Are India’s Law Schools Falling Behind the AI Curve?

When surveys warn that legal education must change due to AI, the message often sounds abstract, future-facing, speculative, and even alarmist. But inside Indian law firms, the shift is real.

AI now sits at the core of how contracts are executed, compliance is tracked, deadlines are monitored, and risk is reported. While legal tech startups are quietly giving AI a paralegal role, law schools are struggling to keep pace with the shift.

A LawNews report has highlighted how AI startups are forcing universities to confront uncomfortable questions about ethics, accountability, and assessment. A separate Artificial Lawyer survey found near-consensus among legal professionals that AI literacy and oversight must become foundational skills. In India, those pressures collide with a legal education system still anchored in doctrinal teaching and manual workflows.

The result is a widening gap between what law students learn and what modern legal practice demands, particularly in data accountability, audit trails, and transparency in AI-assisted legal work.

From Documents to Systems

For decades, Indian legal training has revolved around mastering statutes, drafting clauses, and interpreting case law. That foundation remains important, but it does not reflect reality.

“Traditionally, contracts are treated as paperwork,” says Aditya Pandranki, Founder and CEO of contact management startup Doqfy. Once signed, contracts are archived and revisited only when something goes wrong. “That mindset doesn’t work anymore,” he says, pointing to the rise of AI-enabled contract and compliance platforms.

Law schools traditionally don’t train students to think in terms of contract lifecycles. “Law graduates are trained to draft contracts, but not to manage them end-to-end,” Pandranki explains. AI platforms force lawyers to engage with workflows, timelines, and compliance logic step by step, turning contracts into living systems rather than static documents.

That disconnect is even more pronounced inside law firms adopting practice management and workflow software.

“Law schools do a great job teaching the ‘what’, what the law is, what cases say,” says Hitesh Jirawla, Founder and CEO of AI-driven litigation analytics company Cubictree. “But professional legal life is about the ‘how’, how work gets done fast, accurately, and at scale, using dashboards, workflows, and automation.”

Jirawla says new graduates have strong analytical reasoning but little exposure to the tools firms rely on. “Firms are using software to bring operational efficiency, but new entrants lack hands-on experience with these systems,” he observes. 

Legal research has shifted to AI-powered platforms like SCC Online and CaseMine. Documentation has moved to contract lifecycle management tools. Litigation increasingly involves e-filing portals and virtual hearings. Yet most law schools still teach drafting as if the final output is a Word document.

AI has Raised the Bar

Contrary to fears of mass job loss, AI has actually raised expectations for entry-level lawyers.

“Earlier, juniors did manual research, basic drafts, and document checks,” Jirawla explains. “Today, AI handles much of that. Firms now want strategic thinkers who can interpret outputs and add judgment from day one.” 

He describes a shift away from the “paper-pusher” model. If a junior lawyer cannot navigate legal tech platforms or automate routine tasks, they are at a disadvantage. What firms value now are skills machines cannot replicate: ethical judgment, contextual reasoning, and the ability to work with clients.

“Adaptability is the new job security,” Jirawla notes. 

When AI Goes Wrong

The risks of inadequate AI literacy are no longer hypothetical. Legal professionals often rely on AI tools without understanding their limitations, assumptions, or errors.

Earlier this year, the Bombay High Court imposed a penalty of ₹50,000 on a litigant for submitting a ‘non-existing’ judgment generated through AI. Last year, a petition before the Delhi High Court was withdrawn after it emerged that several cited judgments did not exist and appeared to have been generated by an AI tool. 

“This isn’t about laziness,” says Jameela Sahiba, Associate Director at tech policy think-tank The Dialogue. “It’s about misplaced trust. Dashboards can create a false sense of certainty.” 

If students are never trained to question thresholds, models, or training data, she warns, they may assume that “the system didn’t flag it, so we’re safe.”

Even major AI developers are encountering legal quagmires. In a 2025 copyright dispute involving Anthropic, lawyers from Latham & Watkins acknowledged that they used Anthropic’s chatbot Claude to draft expert citations, resulting in incorrect titles and authors.

The Governance Blind Spot

Nowhere is the education gap more dangerous than in data governance.

“One of the biggest risks today is misalignment with India’s Digital Personal Data Protection Act,” says Ibrahim H Khatri, Founder and CEO of enterprise data privacy solutions provider privEzi.

The Digital Personal Data Protection (DPDP) Act, 2023, now places legal obligations on data custodians to ensure transparency, accountability, and secure processing. But existing legal education rarely covers audit trails, model explainability, and governance structures—essential elements in an AI-enabled practice.

As law firms centralise sensitive contract and compliance data on AI platforms, Khatri points to risks around purpose limitation, access controls, and unclear data fiduciary–processor boundaries. “Without explainable logic behind AI-generated alerts or risk flags, firms may struggle to meet accountability and grievance redressal obligations,” he says.

Crucially, he argues that law schools are not preparing students for this reality. “The DPDP Act makes demonstrable accountability, who accessed data, for what purpose, and under whose authority, a legal requirement,” Khatri says. “But most law schools still treat audit trails and explainability as technical issues rather than legal ones.” 

Human Judgement Remains Crucial

Despite the rise of automation, experts stress that AI does not replace lawyers; it redefines their responsibility.

“AI is a math machine,” Jirawla says. “It can find patterns, but it doesn’t understand why something matters to a client.” 

Human skills, ethical reasoning, accountability, and contextual awareness become more important as AI handles routine tasks. Lawyers must detect bias, challenge flawed outputs, and ensure systems operate within ethical guardrails.

Sahiba echoes this point, arguing that human judgement hasn’t disappeared; it has simply moved up a level. “AI doesn’t remove judgement; it changes where judgement sits,” she says.

Why Law Schools are Falling Behind

Despite these shifts, most Indian law schools still treat legal tech as an elective. While the Bar Council of India emphasises clinical education, there is no mandate to teach AI governance, system accountability, or compliance workflows.

Pandranki believes this must change. “Manual processes are becoming unsustainable,” he says. “Technology proficiency is becoming a non-negotiable survival skill.” 

Jirawla is more blunt: until legal tech is treated as infrastructure rather than innovation, the disconnect will persist.

Experts suggest a structural rethink, not cosmetic reform.

Sahiba proposes replacing at least one doctrinal course with a systems-and-workflows studio, where students design end-to-end compliance processes using AI tools. Assessment would focus on explainability, fairness, and accountability rather than rote answers.

Khatri argues that governance concepts, audit trails, data minimisation, and transparency must be embedded across subjects, not confined to privacy law electives. “If lawyers are responsible for AI-driven decisions in practice, they must be trained for that responsibility,” he says.

AI startups are already shaping Indian legal practice. And now, law schools have two options: adapt or risk irrelevance.