July 13, 2026, (Inside AI) — The Supreme Court of India has released a draft regulatory framework for artificial intelligence in the judiciary, setting strict boundaries on algorithmic decision-making while pushing courts to adopt AI for administrative efficiency. The draft, titled Regulations for Use of Artificial Intelligence in Courts, 2026, is open for public comment until July 15.
The regulations arrive as judiciaries worldwide grapple with AI's dual promise and peril. India’s approach is notably prescriptive: it outright bans certain high-risk applications, mandates human oversight for all judicial outcomes, and establishes a multi-tiered governance structure. The framework will not apply uniformly—it comes into force for the Supreme Court on a date notified by the Chief Justice of India, while High Courts and subordinate courts will adopt it on dates set by their respective Chief Justices, allowing phased implementation.
The draft marks one of the most detailed judicial AI policies globally, going beyond high-level principles to specify permitted uses, prohibited practices, audit requirements, and grievance mechanisms. Yet it leaves critical questions unanswered, particularly around enforcement, algorithmic transparency, and the practical capacity of courts to conduct in-house technical audits.
The Permissible and the Forbidden
Courts are directed to "actively seek opportunities" to deploy AI that demonstrably improves access to justice, reduces delays, or enhances administrative efficiency. Permitted functions include case management, transcription, translation, legal research, document summarization, accessibility tools, and court administration. Any such deployment requires written approval from the Supreme Court’s Apex Body or a High Court’s AI Committee, plus supervision by nominated officers.
However, the regulations draw an "absolute and non-derogable" line against several uses. These include risk scoring for flight risk or bail eligibility, predicting recidivism, assessing witness credibility, and any AI that predicts or profiles future behavior of parties, accused persons, witnesses, or lawyers. AI-generated output cannot be submitted as independent evidence without full disclosure of its AI character. Black-box AI systems—those whose decision-making cannot be explained—are banned in matters affecting personal liberty.
This categorical prohibition contrasts with approaches in jurisdictions like the United States, where risk assessment tools such as COMPAS have been used in sentencing despite controversy over bias. India’s draft preempts such debates by foreclosing these applications entirely, a move that legal scholars say reflects the country’s heightened sensitivity to algorithmic discrimination given its vast and diverse population.
“No judicial outcome shall be reached through algorithmic decision-making alone, or solely on the basis of AI-generated information,” the draft states. AI’s role in decision-making is strictly advisory, subject to independent human evaluation. This aligns with the European Union’s AI Act, which classifies certain AI uses in law enforcement and judiciary as high-risk, requiring human oversight. But India’s draft goes further by explicitly naming prohibited use cases rather than relying on broad risk categories.
Governance, Transparency, and Vendor Guardrails
The institutional architecture is led by an Apex Body at the Supreme Court, comprising sitting Supreme Court and High Court judges, a Ministry of Electronics and Information Technology official, and experts in finance and cybersecurity. It will set minimum mandatory standards and issue implementation guidelines, working through five specialized committees. Each Supreme Court and High Court will have its own AI Committee and Secretariat. A new Centre of Research and Excellence on Artificial Intelligence (CoRE-AI) will evaluate tools and track developments.
Private vendors can participate only with written court approval and must adhere to strict contract terms. They cannot claim exclusive intellectual property over tools built substantially on judicial data or public resources. Vendor agreements must bar use of sensitive judicial data for model fine-tuning without the AI Committee’s written consent. This addresses growing concerns about public-private partnerships in judicial AI, where commercial interests could conflict with judicial independence.
Transparency for litigants is mandated but not absolute. Courts must inform parties when AI provides "material assistance" in case management, document analysis, or judicial administration. Routine AI use, such as basic transcription, may not trigger disclosure. This standard mirrors debates in the U.S. over disclosure of AI use in legal proceedings, where some argue for full transparency while others warn of unnecessary alarm over low-risk tools.
Safety measures follow a lifecycle approach. Before deployment, a Technical and Ethical Impact Assessment must cover system architecture, training data, bias, hallucination risks, and cybersecurity. Some systems may require Controlled Environment Testing in an isolated setup. After deployment, technical, legal, and ethical audits—plus separate cybersecurity audits—are required on the same cycle. Crucially, these audits must be conducted in-house because source code and training data cannot be shared with third parties. This poses a significant challenge: few courts have the in-house expertise to audit complex AI systems, raising doubts about practical implementation.
Each court must maintain an AI Register of approved systems and audit outcomes. An AI Incident Database will log malfunctions, errors, and biases, with a mandatory 24-hour notification if a tool fails or is suspended. High Courts must also have emergency fall-back protocols to revert to manual processes during system outages.
If a prohibited AI use causes harm, an affected party can file an application with the relevant court, which must grant a hearing and pass appropriate orders. High Courts may simplify procedures for those with limited legal literacy. This grievance mechanism sits alongside any other legal remedies available under ordinary law, but its effectiveness will depend on how courts interpret "appropriate orders"—the draft provides no guidance on compensation or corrective measures.
The draft regulations represent a significant step toward governing AI in one of the world’s largest judicial systems, but their success hinges on implementation capacity, judicial training, and the willingness of courts to enforce vendor compliance. As the July 15 comment deadline approaches, stakeholders are likely to push for clearer audit standards, stronger accountability for AI failures, and mechanisms to ensure that the promise of efficiency does not erode due process.
