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Incident 1573: National Company Law Tribunal Reportedly Relied on AI-Hallucinated Precedents in Pooja Ramesh Singh v. Jammu and Kashmir Bank Ltd

Description: In Pooja Ramesh Singh v. Jammu and Kashmir Bank Ltd., India's National Company Law Tribunal (NCLT) reportedly admitted insolvency proceedings against Essel Infraprojects after relying on six purported precedents later found to be fabricated or materially inaccurate. The appellate tribunal upheld the ruling, but the Supreme Court later invalidated both decisions and sent the insolvency petition back to the NCLT for a new ruling.
Editor Notes: Timeline notes: The incident ID date is 08/28/2024, based on the NCLT ruling that relied on purported precedents later identified as AI-generated. On 07/02/2026, the Supreme Court invalidated the tribunal rulings and directed that the insolvency case be reconsidered. The incident ID was created on 07/07/2026.

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Alleged: Large language model developers and AI research tool developers developed an AI system deployed by National Company Law Tribunal and Courts, which harmed Essel Infraprojects Ltd , Pooja Ramesh Singh , Parties to insolvency proceedings , Epistemic integrity and Judicial integrity.
Alleged implicated AI systems: Large language models and AI research tools

Incident Stats

Incident ID
1573
Report Count
1
Incident Date
2024-08-28
Editors
Daniel Atherton

Incident Reports

Reports Timeline

Incident OccurrenceAI hallucinated judgments: Why Supreme Court set aside a tribunal order
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AI hallucinated judgments: Why Supreme Court set aside a tribunal order

AI hallucinated judgments: Why Supreme Court set aside a tribunal order

indianexpress.com

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AI hallucinated judgments: Why Supreme Court set aside a tribunal order
indianexpress.com · 2026

Six AI-hallucinated judgments formed the basis for the Supreme Court's striking down of an order passed by the National Company Law Tribunal (NCLT) on Thursday.

Three of the cited judgments did not exist, while the remaining three either di…

Variants

A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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