Context

• The integration of Artificial Intelligence (AI) into judicial processes represents one of the most significant shifts in the administration of justice in recent years.
• In July 2025, the Kerala High Court became the first judicial body in India to release a policy regulating the use of AI in the district judiciary.
• This policy is timely and forward-looking, given the enormity of India’s judicial backlog—over five crore pending cases, and the potential of AI to introduce efficiency, accuracy, and speed into a strained system.
• However, while the allure of AI-enabled efficiency is undeniable, its risks and ethical implications demand equal attention.

The Promise of AI in Judicial Processes

• AI tools offer numerous advantages for courts, particularly in automating routine tasks.
• Document translation, transcription, defect identification in filings, and legal research can all be significantly accelerated through AI integration.
• For a system plagued by excessive pendency and resource constraints, these efficiencies are attractive incentives.
• Pilot projects in Indian courts have already explored AI transcription of oral arguments and witness depositions, with the potential to standardize records and reduce delays.
• Beyond speed, AI can also increase accessibility by providing translations in regional languages, ensuring litigants and lawyers from diverse linguistic backgrounds can engage more effectively.
• Moreover, AI-powered data analysis may help in identifying case patterns, facilitating judicial reforms, and streamlining case management.

Risks and Challenges

• Translating and Transcription Errors
  • Instances such as the mistranslation of leave granted into holiday approved or transcription software mistaking Noel for no underscore the dangers of over-reliance on imperfect systems.
  • Large Language Models (LLMs), while powerful, are prone to hallucinations, generating false case laws or misrepresenting facts, an unacceptable risk in legal contexts where accuracy is paramount.
• Lack of Clear Framework
  • AI risks reducing adjudication into mechanical, rule-based outcomes, neglecting the contextual interpretation, human reasoning, and moral judgment that underpin justice.
  • Furthermore, without clear frameworks for data storage, access, and security, the use of sensitive personal information through AI could lead to breaches of privacy.
  • Market-driven pilot projects offered on a test basis risk creating dependencies without long-term sustainability, especially in the absence of supporting infrastructure such as reliable internet connectivity and secure digital systems.
• Absence of Robust Risk Management
  • Equally concerning is the absence of robust risk management frameworks in AI procurement by courts.
  • Current practices reveal little attention to ethical safeguards, technical accountability, or error mitigation.
  • Even where human oversight exists, such as retired judges manually vetting AI translations, the problem remains that AI systems continuously learn and adapt, introducing new forms of error in evolving contexts.

Safeguards and Frameworks for Responsible Adoption

• AI Literacy
  • Judges, lawyers, and court staff require training not just in using AI tools but also in understanding their limitations and risks.
  • Judicial academies and bar associations, working alongside AI governance experts, can lead capacity-building programmes that equip legal professionals to critically assess AI outputs.
• Clear Guidelines
  • Second, Clear Guidelines must govern the individual use of generative AI in research and judgment writing.
  • Litigants should have the right to know if AI has been used in a case, whether for transcription, legal research, or drafting.
  • Courts may also consider offering litigants the right to opt out of AI-assisted proceedings, ensuring respect for individual consent and safeguarding against blind reliance on machines.
• Standardised Procurement Frameworks
  • These should include pre-procurement assessments to evaluate whether AI is the most suitable solution, followed by strict criteria for explainability, accountability, and data security.
  • Such frameworks can help courts monitor vendor performance and compliance with ethical and legal standards, tasks that often extend beyond judicial expertise.

The Way Forward

• As Indian courts cautiously move toward AI adoption, it is essential not to lose sight of the ultimate purpose of judicial processes, the pursuit of justice.
• Efficiency cannot come at the cost of fairness, transparency, or accountability.
• The challenge lies not in rejecting AI altogether but in ensuring its careful, ethical, and context-sensitive adoption.
• If deployed with appropriate literacy, guidelines, procurement frameworks, and institutional support, AI can become a valuable ally to the judiciary.

Conclusion

• The Kerala High Court’s initiative in laying down the first policy framework for AI in the judiciary is a critical milestone.
• It signals recognition of both the transformative potential of AI and the urgent need for safeguards.
• As courts across the country experiment with digital solutions, the key lies in ensuring that technology enhances human judgment rather than displaces it.