Artificial Intelligence (AI) promises to heighten human decision-making, including in court. AI sentencing would be better at detecting, organizing, and calibrating all of the variables correlated to sentencing, such as prior criminal records, educational background, substance abuse history, and employment history, resulting in consistencies that traditional sentencing may not be able to provide. AI pervades the Malaysian judiciary system when AI criminal sentencing was launched for the first time to augment the process of meting out sentences in Sabah courts. Despite its promising benefits, AI sentencing may infringe the fundamental principle of due process, presents unacceptable risks of error and implicit bias, and reliance on AI to predict recidivism which forms significant components of the rule of law. The rule of law guarantees that all entities are subject to and accountable to a clear and known law. It enables the judicial branch of the government to be independent and to resolve dispute in a fair manner while upholding the presumption of innocence and preventing the exercise of arbitrary powers. The present research, therefore, examines the use of AI in supporting court processes and human judges, discovering its technical characteristics, practical constraints, and legal theoretical consequences for decision-making processes. Employing jurisprudential analysis as the method of research, this research explores an adjudicatory paradigm that prefers standardisation over discretion, leading in the waning of the notion of rule of law pertinent to the justice system. The metamorphosis to AI adjudication will undoubtedly promote the growth of digitalized dispute resolution by providing efficiency and at least a semblance of impartiality, but it is also poised to birth concerns by making the legal system data-driven, alienating, and disillusioning. Keywords: Artificial Intelligence, Artificial Intelligence in Courts, Artificial Intelligence in Criminal Justice eISSN: 2398-4287© 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7iSI7%20(Special%20Issue).3813