Short answer: yes as an assistant to human drafters, no as the author. And "watertight" laws wouldn't fix most of what people mean by lawlessness.
Where AI would help
- Consistency checking. Flagging contradictions with existing statutes, undefined terms, cross-reference errors, and conflicts between Central and State law. India has a huge, layered body of legislation, so this is tedious work that software handles well.
- Spotting obsolete or overlapping laws and drafting repeals or consolidations.
- Stress-testing. Having a model act as an adversary and look for loopholes or ambiguous clauses before a Bill is introduced.
- Plain-language and multilingual versions of the text.
- Commentators have already pointed to these uses, such as helping identify outdated laws and streamline the legislative process.
Where it fails
- No law is watertight. Language is ambiguous, and facts and technology change. Courts exist partly to fill gaps, and over-precise drafting often creates new loopholes.
- Drafting involves value choices, such as who bears the burden of proof, how to trade privacy against security, and what penalty fits. Those need democratic accountability, which a model can't supply.
- Opacity and bias. Critics note that AI models can be so complex that it's hard to understand how they reach decisions, which matters for something that becomes binding law.
- Hallucination. Models can invent plausible-sounding citations or misstate what an existing provision says. Every output needs expert verification.
- Training data is skewed toward whatever is online and may miss local or customary context.
The bigger issue is the diagnosis. India's problem is less badly drafted law than weak implementation and enforcement. The National Judicial Data Grid showed roughly 4.92 crore pending cases across district and high courts as of 31 May 2026, with about 92,000 more in the Supreme Court. Analyses of that backlog point to causes like multiple appeals, frequent adjournments, vague laws, weak compliance and poor case management. Vague drafting is one cause among several. Judge vacancies, police capacity, procedure and compliance culture matter at least as much. A perfectly drafted statute still stalls in a court that takes a decade to hear it.
A sensible model for India
- Use AI for internal vetting, consistency checks and adversarial review, with humans, Parliament and the Legislative Department owning every word.
- Require disclosure of when and how AI was used in a draft, and publish the prompts or checks where feasible.
- Keep the public consultation step human and real.
- Spend equal effort on capacity: courts, prosecution, and digitised case management. AI-based case management is already part of the eCourts Phase III push.
Also worth noting, MeitY has said it will begin stakeholder discussions and drafting of AI regulation, so there's an open question of who governs AI used inside lawmaking itself.
This is a debated policy area, and reasonable people weigh the efficiency gains against accountability concerns differently. If you want, I can sketch what an AI-assisted drafting pipeline with human review checkpoints could look like, which might also suit a student capstone.
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