The integration of AI into judicial systems represents a consequential and underregulated transformation in modern governance. This study is anchored in the accountability gap framework, which argues that autonomous systems create a gap between human agency and legal responsibility, and in the principle of due process, which requires procedural compliance and protection of fundamental rights in AI-mediated decisions. The study evaluates the opportunities and risks associated with AI in legal document automation, case management, predictive analytics, and decision-making. The study analyzes the ethical, legal, and practical challenges AI poses to judicial systems, including bias, accountability, transparency, and data protection. A qualitative methodology, including doctrinal analysis and document review, examined legislation, case law, and institutional frameworks, supported by empirical illustrations. The findings highlight efficiency gains, improved access to justice, and enhanced analytical capabilities. In response to the identified risks, the research recommends establishing ethical oversight boards, maintaining AI transparency logs, developing hybrid human-AI decision-making frameworks, and implementing robust legislative mechanisms. AI offers unprecedented advances in case management, improved legal research, and more consistent analytical support for judicial decision-making. Its deployment must be carefully and strictly regulated. The paper concludes that efficiency and fairness are not inherently opposed, but that realizing both requires moving beyond technical fixes toward structural legal reform.
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