AI and its Regulation in India, Limitations and Gaps

Context: The governance and regulation of Artificial Intelligence (AI) have garnered significant global attention over the past year.

What is Artificial Intelligence (AI)?

• Artificial Intelligence (AI) is the branch of computer science concerned with developing machines that can complete tasks that typically require human intelligence. 
• The goals of artificial intelligence include computer-enhanced learning, reasoning, and perception.
• Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the simplest to those that are even more complex.

India’s Approach to AI Regulation

India has opted for a soft-regulatory, mission-driven model rather than a hard legislative or enforcement-based approach. Unlike some countries that have enacted AI-specific laws or national AI strategies with implementation roadmaps, India’s approach is flexible, adaptive, and evolving.

Key Elements of India’s AI Approach

• No dedicated AI regulation or law: India lacks an AI-specific legal framework.
• No formally endorsed National AI Strategy: NITI Aayog’s 2018 strategy document remains only a suggestive blueprint.
• Mission-mode focus through IndiaAI: Emphasis is on fostering innovation and the AI ecosystem through the IndiaAI mission, backed by 7 pillars like compute infrastructure, datasets, research, and skilling.
• Advisory frameworks under development: Expert groups are working on governance frameworks, but adoption remains uncertain.
• Leverage of existing digital laws: India may build AI regulation on the backbone of the Digital Personal Data Protection (DPDP) Act, 2023.

Merits of India’s Current Approach

Flexibility & Adaptability

• No rigid law enables India to respond to rapidly evolving technologies and global AI geopolitics.
• Allows policy experimentation and space for stakeholder consultations.

Focus on Ecosystem Development

• India is prioritising building AI capacity, infrastructure, skills, datasets, and public-private partnerships.
• Early-stage adoption requires enabling tools and not overregulation.

Learning from Global Models

• India can observe regulatory outcomes in other countries (like the EU’s AI Act) before acting.
• Provides time to create indigenous frameworks sensitive to local socio-economic realities.

Limitations and Gaps in India’s AI Regulation

• Lack of Coherent Vision and Roadmap: Absence of an official AI policy means unclear vision, no fixed milestones, and weak accountability.
• No Legal Guardrails: Implementation of AI systems remains largely voluntary and opaque.
  • This creates the risk of privacy breaches, biased algorithms, and a lack of redressal mechanisms.
• Public Unawareness and Lack of Debate: Citizens are largely unaware of where and how AI is being used — in banking, health, education, or welfare delivery.
  • Civic discourse on ethics, labour disruption, misinformation, and model safety is limited.
• Risks of Leadership Dependency: Without institutionalised regulation, AI adoption risks becoming personality- or ministry-driven, lacking continuity.
• Reactive, Not Proactive: India has responded after harm, e.g., AI-generated content causing social unrest, instead of anticipating and preparing.

Global Models India Can Learn From

Way Forward for India

• Draft and Publish a National AI Policy: Should outline:
  • Vision for AI in India
  • Priority sectors (health, agriculture, education, governance)
  • Capacity-building strategy
  • Ethical and legal frameworks
  • Public awareness, participation, and grievance redress
• Pilot Regulatory Mechanisms: Use regulatory sandboxes in key sectors (e.g., Fintech, HealthTech) to test AI systems in real-world conditions.
• Strengthen Citizen-Centric Safeguards: Mandate algorithmic transparency, impact assessments, and opt-out mechanisms in public services.
• Integrate with DPDP Act, 2023: Use India’s centralised data protection law as a foundation for cross-sector AI governance.
• Create an Independent AI Oversight Body: Like a “National AI Commission” to audit high-risk models, set standards, and ensure responsible AI deployment.

Conclusion

India’s current AI approach is innovation-centric and adaptive, but it lacks regulatory clarity and citizen protection mechanisms. As AI rapidly becomes embedded in socio-economic systems, India needs a clear, inclusive, and enforceable framework. A balanced strategy — combining AI policy, legal guardrails, and ethical principles — is essential to ensure AI in India is not only cutting-edge but also safe, inclusive, and aligned with constitutional values.

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