Kicking Down the Ai Ladder (IE)

Kicking Down the Ai Ladder (IE)

GS Paper III (Science & Technology, Economy, Internal Security) and GS Paper II (Global Governance).

Introduction

The editorial examines a contemporary national issue, highlighting the need for evidence-based reforms, cooperative federalism, and institutional resilience to address emerging governance and development challenges.

Background

1.        Rapid advances in Artificial Intelligence (AI) have intensified global competition, with leading nations increasingly treating AI as a strategic geopolitical asset.

2.      Advanced economies are introducing export controls and governance frameworks that may limit developing countries' access to frontier AI technologies, creating a new technological hierarchy.

3.      Against this backdrop, the editorial argues that India must build indigenous AI capabilities and reduce technological dependence to achieve long-term strategic and economic resilience.

Key Issues

1.        AI Monopoly and Technological Dependence

·         A few advanced countries and Big Tech firms dominate AI infrastructure, chips, data, and foundational models, limiting equitable access and increasing technological dependence of developing nations.

2.      Restrictive AI Governance and Digital Protectionism

·         Emerging global AI regulations, export controls, and restrictions on advanced technologies risk creating digital barriers that prevent latecomer countries from developing indigenous AI capabilities.

3.       Weak Domestic AI Ecosystem

·         India faces challenges such as inadequate compute infrastructure, limited access to quality datasets, dependence on imported semiconductors, and shortages of advanced AI talent, constraining innovation.

4.       Need for Inclusive and Sovereign AI Development

·         Ensuring AI sovereignty requires strengthening domestic R&D, semiconductor manufacturing, digital public infrastructure, open-source AI, skilled human capital, and international cooperation to achieve equitable and self-reliant AI growth.

Challenges

1.        Technology Concentration and AI Dependence

• Export controls, licensing requirements, and restrictions on advanced AI models and chips risk creating long-term technological dependence for developing countries, limiting equitable access to frontier AI capabilities.

2.      Regulatory Capture and Erosion of Sovereignty

• AI governance led by a few technologically advanced nations and private firms may centralise decision-making, weaken democratic accountability, and constrain the policy autonomy of developing economies.

3.      Socio-Economic Risks for Developing Economies

• Existing AI governance focuses primarily on security risks while inadequately addressing labour displacement, employment disruptions, and widening digital inequalities in countries with limited social protection systems.

4.      Barriers to Indigenous AI Capability

• Dependence on foreign AI infrastructure, advanced semiconductors, and foundational models hinders domestic innovation, strategic resilience, and the development of sovereign AI ecosystems.

Government Initiatives

1.        IndiaAI Mission & AI Stack: Expanding indigenous AI capabilities through compute infrastructure, foundational AI models, IndiaAIKosh datasets, and support for startups under the ₹10,300 crore IndiaAI Mission.

2.      Semicon India Programme & India Semiconductor Mission (ISM 2.0): Strengthening semiconductor design, R&D, supply chains, and domestic chip manufacturing to reduce external technology dependence.

3.      Digital Public Infrastructure (DPI): Leveraging platforms such as Aadhaar, UPI, ONDC, and Bhashini to build India-centric AI applications in governance, healthcare, agriculture, and multilingual services.

4.      AI Governance, Skilling & Sovereignty: Advancing ethical AI, AI skilling, and sovereign AI capabilities through the India AI Impact Summit, UNESCO AI Readiness Assessment, and the proposed revamp of the IndiaAI Mission focusing on sovereignty, safety, talent, and research.

Way Forward

1.        Build Strategic AI Capabilities: Develop indigenous AI across the value chain—compute, semiconductor design, small language models, and next-generation hardware—to reduce technological dependence and achieve strategic indispensability.

2.      Promote Inclusive and Democratic AI Governance: Advocate for transparent, multilateral AI regulations that ensure equitable participation of developing countries while preventing regulatory capture by a few dominant technology powers.

