SRM University (SRMUH) 
Introduction
Something significant is happening in law right now.
A technology that barely existed in legal practice five years ago is now writing contracts, predicting case outcomes, assisting in legal research, and making decisions that affect people’s jobs, finances, and freedoms. And the legal frameworks governing this technology are being written right now, often by people who do not fully understand it.
The gap between the pace of AI development and legal regulation is one of the most consequential challenges facing legal systems globally. And it is creating one of the most interesting and rapidly expanding areas of legal practice available to the next generation of lawyers.
For students looking at the best law universities in Delhi, AI regulation is not a distant or abstract topic. It is a career direction that is opening up in real time. The lawyers who understand both the technology and the law will be among the most sought-after legal professionals of the next decade.
Why Does AI Need Regulation?
AI systems are making consequential decisions across virtually every domain of life.
Here is where AI decision-making is already operating:
- Credit and financial services: Algorithms decide who gets loans, at what interest rates, and which transactions are flagged as fraudulent.
- Employment: AI systems screen job applications, conduct initial interviews, and in some cases make hiring recommendations.
- Healthcare: AI tools diagnose medical conditions, recommend treatments, and triage patients in emergency settings.
- Criminal justice: Predictive policing tools, bail recommendation systems, and recidivism risk scores influence how the justice system treats individuals.
- Content moderation: Algorithms decide what speech is allowed on platforms used by billions of people.
- Insurance: AI systems assess risk and set premiums across health, life, and property insurance.
- Education: Automated proctoring systems monitor students. AI grading tools assess work; algorithmic admissions systems screen applicants.
Each of these applications raises significant legal questions. Who is liable when an AI system makes a harmful decision? What rights does an individual have when an algorithm determines their access to credit, employment, or justice? How should AI-generated evidence be treated in court? What obligations do companies have to disclose when AI is making decisions about people?
These questions are not hypothetical. They are being litigated across multiple jurisdictions right now. And the legal frameworks to answer them are still being built.
What AI Regulation Looks Like Globally
Several major regulatory frameworks for AI are now in various stages of development and implementation.
European Union AI Act
The EU AI Act is the world’s most comprehensive AI regulation. Here is what it establishes:
- Risk-based classification: AI systems are classified as unacceptable, high, limited, or minimal risk. Different rules apply to each category.
- Unacceptable-risk AI is prohibited: Social scoring systems, real-time biometric surveillance in public spaces, and AI that manipulates behaviour are banned.
- High-risk AI faces strict requirements: Systems used in critical infrastructure, education, employment, credit, justice, and healthcare must meet transparency, accuracy, and human oversight standards.
- Compliance obligations: Companies deploying high-risk AI must conduct conformity assessments, maintain technical documentation, and register systems in an EU database.
- Penalties for non-compliance: Fines of up to 35 million euros or 7 percent of global annual turnover, whichever is higher.
- Extraterritorial reach: The regulation applies to any company that deploys AI and affects EU citizens, regardless of where the company is based.
The EU AI Act has direct implications for Indian companies with European operations or customers. Indian lawyers advising multinational clients need to understand it.
United States Approach
The US has taken a more fragmented, sector-specific approach:
- Executive Order on AI (2023): Established safety testing requirements for high-capability AI systems and directed federal agencies to develop sector-specific AI rules.
- NIST AI Risk Management Framework: Voluntary guidelines for responsible AI development adopted across many sectors.
- Sector-specific regulation: Financial regulators, healthcare regulators, and employment law agencies are each developing AI-specific guidance.
- State-level legislation: Several US states, including California and Illinois, have passed AI-specific laws covering facial recognition, employment AI, and automated decision-making.
India’s Approach
India is developing its regulatory approach to AI through several instruments:
- Digital India Act: The proposed replacement for the IT Act includes provisions relevant to AI governance.
- MEITY AI guidelines: The Ministry of Electronics and Information Technology has issued advisories and is developing a more comprehensive AI regulatory framework.
- Sector-specific rules: RBI, SEBI, IRDAI, and healthcare regulators are each developing AI-specific guidance for their sectors.
- India AI Mission: The government’s major AI investment programme includes governance components alongside research and infrastructure investment.
India’s regulatory approach is still developing, which means the frameworks being built now will reflect the work of legal professionals who understand both AI and law. This is a genuine opportunity for law graduates entering the field.
Also Read: Top LLM University in Delhi
What Legal Questions Does AI Create?
The legal issues raised by AI span almost every established area of law.
Liability
- When an AI medical diagnostic tool misidentifies a condition and harms a liable patient? The developer? Is the hospital deploying the tool? The doctor who relied on it?
- When an autonomous vehicle causes an accident, how is fault determined and allocated?
- When AI-generated content defames someone, who bears legal responsibility?
Intellectual Property
- Does AI-generated creative work qualify for copyright protection? If so, who owns it?
- Can AI systems infringe copyright by training on protected works without permission?
- Are AI-assisted inventions patentable? Who is the inventor?
Data Protection and Privacy
- What data can be used to train AI systems without violating privacy rights?
- What rights do individuals have to know when an AI is making decisions about them?
- How should data protection law apply to AI systems that make inferences beyond what was explicitly provided?
Employment Law
- What obligations do employers have to disclose when AI is being used in hiring or performance management?
- Does algorithmic bias in employment AI violate discrimination law?
- What rights do workers have when AI systems monitor their productivity?
Consumer Protection
- What information must companies disclose when AI is making product recommendations or pricing decisions?
- How should consumer protection law apply to AI systems that cause harm through design defects?
