In recent years, India’s judicial ecosystem has increasingly turned to adopting artificial intelligence to support judicial administration and make justice delivery more efficient and responsive. However, the usage of AI within digital contexts also raises significant questions related to fairness, transparency, accountability, privacy, and the protection of fundamental rights.  As AI systems increasingly intersect with processes that affect legal outcomes and access to remedy, ensuring that their adoption is governed by clear, rights-based, and institutionally grounded frameworks becomes essential to preserving the integrity, legitimacy, and equity of the justice system.

In this context, the United Nations Development Programme (UNDP) in India, in partnership with DAKSH and the Digital Futures Lab, undertook the report AI for Justice: Ethical, Fair and Robust Adoption in India’s Courts. The report provides a comprehensive assessment of the emerging use of artificial intelligence within Indian courts, examining how AI tools are currently being introduced, the governance gaps that accompany their deployment, and the implications for judicial integrity, access to justice, and the protection of rights.

Key Insights

• AI adoption in Indian courts is expanding but remains fragmented and insufficiently governed. 
  AI tools are being introduced primarily through isolated pilots and experimental initiatives, often without clear documentation, defined objectives, or consistent evaluation mechanisms. This limits institutional visibility over where and how AI is being used and weakens accountability within the judicial ecosystem.
• Efficiency-driven deployment frequently outpaces institutional readiness. 
  Courts are adopting AI solutions to address caseload pressures and administrative inefficiencies without systematic assessment of their human, technical, and financial capacity to deploy, oversee, and sustain these systems responsibly over time.
• Judicial contexts amplify rights-based risks associated with AI use. 
  The deployment of AI in courts raises heightened concerns related to fairness, transparency, explainability, privacy, and due process, particularly given the sensitive nature of judicial data and the potential impact of AI outputs on legal outcomes and access to remedy.
• Governance and accountability frameworks remain underdeveloped. 
  The absence of standardized approaches to risk assessment, vendor evaluation, human oversight, and post-deployment monitoring increases dependence on private technology providers and poses risks to judicial independence, public trust, and equitable justice delivery.

The Four-Part Assessment Approach

In response to the governance, rights-based, and institutional gaps identified in the assessment, the report proposes a structured, risk-based approach to guide the responsible adoption of artificial intelligence within the Indian judicial ecosystem through utilizing the four-part assessment approach. 

• Institutional Readiness Assessment 
  This framework supports courts in evaluating their preparedness to adopt AI responsibly. It examines governance structures, human and technical capacity, financial sustainability, and internal accountability mechanisms necessary to oversee AI systems effectively.
• Risk Assessment 
  The risk assessment framework enables courts to identify potential harms associated with specific AI use cases, including risks to fairness, equality, privacy, and due process. It supports decision-making on whether a proposed application should proceed, require additional safeguards, or be deemed unsuitable for judicial use.
• Technical and Vendor Assessment 
  This component provides a structured method for evaluating AI tools and technology providers, focusing on data governance, model transparency and explainability, robustness, cybersecurity, and compliance with legal and ethical standards.
• Ongoing and Continuous Assessment 
  Recognizing that risks evolve over time, this framework supports post-deployment monitoring of AI systems. It emphasizes performance evaluation, impact assessment, documentation, grievance redress mechanisms, and periodic review to ensure sustained accountability.

How to Use These Frameworks

These assessment tools are designed to function as a sequenced and documented decision-making process for courts considering AI adoption. Each workbook contains structured indicators, scoring logic, and summary outputs that must be completed in full before progressing to the next stage. For more details on the use of these frameworks, please refer to the full report (linked below).

Watch this video for an introduction to, explainer of, and demonstration of these assessment tools.