Ethical AI Adoption in the Indian Judiciary: Strengthening Access to Justice

1. AI is increasingly seen as a way to improve efficiency and time management in court processes. For instance, the use of AI-enabled translation and transcription tools can speed up the transcription of depositions and arguments and help compensate for staffing gaps. Moreover, the use of GenAI tools like ChatGPT for tasks such as document drafting is indicative of the ubiquity and ease of access to this technology.
2. But current adoption trajectories are not guided by adequate thought about AI’s ethical risks and harms, or its technical limitations. Judges and policymakers do not perceive AI as a replacement for human decision-making, but more as a means to augment existing processes, and have, in general, called for a cautious approach. However, they may simultaneously be under-equipped to recognise these limitations.
3. Guiding frameworks that enable courts to decide how to select the best available AI tool and ensure adequate data protection frameworks can streamline AI acquisition. They can support courts in technical evaluation, risk assessment, and risk mitigation, overall ensuring the quality of AI tools. Further, AI adoption guidelines serve a way to integrate AI responsibly for public institutions that serve as upholders of the law. Such guidelines offer pathways to establish a systematic review and evaluation process to support safer, accountable, and responsible AI for courts. These can also help better evaluate vendors and products, and enable the establishment of post-contracting management systems to ensure sustainable use of technology.

Across India’s courts, there is a growing appetite for AI adoption. From translation and transcription tools to AI-enabled legal research, case management, and even scheduling, courts are increasingly seeing the value of these technologies. While adoption has largely been cautious, it has also been fragmented, often led by individual judges or through pilots, with no clear framework to guide long-term use.

This is where formal processes, such as procurement, become critical. AI holds promise, but also serious risks when deployed at scale in public institutions. Experiences from other jurisdictions, like errors in automated alimony calculations in the UK, highlight the dangers of unchecked implementation. For courts, where justice must not only be done, but be seen to be done, responsible pathways for AI adoption are essential.

At present, procurement in the judicial system is ad hoc. There are no clear rules for evaluating AI solutions, no safeguards to ensure vendors deliver on their promises, and little foresight about requirements for their continued use once pilot projects end. Questions around infrastructure costs, technical capacity, and the protection of sensitive judicial data remain unresolved. Institutional capacity for formal procurement processes is limited, as is the range of providers offering digital tools for courts. In such a scenario, developing voluntary guidelines as a first step towards institutionalising AI adoption processes can strengthen:

• Principled Adoption: Establish guiding frameworks that can be applied consistently across courts, different stages and use cases of AI in the judiciary.
• Risk Awareness and Mitigation: Provide courts with practical tools to assess and address ethical, technical, and sustainability risks associated with AI.
• Ease for Procurers: Streamline procurement processes to reduce burdens on already overstretched courts while enabling informed, efficient decision-making.
• Responsible Use of Public Finance: Ensure that investments in AI are accountable, transparent, and in the public interest.
• Transparency and Accountability: Build trust in how AI is deployed within the judicial system by setting standards that protect rights and safeguard sensitive judicial data.

In the long term, it is essential to build standardised processes, such as public procurement, as tools of accountability and trust, helping courts adopt AI in ways that are responsible, sustainable, and aligned with the public interest.

Our outputs - a report and toolkit - grow out of a foundational research and consultation process. We began by mapping how courts around the world are currently approaching AI adoption, producing a landscape report that proposes a rights and risk-informed framework tailored to the Indian legal context. Central to this framework is the recognition that risk and potential for harm vary significantly depending on case types, stages of proceedings, and the litigants involved.

To translate this framework into practice, we developed four assessment tools:

• Institutional Readiness: A diagnostic questionnaire helping courts evaluate whether their human resources, infrastructure, and finances are sufficient for the responsible design, deployment, and monitoring of AI tools.
• Risk Assessment: A structured mechanism for identifying potential risks across judicial processes — enabling courts to decide whether to proceed with AI deployment and, if so, what safeguards to put in place.
• Technical Assessment: A detailed vendor questionnaire that systematically examines credentials, technical capabilities, data governance, transparency, safety protocols, and accountability mechanisms.
• Ongoing Assessment: A set of questions for courts to continuously monitor impact and track whether the tool is meeting its intended goals after deployment.

The toolkit is intended to be dynamic, updated periodically to suit the needs of the judiciary and reflect practical considerations. We welcome all suggestions and feedback for the tools at hello@digitalfutureslab.in.