AI Governance in India: Policy Gaps and Way Forward
Why in the news
As nations race to regulate AI, India still relies on soft, non-binding measures. The analysis argued for an official AI policy and public debate on ethics.
Key facts
- Binding AI rules exist in China, EU, Canada, South Korea, Peru and the U.S. (where Trump revoked Biden’s AI order); drafts in UK, Japan, Brazil and others.
- 85+ nations, including the African Union, have national AI strategies.
- India has no formal AI law or endorsed strategy; the 2018 NITI Aayog report is unofficial and unfunded.
- The IndiaAI Mission works through seven thematic pillars, such as foundational models, skilling, innovation hubs and data platforms.
Flexible approach
| Plus | Minus |
|---|---|
| Adapts to changing technology | No clear roadmap |
| Flexible amid geopolitical shifts | No milestones, budget, accountability or enforcement |
| Reactive, leader-dependent policy |
Need for guardrails
- Adoption is quick but oversight is weak; healthcare, finance, education and administration lack transparency, efficacy metrics and evaluation.
- Voluntary compliance risks discrimination, privacy breaches, cyber threats, job losses and misinformation.
Lessons from data rules
- The DPDP Act, 2023 is centralised and cross-sectoral, like EU’s GDPR and China’s PIPL; the U.S. is sector-specific.
- China has specific laws on generative AI and deep synthesis.
- India could adopt a hybrid model built on DPDP.
Way forward
- Release a National AI Policy covering vision, implementation, ethical guardrails, sector risks, responsible authorities and priority sectors.
- Lead public debate on bias, jobs, data provenance and algorithmic accountability.
Exam angle
- Mission: IndiaAI Mission – seven pillars.
- Law linked: DPDP Act, 2023.
- Suggestion: policy first, legislation later.