AI-Generated Fake Case Law in the Supreme Court: India’s First Brush With AI Fraud in Litigation

The revelation that the Supreme Court of India was presented with an entire set of fabricated judicial precedents—apparently generated by an artificial intelligence tool—did not merely trigger a moment of courtroom embarrassment on December 9, 2025. It marked a turning point in India’s legal and technological landscape, a moment when the abstract fears surrounding AI misuse abruptly collided with the realities of legal practice.

What unfolded during a high-stakes corporate dispute was not simply an error of research or an overreliance on technology. It was a warning flare for every institution that depends on the integrity of information. As the judges examined the rejoinder claiming to rely on “hundreds of judicial precedents,” they found that none of the citations existed. Not partially misquoted. Not mistakenly attributed.

Entirely nonexistent.

The Supreme Court called it a “deliberate misuse of artificial intelligence,” and even in a judicial environment accustomed to clever argumentation and strategic omissions, the shock was palpable. This was not merely sloppy lawyering. It was AI-driven fabrication making its first recorded entry into Indian litigation.

That this moment arrived may surprise many, but perhaps it should not. The past two years have witnessed an explosion in the adoption of generative AI tools marketed for speed, convenience, and automation. Some of these tools are impressively capable of distilling complex material. Others, especially unsecured or non-specialised models, rely on probabilistic text generation that can produce convincing but entirely imaginary information—a phenomenon now commonly referred to as “hallucination.”

It is easy to see how such tools, if used without rigorous verification, can become shortcuts that tempt busy lawyers or inexperienced researchers under pressure. Yet the legal profession does not operate like other fields. Here, precedent is not just a reference point but a cornerstone. A fabricated case is not a minor error; it is a direct assault on the integrity of judicial reasoning.

To understand why this incident has shaken legal and technological circles, it helps to recall a familiar warning from philosopher Hannah Arendt, who once wrote, “The moment we no longer have a shared grip on reality, we lose the conditions for justice.” What unfolded in the Supreme Court speaks directly to this fear. Courts depend on the authenticity of inputs. Judges assume that advocates—especially senior counsel—uphold their duty to present verified law. When that foundation crumbles, the entire system begins to wobble.

The incident itself unfolded with a rapid intensity. As media reports have described, a party in the corporate dispute submitted a rejoinder that relied on an enormous number of precedents, each presented with the confidence of settled law. But when the judges reviewed the citations, none appeared in official databases.

They were not available on SCC Online, not traceable through Manupatra, not present in Supreme Court reporters, and not even found in archived judgments. The opposing senior counsel promptly apologized, acknowledging the error and expressing dismay that AI-generated content had slipped into the filing. But the apology, while appropriate, could not erase the broader implications. The Court had just witnessed India’s first recorded instance of AI-generated fake case law being placed before a judicial authority.

The temptation now is to treat this as an isolated blunder—a lapse in diligence rather than a systemic threat. But doing so would be a mistake. This event illuminates the widening gap between the rapid adoption of AI tools and the legal profession’s preparedness to govern and use them responsibly. It also exposes how easily sophisticated technology can be weaponised, intentionally or otherwise, in environments that rely heavily on trust.

To appreciate the gravity of the moment, one must understand how generative AI models operate. They do not “look up” case law the way a legal database does. They predict text based on patterns. When prompted to produce judicial precedents, a general-purpose AI tool may fabricate citations that resemble real ones—using plausible judge names, legal principles, and formatting.

Without verification, such invented cases can look indistinguishable from authentic ones. This is not malicious intent on the part of the technology; it is a limitation of design. But when such tools are used in legal practice without human oversight, the risk becomes profound.

Lawyers have always relied on research assistants, interns, and junior colleagues. The shift to AI-driven tools is not entirely different in spirit—except, of course, for the scale and speed at which misinformation can now be produced. One faulty intern can generate a flawed brief. One unregulated AI tool can generate hundreds of fabricated authorities in seconds. And while a human assistant may hesitate before inventing case law, an AI model feels no such discomfort. Its only objective is to produce text that fits a pattern, not to ensure legal accuracy.

This is precisely why the incident raises serious concerns under multiple intersecting areas of Indian law. Under the Indian Penal Code, the knowing or reckless submission of fabricated materials could implicate offences such as cheating (Section 420), forgery (Section 468), and using forged documents as genuine (Section 471). Even if a lawyer did not intentionally fabricate cases, the question of negligence or recklessness remains central.

Professional ethics demand due diligence, and the Bar Council of India’s conduct rules are clear: advocates must not mislead the court and must verify authorities before presenting them. The Supreme Court’s strong reaction indicates that the judiciary views the misuse of AI tools as a breach of this professional duty.

The incident also raises questions about the Digital Personal Data Protection Act (DPDP Act) if the AI system used any litigant’s personal data improperly. While DPDP implications are not central to the fabricated-precedent scenario, the event highlights a broader issue: lawyers increasingly use AI tools without understanding where the data goes, how it is processed, or whether it is stored securely. Even legitimate legal research tools must demonstrate compliance with India’s data protection framework. The unregulated use of consumer-grade generative AI systems adds another layer of risk.

What, then, should the legal community take away from this moment? The first lesson is painfully straightforward: AI is not a research database. Lawyers cannot outsource their judgment. Tools that generate text cannot replace tools that retrieve verified documents. In legitimate legal research, every citation can be traced to an official source; every judgment has a provenance; every paragraph can be located in a published report. The incident before the Supreme Court demonstrates what happens when this distinction collapses.

