Differentiated Case Management Integrated Artificial Intelligence in the Case Management System in Indonesian Courts

The case management system in Indonesia still applies a one-size-fits-all approach, leading to disparities in case resolution times and inefficiencies in managing court workloads. This study aims to develop a Differentiated Case Management (DCM) model integrated with Artificial Intelligence (AI) to enhance the efficiency of case handling in Indonesia. The research employs a normative juridical approach with a comparative study of DCM and AI implementations in various jurisdictions, as well as an analysis of regulations and legal policies in Indonesia. The findings indicate that DCM enables the classification of cases based on complexity levels, evidence requirements, and urgency, allowing for a more proportional allocation of judicial resources. The integration of AI into DCM can automate the case categorization process through Natural Language Processing (NLP) analysis of legal documents and case metadata, thereby reducing administrative burdens and improving the accuracy of case resolution time predictions. The implementation of AI- DCM also facilitates real-time case monitoring through the court information system, which can identify potential delays and optimize trial scheduling. This study recommends the development of specific regulations regarding the use of AI in case management, as well as the gradual implementation of the AI-DCM system through pilot projects in several courts before nationwide adoption. With this approach, Indonesia’s judicial system is expected to achieve higher efficiency, reduce case backlogs, and enhance transparency and accountability.