The Supreme Court of India’s draft Regulations for the Use of Artificial Intelligence in Courts, set for implementation in 2026, establishes a critical boundary in the integration of AI within the judicial system. While AI is welcomed for aiding in legal research, drafting, translation, and other court-related tasks, it is explicitly prohibited from making judicial decisions, predicting outcomes, or substituting judicial judgment.
The Need for a Provenance Record
A pressing operational question arises: What records should accompany AI-assisted materials filed in court? Merely disclosing AI usage is insufficient. Legal professionals and parties might reveal AI involvement in preparing pleadings, transcripts, translations, or other materials. However, disclosure does not adequately address potential disputes over the AI’s output. Questions regarding source materials, modifications, tools used, human oversight, citation verification, and file preservation must be addressed to ensure accountability.
Risks of AI-Generated Misrepresentation
The issue of AI-generated inaccuracies is not theoretical. The Indian legal community is already grappling with AI-produced fake citations and non-existent legal authorities. The Bar Council of India has made it clear that advocates cannot evade responsibility for false citations by attributing them to technology. The Supreme Court has similarly voiced concerns over reliance on AI-generated fictitious judgments.
Such incidents highlight the risk of outright falsehoods in AI-generated content. However, subtler risks also exist, such as AI altering the evidentiary character without overt fabrication. Translations may alter meanings, summaries might omit essential context, and enhanced images could misrepresent details. The real concern is not just AI usage but whether its application can be reconstructed and verified.
Implementing a Practical Provenance Record
A practical provenance record does not need to be overly complex. For most filings, a concise record should suffice, detailing the nature of AI assistance, the tool category, the source material, human review, verification steps, and whether original files are preserved. In cases involving electronic evidence, additional metadata, hash values, chain-of-custody information, or tool logs might be required.
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This approach is not about transforming every AI-assisted filing into a forensic investigation, which would stifle court processes. Instead, when questions of authenticity, source, alteration, evidentiary weight, or authorship arise, courts should not rely solely on checkbox disclosures.
Judicial Discretion and Risk-Sensitive Approaches
Judicial discretion remains paramount. AI-assisted records should not be automatically deemed inadmissible simply because AI was involved. Instead, a risk-sensitive approach is necessary. Routine formatting assistance should not face the same scrutiny as AI-enhanced audio, AI-generated images, or AI-assisted translations of critical evidence. Courts may require only a basic declaration in some cases, while others might necessitate detailed integrity statements or expert examinations.
Strengthening Draft Regulations
The draft regulations could benefit from refinement. While distinguishing between permitted and prohibited AI uses is helpful, it does not fully address the nuances. AI tools that shape judicial summaries or registry communications should warrant more stringent records, logs, and verification controls.
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The same logic applies to AI-assisted content in courts. If AI plays a significant role in generating court notices, translations, or registry communications, the institution must be able to verify AI involvement, the system used, human review, and document traceability. Without such records, auditability becomes merely theoretical.
Advocates’ Responsibilities and Litigation Hygiene
A filing provenance record also supports advocates by encouraging practical discipline when relying on AI-generated output. Lawyers must ensure source material can be produced, citations verified, and original documents presented. Courts should be able to discern AI’s impact and the human review process.
When it comes to AI-assisted or synthetic evidence, stronger filing records are essential. Images, audio, video, translations, summaries, and data extracts can be materially altered in subtle ways. In cases where such material is crucial for proving identity, conduct, communication, or other key issues, source preservation is vital.
Courts should have the authority to request original files, metadata, system logs, and provenance records when the issue is material. Forensic examination or expert review may be necessary where required.
Navigating Between Extremes
The goal is to avoid two extremes: blind acceptance and blanket suspicion. AI-assisted filings can be appropriate when their source, review, and integrity are demonstrable. The Supreme Court’s draft regulations advance the conversation beyond vague AI ethics, emphasizing AI’s subordination to judicial authority. The next step is operationalizing this principle in legal filings, registry communications, and electronic evidence.
Ultimately, the core question for Indian courts should be: If AI helped create or modify this material, can the source and process be demonstrated? If yes, the court can evaluate relevance, authenticity, and evidentiary weight. If no, disclosure becomes a mere label devoid of substance. AI can assist the legal system but should not complicate the verification of legal records.
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Abhishek G Sharma is the Founder and CTO of EU AI Compass and Move78 International, a Hong Kong-based cybersecurity, AI governance, and enterprise risk advisory firm.
