The integration of Artificial Intelligence (AI) and Machine Learning (ML) is profoundly impacting the civil and criminal legal systems, particularly in India, where over 5 crore cases are pending across courts, including 59 lakh in High Courts, as per the National Judicial Data Grid (NJDG). While the judiciary has historically lagged in digital adoption, accelerated efforts, especially spurred by the COVID-19 pandemic’s push for e-filing and online hearings, are driving a gradual but significant shift towards e-governance. This digital transformation, supported by initiatives like India’s e-Courts Project, aims to enhance efficiency, accessibility, and transparency. Globally, AI/ML is being adopted for diverse applications, including smart case management, improved investigation through systems like CCTNS, predictive analytics for insights into case outcomes, streamlined legal research with tools for finding precedents and summarizing judgments (like India's SUVAS), and supporting decision-making in areas like evidence analysis and sentencing guidelines. However, this promising future necessitates careful consideration of ethical challenges such as algorithmic bias from flawed training data, the black box problem of opaque AI decision-making, accountability for AI-induced errors, and robust data privacy and security measures. The ultimate goal is to leverage AI and digitization to democratize justice delivery, making it more affordable and accessible for the public while enabling the State to deliver justice efficiently and transparently.