“This article has been authored by Shradha N. Mathur, a legal operations professional with expertise in immigration law and AI policy. She has worked extensively on U.S. visa petitions and previously gained practical experience as an associate in the Founder’s Office at a full-stack AI company in India.”
Artificial intelligence (AI) is no longer a distant concept in Indian law. From courtrooms to boardrooms and law offices, algorithms are helping judges manage massive backlogs, enabling directors to make data‑driven decisions and assisting lawyers with research and drafting. This rapid adoption raises practical and ethical questions: who is liable when an automated decision goes wrong? How do we protect individual rights when machines process personal data? What safeguards should exist so that efficiency does not eclipse justice?
This analysis surveys three areas where AI is reshaping Indian law – the courts, corporate governance and legal practice – and considers the regulatory gaps and challenges that accompany this transformation. The goal is not to vilify technology but to ask how it can be deployed responsibly.
AI in the courts: promise versus policy
e‑Courts and AI tools
India’s judiciary, burdened by millions of pending cases, is turning to technology to speed up justice. Under the third phase of the e‑Courts Project, the Supreme Court and Ministry of Law and Justice are deploying AI to automate scheduling, predict case timelines, digitise documents and perform optical character recognition. Natural language processing engines provide judges quick access to relevant precedents and can translate judgments into regional languages. AI‑powered chatbots update litigants and guide them through procedures. The government has allocated more than ₹7,200 crore for this phase, with tens of crores earmarked for AI and blockchain initiatives in high courts.[1]
Two flagships highlight this push: SUVAS (Supreme Court Vidhik Anuvaad Software) and SUPACE (Supreme Court Portal for Assistance in Court Efficiency). SUVAS uses machine learning to translate judgments into nine languages[2]; SUPACE helps judges summarise facts, sift evidence and mine case law. These tools aim to reduce pendency and ease the burden on judges.[3]
The rights‑based critique
Technology alone cannot fix a justice system. A policy watch by The Hindu Centre notes that the Supreme Court has yet to publish clear guidelines on how AI should be used. Most official statements emphasise efficiency and cost savings, but little is said about fairness, transparency or the right of litigants to question machine‑generated outcomes. The report warns against a purely “managerial” approach that treats AI as a neutral tool and calls for a rights‑based framework that guards against bias and ensures explainability. Without such policies, translation tools like SUVAS may improve accessibility on paper but fail to make complex judgments understandable to ordinary citizens.[4] As courts adopt AI, clear rules on data quality, algorithmic bias and redress mechanisms will be essential.
AI in corporate governance
Data‑driven boardrooms
Indian companies are inviting AI into the boardroom. Algorithms parse mountains of data to predict market trends, detect fraud and flag compliance issues.[5] They also generate minutes and draft reports, allowing directors to focus on strategy. However, efficiency is only part of the story. An IndiaAI article emphasises that transparency and accountability are “non‑negotiable”.[6] In the realm of corporate governance, Indian law firms are also leveraging AI to streamline their work. For instance, SAM, a prominent law firm, has integrated Harvey AI across all their offices to enhance efficiency and client service.[7] Directors must understand how algorithms arrive at recommendations and should be ready to challenge them when outputs look suspicious. Governance frameworks need to clarify responsibility: if an AI tool makes a bad call, the liability still rests with human directors. Upskilling board members and bringing in AI expertise are part of this transition.[8]
SEBI’s approach and data privacy law
Regulators are beginning to codify these responsibilities. Amendments to the Securities and Exchange Board of India (Intermediaries) Regulations, 2008 state that firms deploying AI in financial services remain responsible for the accuracy and integrity of machine‑generated outputs. Even when algorithms come from third‑party vendors, the burden of investor protection, data privacy and compliance falls on the regulated entity. This responds to the “black box” problem – the opacity of machine‑learning models that can hide errors and biases. SEBI’s stance hints at a future where boards might require independent audits or “AI ethics committees” to oversee algorithmic decision‑making.
Alongside sector‑specific rules, India enacted the Digital Personal Data Protection Act (DPDPA) in 2023. The law gives individuals rights such as consent, access and correction, while requiring organisations to minimise data collection and secure it. Non‑compliance can attract fines of up to ₹250 crore and other penalties.[9] However, scholars have pointed out that the Act does not address AI directly – there are no provisions on automated decision‑making or algorithmic bias. A paper in the Defacto Law Journal argues for AI‑specific guidelines on transparency and accountability, especially to protect marginalised communities.[10] Without such rules, companies might comply with data consent requirements but still deploy biased or opaque algorithms.
AI in legal practice and litigation
Research, drafting and due diligence
AI is transforming how lawyers work. Natural language processing tools search millions of judgments in seconds. Instead of wading through volumes of case law, advocates can prepare motions and craft arguments quickly. Generative models turn contract drafting from weeks into hours. Document‑automation engines flag risky clauses and suggest compliant structures.[11] Due‑diligence algorithms scan thousands of pages at once. AI‑powered monitoring tools track regulatory updates to help clients stay compliant.
Predictive analytics and strategy
Beyond research and drafting, AI tools predict litigation outcomes and suggest whether to settle or proceed to trial. Real‑time transcription systems reduce documentation costs. These innovations promise more efficient services, but they come with caveats: over‑reliance on predictions may discourage valid claims, so guidelines are needed to ensure that analytics inform rather than dictate strategy and that data sources and model limitations are transparent.
