated decisions also raise questions on accountability, the integrity of evidence, and the preservation of human judgement in justice.