AI-Enabled Legal Report Management for JudicialAccuracy, Transparency, and Efficiency
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Abstract
The growing volume and complexity of legal documentation have exposed persistent weaknesses in traditional legal report management, including factual inaccuracies, procedural opacity, and administrative inefficiencies that undermine judicial performance. While digitalization initiatives have improved document storage and retrieval, they have largely replicated manual practices and failed to address the informational foundations of judicial decision-making. Against this backdrop, this study examines how artificial intelligence (AI) can be systematically embedded into Digital Legal Report (DLR) management to enhance accuracy, transparency, and judicial efficiency. The article adopts a conceptual– analytical methodology grounded in legal informatics, socio-technical systems theory, algorithmic governance, and information quality theory. Through structured literature synthesis and framework development, it designs an AI-enabled DLR management model that integrates natural language processing, machine learning– based validation, automated consistency checking, and governance-by-design safeguards across the legal report lifecycle. Comparative analysis is used to distinguish traditional and semi-digital practices from the proposed AI-enabled approach. The analysis suggests that AI-enabled Digital Legal Report (DLR) management systems have the capacity to substantially reduce reporting errors, enhance traceability and auditability, streamline administrative workflows, and strengthen decision-support functions, while preserving human legal authority and judicial discretion. The study’s originality lies in its reframing of legal reports as digitally native, intelligent, and governable legal artifacts, rather than as static documents, positioning legal information governance rather than automated adjudication as the primary locus of AI-driven judicial reform. The article concludes with policy and institutional implications for courts and justice-sector organizations, emphasizing responsible AI governance, human oversight, and phased implementation. It offers a practical pathway for judicial reform aimed at strengthening the informational integrity upon which fair, transparent, and efficient justice depends.
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