The rapid advancement of Artificial Intelligence is reshaping the foundations of modern governance, with policing emerging as one of its most transformative frontiers. In an AI-driven society, law enforcement is no longer confined to reactive patrols and traditional investigative methods; instead, it is increasingly guided by algorithms capable of detecting patterns, forecasting risks, and optimizing operational decisions. This conceptual and analytical study explores how AI technologies are redefining the structure, strategies, and accountability mechanisms of contemporary policing. Rather than viewing AI merely as a technical upgrade, this article critically examines its broader institutional and societal implications. It analyzes how predictive analytics, automated surveillance, and data integration systems influence decision-making processes, resource allocation, and crime prevention models. At the same time, it interrogates the ethical tensions embedded in algorithmic governance, particularly concerns surrounding bias, transparency, civil liberties, and democratic oversight. By synthesizing technological, legal, and ethical perspectives, the study argues that the future of policing depends on harmonizing innovation with principled regulation and human judgment. Digital justice, therefore, is not solely about efficiency or technological sophistication; it is about constructing a model of law enforcement that remains accountable, equitable, and aligned with the core values of justice in an increasingly data-centric world.
Chauhan et al. (Mon,) studied this question.