The Impact Of Artificial Intelligence / Machine Learning For Improvement Of Indian Justice System: A Detailed Study

Abstract

This study examines the transformative potential of artificial intelligence (AI) and Machine learning (ML) in addressing systemic improvements within India’s judicial system, particularly in the context of a rapidly growing democracy of 1.4 billion people and a daunting backlog of over approx. 48 million pending cases. Framed in the context of India’s digitalization journey-initiated through the National Policy and Action Plan for ICT in the Judiciary (2005) where Phase I (2011-2015) laid digital infrastructure foundations for courts, Phase II (2015-2023) expanding citizen centric services and Phase III ( starting 2023 – Present) prioritizes AI/ML integration for intelligent case management and paperless courts.
Employing a mixed-methods approach combining quantitative analysis metrics and qualitative insights from judicial stakeholders, the study identifies critical determinants of AI/ML adoption. Findings reveal that prior exposure to basic IT systems-such as digital case management software, legal search engines significantly accelerate AI readiness, with specialized legal tech software reducing errors by 50% in document review tasks. However, high implementation costs for setting up end-user digital infrastructure, regulatory framework including cybersecurity, data governance or even staff training, emerge as persistent barriers, disproportionately affecting rural jurisdictions. Efficiency gains are evident as AI-driven transcription systems reduce hearing durations significantly, while automated legal research platforms cut document review hours by 40%.
The research underscores systemic challenges, including a generational divide in technological literacy, with majority of staff lacking formal AI training. Regulatory gaps in data privacy and algorithmic transparency further hinder adoption, while India’s linguistic diversity complicates NLP deployments, as most tools support only English and Hindi. The study highlights the role of standardized IT systems in boosting client satisfaction and the cost-effectiveness of AI-powered contract drafting tools.
The conclusion emphasizes that successful AI/ML integration requires targeted investments in digital infrastructure, standardized training programs, and inclusive policy frameworks addressing linguistic, cultural, and socioeconomic disparities. By bridging these gaps, India’s judiciary can leverage AI to reduce its case backlog and democratize access to justice. The findings underscore the need for a balanced approach that prioritizes constitutional values while harnessing technological innovation to align with global benchmarks for judicial modernization.