India’s criminal justice system faces significant challenges, including a high percentage of under-trial detainees who are often denied bail due to systemic inefficiencies. This article explores the potential of integrating Artificial Intelligence-based Risk Assessment Instruments into India’s bail decision-making process to reduce pre-trial incarceration and enhance judicial efficiency. Drawing from global practices, the study examines how RAIs can offer objective, data-driven insights to supplement judicial discretion potentially mitigating biases in bail decisions. However, the implementation of AI in such sensitive contexts raises critical concerns about algorithmic bias, transparency, and due process. This paper critically assesses these ethical considerations and proposes safeguards, including explainable AI, vernacular access to information, legal oversight, and the crucial integration of human judgment in the loop. It advocates for a phased, constitutionally compliant implementation of RAIs supported by necessary legislative reforms, robust technical infrastructure, and comprehensive judicial training to ensure responsible AI implementation. Ultimately, this study contends that a carefully designed AI-human partnership within the bail system can significantly reduce India’s under-trial population while upholding the foundational principles of fairness, accountability, and inclusivity within the Indian justice system. This approach aims to enhance the efficiency and accessibility of the legal system while addressing the unique challenges posed by the Indian context.