India’s ‘Third Way’ for AI Governance

UPSC Syllabus: Gs Paper 3- Government policies and interventions for development in various sectors and issues arising out of their design and implementation.

Introduction

India is hosting the AI Impact Summit at a time when the world is unsure how to govern artificial intelligence. Countries are struggling to balance innovation with risks that are both known and uncertain. India proposes a “Third Way” that supports development while recognising limits of existing global models. This approach aims to suit countries whose economic and institutional realities differ from major AI powers.

The Global AI Governance Landscape

1. Competing governance models: The world follows three major approaches — the European Union’s compliance-heavy regime, the United States’ hands-off market model, and China’s centralised state control. Each reflects different policy traditions.
2. Limited transferability to other countries: These governance systems were built for specific policy traditions. They do not easily fit the needs of countries outside major AI powers.
3. Global uncertainty over the right balance: There is confusion about how to promote innovation while managing risks. No single model has emerged as universally suitable.

India’s Distinct AI Governance Approach

1. Governance beyond regulation: India’s framework covers adoption, diffusion, diplomacy, and capacity buildingalong with risk management, showing a broader governance vision. For e xample — National AI governance guidelines (November 2025) go beyond regulation and focus on scaling AI responsibly across sectors.
2. Inclusive development as priority: AI is meant to scale across healthcare, agriculture, education, and public administration to support broad social and economic development.
3. Working through existing legal structures: The framework does not create separate AI legislation. It uses current laws while remaining flexible and forward-looking.
4. Agile and evolving policy design: High-level principles are converted into practical guidelines. The framework can change as technology develops.
5. Early implementation through regulatory action: Amendments to IT rules (February 10) require labelling of AI-generated content and a three-hour takedown window for harmful material. This is the first government mandate for AI-generation disclosure.

Concern Related to India’s Distinct AI Governance Approach

1. Worker protection gap in rapid AI expansion: Accelerating adoption without labour safeguards risks displacement and inequality, creating an unbalanced governance model.
2. Insufficient minimum standards for accountability: Clear requirements for transparency and responsibility of AI developers are not fully established.
3. Weak institutional protection for vulnerable groups: Mechanisms to safeguard whistleblowers and affected populations require stronger policy attention.
4. Limited public awareness and participation: Citizens need better understanding of AI risks and greater agency in governance processes.
5. Incomplete people-centred governance structure: Innovation expansion is not fully matched with social protection systems for those affected by technological change.
6. Risk of coordination without safeguards: Governance cooperation among countries may remain ineffective if social protections and accountability measures are not clearly defined.

Significance for the Global South and Middle Powers

1. Unequal global AI investment landscape: AI funding is concentrated among a few private actors in the Global North. This creates uneven access and influence.
2. Dependence on external AI systems creates risks: Reliance on proprietary technologies introduces new context-specific vulnerabilities and limits domestic control.
3. Alternative governance pathway for developing economies: India promotes strategic autonomy, localised governance design, and strong public-private partnerships suited to domestic needs.
4. Need for shared research and safety infrastructure: Middle powers require collaborative evaluation frameworks, joint research networks, and mechanisms to pool expertise on risks that no single country can assess alone.
5. India’s capacity to lead coordination efforts: Its size, scale, and leading role in AI infrastructure, combined with historic success in digital development and access expansion, position it to convene collective governance.

Way Forward

1. Expanding infrastructure and compute access: Empowering national initiatives can widen AI adoption and reduce entry barriers for diverse users.
2. Improving data governance and sharing systems: Strong data governance and portability standards can support responsible innovation and accessibility.
3. Promoting locally relevant datasets: Developing culturally representative datasets enables inclusive and context-sensitive AI models.
4. Ensuring evaluation datasets and compute availability: Access to testing infrastructure supports safe deployment and continuous safety assessment.
5. Integrating AI with digital public infrastructure: Linking AI with existing systems allows scalable and inclusive technology delivery across sectors.
6. Need for international coordination: Effective enforcement against global technology firms requires cross-border regulatory cooperation.

Conclusion

India’s “Third Way” seeks to balance innovation, strategic autonomy, and inclusive development while offering an alternative to dominant global models. Yet important gaps remain in worker protection, accountability, and public safeguards. The coming year will test whether India can align innovation with human welfare. Its choices will shape whether this governance model becomes globally influential.

For detailed information on India’s AI Guidelines for Tech Regulation read this article here

Question for practice:

Examine how India’s “Third Way” for AI governance differs from existing global governance models and evaluate its significance and challenges for developing countries and middle powers.

Source: The Hindu