Artificial Intelligence is increasingly being integrated into crime detection through predictive policing, facial recognition, crime-mapping, cyber-surveillance and financial fraud detection systems. While these technologies may enhance efficiency, speed and pattern recognition in law enforcement, their concentration in the hands of the State and a limited number of private technology vendors creates a distinct form of “AI monopoly” in criminal justice. This paper examines AI monopoly not merely as economic market dominance, but as functional control over data, algorithms and institutional policing infrastructure. The study aims to analyse the operational role of AI in contemporary crime detection, critically assess the impact of monopolised AI systems on investigation and surveillance practices, and propose regulatory safeguards to ensure accountability. Adopting a doctrinal and analytical approach, the paper evaluates the interaction between AI-driven policing and constitutional principles of equality, liberty, privacy, due process and procedural fairness. It argues that monopolised crime-detection technologies may reproduce historical bias, create feedback loops of over-policing, obscure decision-making through black-box algorithms and reduce the scope for independent human judgment. The paper further identifies the absence of a specific legal framework governing AI-based policing as a major regulatory gap. It recommends a rights-oriented accountability model based on data transparency, independent auditability, responsible data governance, human-in-the-loop decision-making, judicial oversight and statutory safeguards. Finally, the paper argues that constitutional values such as non-discrimination, privacy, fairness and due process must be embedded into the design, deployment and review of AI systems so that technological efficiency does not override the humane and constitutional foundations of criminal justice.