AI In Indian Law: Innovation On Trial

The integration of artificial intelligence into legal systems is no longer a speculative future; it is a present reality. Globally, AI tools are being deployed to assist in legal research, contract analysis and even judicial decision-making.

In India, this trend is gaining momentum, albeit with a degree of caution. As someone who has worked across legal, policy, and technology domains, I believe India must approach this transformation with both ambition and restraint.

India’s judiciary has taken early steps toward AI adoption. The Supreme Court's initiatives, SUPACE (Supreme Court Portal for Assistance in Court Efficiency) and SUVAS (Supreme Court Vidhik Anuvaad Software), are designed to assist judges with legal research and translation, not to replace judicial discretion. As former Chief Justice SA Bobde emphasised during SUPACE's launch, the system is intended to enhance efficiency, not to make decisions.

Law firms, too, are embracing AI. Shardul Amarchand Mangaldas has implemented Harvey AI, a generative platform tailored for legal professionals. Cyril Amarchand Mangaldas has adopted a multi-platform strategy, combining Harvey AI, Copilot, and ChatGPT Plus to streamline operations. These tools are not merely improving productivity; they are reshaping the structure of legal service delivery.

Despite these advancements, the risks are significant. A recent study by Stanford HAI found that legal AI models hallucinate, generate false or misleading information, at least once in every six queries. In a legal context, such errors are not trivial. A hallucinated precedent or misinterpreted statute can lead to flawed legal advice or judicial outcomes.

In India, where legal decisions often have profound social and economic consequences, the margin for error is minimal. The judiciary’s cautious stance, explicitly rejecting AI for decision-making, reflects an awareness of these risks. Yet, as AI tools become more integrated into legal workflows, the potential for overreliance and misuse grows.

India currently lacks a comprehensive regulatory framework for AI in legal practice. The Bar Council of India and the Ministry of Law and Justice have yet to issue guidelines on the use of AI-generated legal content, disclosure obligations, or audit trails. This regulatory vacuum creates both opportunity and risk. Early adopters are effectively setting de facto standards, which may or may not align with broader ethical and professional norms.

Moreover, AI systems trained on historical legal data risk perpetuating existing biases, whether related to caste, gender, or class. Without rigorous oversight, these tools could reinforce systemic inequities under the guise of efficiency.

The rise of AI is also reshaping the economics of legal practice. When AI can complete a 10-hour task in two, traditional billing models become unsustainable. This shift is creating a bifurcated market: senior lawyers who leverage AI for strategic tasks will command premium fees, while routine legal work is increasingly automated.

This transformation demands a redefinition of legal expertise. Rather than acquiring entirely new skills, legal professionals must reposition their existing capabilities, such as negotiation, judgment, and ethical reasoning, within an AI-augmented value chain.

To harness AI's potential while mitigating its risks, India must adopt a structured approach:

• Regulatory Clarity: The Bar Council and the Ministry of Law should issue interim guidelines on AI use in legal practice, including disclosure norms and audit requirements.

• Human Oversight: AI-generated outputs must be subject to human review, particularly in litigation and advisory contexts.

• Domain-Specific Training: AI models should be trained on verified Indian legal data to ensure contextual accuracy.

• AI Literacy: Legal education must incorporate AI literacy to prepare future professionals for a hybrid legal environment.