Evidence and Procedure
- How should courts treat AI-generated evidence? What standards govern its admissibility?
- When AI legal research tools produce incorrect citations, what are the professional responsibility implications for the lawyer who relied on them?
- How should expert testimony about AI systems work in litigation?
Each of these areas is generating active legal work. Each requires lawyers who can engage with technical realities alongside legal doctrine.
What New Legal Roles Is AI Regulation Creating?
The emergence of AI regulation is directly creating new professional roles for lawyers.
Here is where demand is growing:
- AI compliance counsel: Companies deploying AI systems need lawyers who can assess regulatory requirements, build compliance programmes, and advise on risk mitigation.
- Technology transactions lawyers: Contracts for AI systems, data licensing agreements, and technology partnerships require lawyers who understand what they entail.
- Regulatory affairs specialists: As government agencies develop AI rules, both regulators and regulated entities need lawyers who can navigate the policy and compliance dimensions.
- Litigation specialists: AI-related disputes over liability, IP, discrimination, and privacy are generating cases that require lawyers with technical fluency.
- Policy advocates: Civil society organisations, technology companies, and governments all need lawyers who can contribute to the policy debates shaping AI regulation.
- Ethics and governance advisors: Companies building AI systems need legal and ethical guidance on responsible development practices.
- Judicial education: Courts need training on AI issues to adjudicate AI-related cases competently. Legal professionals contribute to this.
- International regulatory harmonisation: As different jurisdictions develop different AI rules, cross-border regulatory coordination requires lawyers with international regulatory expertise.
What Skills Do AI Lawyers Need?
Practising effectively in AI regulation requires capabilities that go beyond standard legal training.
Key skills include:
- Technical literacy: Lawyers do not need to write code. They do need to understand how machine learning systems work, what training data is, how models make decisions, and where they fail. This literacy is developed through deliberate learning.
- Regulatory analysis: AI regulation is developing across multiple jurisdictions simultaneously. Tracking and analysing regulatory developments is a core skill.
- Risk assessment: Helping clients understand and manage AI-related legal risk requires assessing technical systems for potential legal exposure.
- Contract drafting for AI: AI procurement contracts, data licensing agreements, and liability allocation provisions in technology contracts require specific drafting expertise.
- Cross-disciplinary collaboration: AI lawyers regularly work alongside technologists, data scientists, ethicists, and policy experts. The ability to collaborate effectively across these disciplines is essential.
- Staying current: AI and its regulation are both moving extremely fast. Continuous learning is not optional in this practice area.
How Does an LLB Prepare Students for This Field?
A strong law degree builds the foundation. Here is what matters most for AI law specifically:
- Constitutional and fundamental rights law: Many debates over AI regulation turn on constitutional questions about due process, equality, and freedom from surveillance.
- Tort and liability law: The foundational frameworks for determining who bears responsibility for AI-caused harm.
- Intellectual property law: Copyright, patent, and trade secret law as applied to AI development and output.
- Data protection law: India’s Digital Personal Data Protection Act and international frameworks, including GDPR.
- Administrative and regulatory law: How regulatory agencies operate and how their rules can be challenged.
- Technology law electives: Courses specifically engaging with legal issues in technology, AI, and digital platforms.
- Moot court experience: Arguing cases with technical dimensions develops the ability to make complex arguments clearly.
- Research skills: The literature on AI law is growing rapidly. Strong research capability is essential for staying current.
Why Should You Consider SRM University Delhi-NCR, Sonepat?
Choosing the right law university in Delhi shapes both the quality of legal education and the professional opportunities available after graduation.
SRM University Delhi-NCR, Sonepat (SRMUH) approaches legal education with a clear focus on preparing students for the demands of contemporary legal practice. Here is what the programme offers:
- A curriculum that covers technology law, data protection, intellectual property, and constitutional rights as substantive areas of study.
- Moot court experience that develops the practical argumentation and advocacy skills that complex legal practice requires.
- Research opportunities that allow students to engage with emerging legal questions, including AI regulation, at a genuine depth.
- Faculty who bring current expertise and industry awareness into the learning environment.
- Internship and placement support that connects students to the Delhi NCR legal market, one of India’s most significant and diverse legal ecosystems.
The university’s location in Delhi NCR is particularly relevant for students interested in AI regulation. The capital region hosts the Ministry of Electronics and Information Technology, major technology company offices, leading law firms handling technology transactions and disputes, and policy institutions shaping India’s regulatory approach to AI. Being embedded in that ecosystem during a law degree provides exposure and networking opportunities not available elsewhere.
Among the best law universities in Delhi, SRMUH offers a programme genuinely oriented toward the future of legal practice, not just the past.
What Does Choosing This Direction Mean?
AI regulation is being written right now.
The frameworks governing how AI systems affect employment, healthcare, justice, education, and finance for the next generation are being debated in legislatures, regulatory agencies, and courts worldwide. The lawyers contributing to those debates and helping clients navigate the resulting rules are doing work that will shape how this technology develops and how its consequences are managed.
That is genuinely consequential work. It sits at the intersection of law, technology, ethics, and power in ways that few other legal practice areas can match.
The lawyers best positioned to contribute are those who develop genuine technical literacy alongside strong legal foundations. Who can engage with a machine learning engineer, a data regulator, and a judge on the same day, communicating effectively with each? Who understands both what AI systems can do and what legal frameworks are designed to protect?
For students at the best law universities in Delhi who want their legal careers to engage with the most important questions of the next decade, AI regulation is a direction that is opening up in real time.
The legal frameworks for AI are being built. The lawyers who help build them and navigate them will define a generation of practice.