Access to justice
AI is also being used to democratise legal information. Chatbots like LAWFYI answer common legal questions and guide citizens on how to proceed.[12] Tools such as SUVAS translate judgments into multiple languages. These applications help rural and underserved communities gain access to the law. Yet technology alone cannot resolve structural barriers. A rights‑based perspective reminds us that linguistic complexity, poor legal representation and social inequalities must also be addressed.
A fragmented regulatory landscape
India does not yet have a unified AI law. Instead, regulation is emerging through a patchwork of privacy legislation and sector‑specific rules. The DPDPA focuses on consent and data security but lacks provisions on algorithmic decision‑making. SEBI’s regulations address AI in financial services but not other industries. Corporate law continues to treat AI decisions as human decisions, leaving directors exposed to liability. Courts are experimenting with AI tools without comprehensive policies.
Globally, regulators are moving toward risk‑based frameworks. The Cloud Security Alliance notes that Asia‑Pacific countries are refining AI and privacy laws, with India’s DPDPA imposing strong consent requirements and significant penalties for non‑compliance. Businesses are encouraged to adopt agile governance models, incorporate privacy by design and invest in privacy‑enhancing technologies.[13] New standards like ISO/IEC 42001 and the EU’s AI Act propose tiered risk classifications and controls. These global developments could inform Indian reforms, especially as cross‑border data flows become more important.
Toward accountable and humane AI
For AI to serve justice, India needs a coherent regulatory and ethical framework. Several steps could help:
- Judicial guidelines: The Supreme Court should publish policies on data quality, transparency, explainability and redress for AI tools used in courts. A rights‑based framework can balance efficiency with fairness.[14]
- Boardroom accountability: Regulators should clarify that directors remain liable for AI‑assisted decisions. Independent audits and AI ethics committees can provide oversight, and training can build literacy.
- AI‑specific privacy rules: The DPDPA should be expanded to cover automated decision‑making and algorithmic bias, ensuring transparency and fairness.[15]
- Invest in literacy: Judges, lawyers, directors and citizens need education on AI capabilities and limitations. Understanding reduces both over‑reliance and unwarranted fear.[16]
Ultimately, AI is reshaping Indian law by accelerating court processes, informing corporate decisions, and enhancing legal services. It offers tools that can reduce case pendency, cut costs, and broaden access to information. Yet unchecked automation risks undermining fairness and privacy. Without clear policies on bias, explainability, and accountability, AI may deepen existing inequalities rather than solve them. The challenge is to embrace innovation without losing sight of justice. By developing rights-based guidelines, aligning privacy law with AI realities, and ensuring human oversight, India can harness AI to build a more efficient and equitable legal system. Future reforms should involve not just technocrats but also judges, lawyers, activists, technologists, and citizens, ensuring that AI tools reflect India’s diverse languages and social realities. Only then can technology assist rather than displace human judgment and maintain trust in the rule of law.
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[1]https://indiaai.gov.in/article/ai-in-judicial-processes-transforming-india-s-legal-system.
[2]https://www.pib.gov.in/PressReleasePage.aspx?PRID=2113224.
[3]https://www.frontiersin.org/journals/political-science/articles/10.3389/fpos.2025.1553705/full.
[4]https://www.thehinducentre.com/incoming/ai-and-the-indian-judiciary-the-need-for-a-rights-based-approach-html-version/article68917505.ece#:~:text=the%20instance%20of%20SUVAS%2C%20the,15.
[5]https://indiaai.gov.in/article/how-ai-is-disrupting-corporate-boardrooms.
[6]https://indiaai.gov.in/article/how-ai-is-disrupting-corporate-boardrooms.
[7]https://www.barandbench.com/news/corporate/shardul-amarchand-mangaldas-announces-partnership-with-harvey-ai.
[8]https://indiaai.gov.in/article/how-ai-is-disrupting-corporate-boardrooms.
[9]https://secureframe.com/blog/digital-personal-data-protection-act-dpdpa.
[10]https://defactolawjournal.org/papers/why-we-need-data-protection-laws-for-ai-in-india/#:~:text=approach%20that%20balances%20innovation%20with,leader%20in%20ethical%20AI%20deployment.
[11]https://americanbazaaronline.com/2025/03/11/the-100-billion-disruption-how-ai-is-reshaping-legal-tech-460549/#:~:text=Contract%20drafting%20is%20experiencing%20a,jurisdictional%20compliance%20and%20risk%20avoidance.
[12]https://indiaai.gov.in/article/india-s-ai-driven-legal-future-opportunities-and-emerging-trends-in-2025.
[13]https://cloudsecurityalliance.org/blog/2025/04/22/ai-and-privacy-2024-to-2025-embracing-the-future-of-global-legal-developments.
[14]https://www.thehinducentre.com/incoming/ai-and-the-indian-judiciary-the-need-for-a-rights-based-approach-html-version/article68917505.ece#:~:text=This%20Policy%20Watch%20will%20examine,7%5D%2025%20Return.
[15]https://defactolawjournal.org/papers/why-we-need-data-protection-laws-for-ai-in-india/#:~:text=approach%20that%20balances%20innovation%20with,leader%20in%20ethical%20AI%20deployment.
[16]https://indiaai.gov.in/article/how-ai-is-disrupting-corporate-boardrooms.