The second lesson is that judicial systems globally are already grappling with similar problems. In 2023, a case in the United States drew international attention when lawyers submitted a brief containing multiple fictitious citations generated by an AI chatbot. The judge in that matter sanctioned the lawyers, emphasising that “there is nothing inherently improper about using AI for assistance, but existing rules require attorneys to ensure the accuracy of their filings.” The Indian judiciary now faces its own version of this challenge, and the parallels are instructive. Both incidents reveal a common pattern: technological enthusiasm outpacing professional caution.

Yet there is also a counterargument worth considering. One might say that the problem is not AI itself but the misuse of AI. After all, every tool in history—printing presses, typewriters, computers—has been misused. Should we attribute blame to the technology, or to those who wield it recklessly? There is merit in this view, particularly because AI is also transforming law in positive ways. It can analyse large datasets quickly, summarise complex judgments, and assist in document review. Efficiency gains are real. But the counterargument falters at the point where systemic incentives collide with technological capability.

AI tools work at a speed and volume that fundamentally change the consequences of negligence. A single moment of carelessness can now produce hundreds of fabricated authorities. The scale of potential damage is no longer analogous to earlier tools.

Moreover, the very nature of AI hallucinations makes them harder to detect. A poorly drafted legal argument is easy to spot. A cleverly invented judgment that sounds realistic is not. When such fabricated content is fed into judicial processes that depend on authenticity, the harm extends beyond individual disputes. It erodes trust in the system, burdens courts with additional verification responsibilities, and incentivizes bad actors who may seek to exploit the technology intentionally.

To prevent such outcomes, both systemic and cultural changes are necessary.

First, the legal profession must develop clear best practices for the use of AI tools. These guidelines should require verification of all AI-generated content against authoritative legal databases. They should emphasize transparency: if AI assistance is used, the lawyer should disclose the tool and confirm that all legal authorities have been independently checked.

Second, courts should consider technological solutions of their own. Automated citation-checking tools, already in use in some jurisdictions, could help identify nonexistent judgments before they reach a judge’s desk. Training programmes for judges and court staff on AI-generated misinformation would further strengthen institutional resilience.

Third, law firms and corporate legal teams should implement internal protocols. Just as quality-control reviews exist for contract drafting, similar processes must govern briefs and petitions generated with AI assistance. Research teams should receive training not only in how to use AI but in how to not use it. The distinction is essential.

And finally, law schools must adapt. Future lawyers will enter a profession transformed by generative AI. Traditional research training remains essential, but curricula must also address digital literacy, AI ethics, and verification standards. Students must learn that technological convenience is not a substitute for professional responsibility.

Some critics argue that fears surrounding AI in the legal profession are exaggerated. They point out that courts already require citations to be verified and that blatant fabrications will always be caught before decisions are made. But this argument underestimates the sheer complexity of modern litigation. Judges handle massive caseloads.

Litigants rely on courts to sift through volumes of information. If courts must now spend time verifying each citation because they cannot trust lawyers’ submissions, the burden becomes unsustainable. It is not merely about catching falsehoods but preventing them from entering the system in the first place.

Others suggest that AI hallucinations will diminish as models improve. While advances in legal-specific AI systems may reduce errors, the risk will never fully disappear.

Even the most advanced AI cannot replicate the foundational requirement of legal practice: reasoning grounded in authentic, binding authority. Law is not a domain where “close enough” is acceptable. Precision is non-negotiable. And as long as general-purpose AI tools are accessible to the public, the temptation to use them for legal drafting will persist.

At the heart of this editorial lies a simple truth: technology is not the enemy. The real crisis emerges when legal systems embrace new tools without building the ethical, procedural, and technical guardrails required to prevent misuse. India’s first known case of AI-generated fake law reaching the Supreme Court is not a cause for panic, but it is a call to action. The incident should catalyse a broader movement to ensure that as AI reshapes legal practice, it does not undermine the very values the justice system is built on—integrity, truth, and trust.

What happened on December 9 was a mistake, but it was also a mirror. It showed us the risks of convenience without caution, acceleration without accountability. It is now up to lawyers, judges, lawmakers, and technologists to decide whether this moment becomes a footnote or a turning point. If we respond with seriousness and foresight, India can become a leader in crafting responsible AI norms for the legal industry. If we ignore it, the next incident may not be so easily contained.

As we move forward, we might recall Justice Oliver Wendell Holmes Jr., who wrote over a century ago, “The law is the witness and external deposit of our moral life.” If AI is to become a part of that moral life, it must be held to standards that preserve—rather than degrade—the credibility of our institutions. The Indian legal system now faces a defining test: to integrate powerful new technologies while maintaining its foundational commitment to truth.

This incident should not overshadow the immense opportunities AI presents for justice—faster research, better access to information, more equitable support for under-resourced litigants. But opportunity does not erase responsibility. The path ahead requires vigilance, wisdom, and humility. It requires acknowledging that the tools we build can both strengthen and weaken the systems we rely on.

The Supreme Court has sounded the alarm. The question now is whether the legal community will answer it with the seriousness it deserves. If AI is to serve justice rather than distort it, then transparency, verification, and ethical practice must become the new pillars of digital-era advocacy. The future of law is undeniably technological. The challenge is to ensure it remains truthful.