3.      Leverage India's Comparative Advantage: Scale domain-specific AI in agriculture, healthcare, governance, and Digital Public Infrastructure (DPI), while strengthening R&D, innovation ecosystems, and global partnerships to create globally relevant AI solutions.

4.      Balance Innovation with Employment and Security: Encourage responsible AI deployment through workforce reskilling, social safeguards, and robust cybersecurity to ensure AI-driven growth remains inclusive and resilient. 

Conclusion

India should support inclusive and democratic AI governance while strengthening indigenous AI capabilities, ensuring that global regulations promote equity, innovation, and technological sovereignty rather than entrenching existing technological monopolies.

Source: https://www.newindianexpress.com/opinion/2026/Jun/23/kicking-down-the-ai-ladder

Question

1. Examine the concept of 'AI sovereignty'. What measures should India adopt to achieve strategic autonomy in Artificial Intelligence?

Introduction

AI sovereignty refers to a nation's ability to independently develop, deploy, regulate, and secure Artificial Intelligence systems by retaining control over data, computing infrastructure, talent, algorithms, and governance, thereby ensuring strategic autonomy and national security.

AI Sovereignty for India

1.        Reduces dependence on foreign AI models, cloud infrastructure, and semiconductor supply chains.

·         Example: The IndiaAI Mission (34,000+ GPUs) and the India Semiconductor Mission aim to build indigenous AI compute and chip manufacturing capabilities, reducing reliance on foreign technology.

2.      Protects data sovereignty, critical infrastructure, and national security.

·         Example: The IndiaAI Mission (2024) seeks to build sovereign AI compute infrastructure, reducing dependence on foreign AI ecosystems for sensitive government and strategic applications

3.       Bhashini Initiative (MeitY) develops indigenous multilingual AI models for 22+ Indian languages, enabling inclusive digital governance and AI solutions aligned with India's linguistic diversity and socio-economic needs.

Challenges To India’s Ai Sovereignty

         i.            Dependence on imported GPUs, advanced chips, and cloud services.

       ii.            Limited indigenous foundation models and high-performance computing capacity.

     iii.            Shortage of advanced AI research talent and fragmented datasets.

    iv.            Risks of algorithmic bias, cyber threats, and external technological dependence.

Measures To Achieve Strategic Ai Autonomy

1.        Strengthen AI Infrastructure

1. Expand compute capacity through the IndiaAI Mission (MeitY), which aims to provide 34,000+ GPUs via the IndiaAI Compute Facility to startups, researchers, and academic institutions at subsidized rates.
2. Example: In 2025, the Government operationalised the IndiaAI Compute Facility, empanelling multiple cloud service providers to make high-end GPU access available for indigenous AI development.

2.      Build Indigenous Semiconductor Capability

1. Accelerate the India Semiconductor Mission (ISM) and Semicon India Programme to reduce dependence on imported AI chips.
2. Example: The Government approved semiconductor projects such as the Tata Electronics semiconductor fabrication plant at Dholera, Gujarat, and the Tata OSAT facility at Morigaon, Assam, strengthening India's domestic chip ecosystem.

3.      Develop Sovereign AI Models

1. Promote Indian multilingual foundation models using the Bhashini Initiative (MeitY) and trusted public datasets.
2. Example: BHASHINI enables AI applications in 22+ Indian languages, supporting translation, speech recognition, and voice-based public services for inclusive digital governance.

4.      Strengthen Governance and Talent

1. Implement the IndiaAI Mission's Safe & Trusted AI pillar, expand AI skilling, and foster academia-industry collaboration.
2. Example: The IndiaAI FutureSkills pillar under the IndiaAI Mission is supporting AI education, reskilling, and fellowships in partnership with IITs, IIITs, and other higher educational institutions, while the Safe & Trusted AI pillar promotes responsible and ethical AI development.

Conclusion

AI sovereignty is central to India's economic competitiveness, digital security, and strategic autonomy. A coordinated approach combining indigenous innovation, robust digital infrastructure, skilled human capital, and responsible governance will enable India to emerge as a trusted global AI leader.