AI-driven Reforms 3.0: Artificial Intelligence as Public Digital Infrastructure for India’s Next Growth Phase

Recent Developments:

• Experts have proposed Reforms 3.0, a roadmap that places Artificial Intelligence (AI) at the centre of India's next phase of economic transformation by treating AI as a public digital infrastructure.
• The proposal aims to achieve a sustained Bharat Rate of Growth of more than 8% over the next decade by shifting India from a technology consumer economy towards a sovereign AI ecosystem.
• The Government of India has already launched the IndiaAI Mission with an objective to build an AI innovation ecosystem through public-private partnerships, improved computing access, indigenous capabilities and responsible AI development.
• India is also strengthening semiconductor capabilities through the India Semiconductor Mission, aimed at developing a domestic semiconductor and electronics ecosystem.

Concept of Reforms 3.0 and Bharat Rate of Growth:

Evolution of India’s Economic Reform Journey:

• Reforms 1.0 (1991): Initiated after the Balance of Payments crisis, introducing Liberalisation, Privatisation and Globalisation (LPG) reforms that accelerated economic growth.
• Reforms 2.0 (Post 2010s): Focused on building Digital Public Infrastructure (DPI) through platforms such as biometric identity systems, Unified Payments Interface (UPI) and affordable mobile internet.
• Reforms 3.0: Represents a shift from physical and basic digital infrastructure towards cognitive infrastructure, where AI becomes a key driver of productivity, innovation and economic growth.

Meaning of Bharat Rate of Growth:

• Historically, India's growth rate remained around 3.5% to 4% for several decades after independence, often referred to as the HindRate of Growth.
• The proposed Bharat Rate of Growth aims to achieve an inclusive, technology-driven growth rate of 8% or above through AI-enabled productivity improvements and innovation.

Key Proposals under AI-driven Reforms 3.0:

National AI Token Policy:

• India should introduce a National AI Token Policy within the next few years to make advanced AI computing resources accessible to researchers, startups and educational institutions.
• The policy proposes Public-Private Partnerships (PPPs) with global cloud and technology companies to develop sovereign AI infrastructure.
• Similar to the Jio effect in telecommunications, affordable AI access can democratise cognitive computing.
• Proposed measures include:
• Free AI research tokens for premier institutions such as Indian Institutes of Technology (IITs) and Indian Institute of Science (IISc).
• Application Programming Interface (API) sandboxes for startups.
• AI literacy programmes in schools.

Subsidising Cognitive Capacity:

Need for Greater AI Research Investment:

• India spends only around 0.65% of GDP on Research and Development (R&D), significantly lower than countries such as:
• Israel,
• South Korea,
• United States,
• China.
• Experts suggest shifting a portion of traditional physical subsidies towards cognitive subsidies that enhance knowledge, computing power and innovation capacity.

Affordable AI Access Model:

• Providing AI access to universities, research institutions and schools would require a relatively small share of national expenditure compared with existing welfare subsidies.
• Such investment can create:
• AI-skilled workforce,
• Research capacity,
• Startup innovation,
• Indigenous AI solutions.

Building Sovereign AI Infrastructure:

Need for Domestic AI Capability:

• India should host major open-source AI models along with indigenous AI models on domestic infrastructure to reduce dependence on foreign AI platforms.
• Dependence on external Application Programming Interfaces (APIs) creates strategic risks because access restrictions can affect national AI capabilities.
• AI infrastructure should be treated as a strategic national capability similar to critical sectors such as space and nuclear technology.

Infrastructure Requirements:

• Large-scale AI deployment requires:
• High availability systems with minimal downtime,
• Low-latency access across Tier-2 and Tier-3 cities,
• Strong data security and domestic data residency frameworks.
• Building such infrastructure is essential for making AI accessible beyond metropolitan areas.

Diversifying AI Compute Hardware:

Challenge of Hardware Dependency:

• AI development requires massive computing power through specialised chips and processors.
• Excessive dependence on a limited number of global hardware suppliers can increase costs and create strategic vulnerabilities.

Proposed Hardware Strategy:

• A balanced hardware ecosystem has been suggested:
• 40%: Domestic inference workloads through alternative AI processors.
• 30%: Academic research and model training through specialised processing units.
• 30%: High-performance graphics processors for advanced training and compatibility.

Public-Private Partnerships and Market Leverage:

Using India’s Market Advantage:

• India’s large consumer base can act as a strategic advantage while negotiating with global technology companies.
• The government can provide:
• Land,
• Energy access,
• Data policy support, in exchange for cloud infrastructure and computing capacity.

Cross-Subsidisation Model:

• Enterprise-level AI services can financially support affordable AI access for:
• Education sector,
• Research institutions,
• Public services.

Developing Indic AI Ecosystem:

Language and Inclusion:

• India needs foundational AI models optimised for all 22 Scheduled Languages.
• Indic AI can expand AI benefits to:
• Rural communities,
• Local governance,
• Agricultural sector,
• Healthcare services,
• Regional legal systems.
• Language-focused AI development can reduce the digital divide created by English-dominated AI systems.

Challenges to AI-driven Reforms 3.0:

Compute-Energy-Climate Trilemma:

• AI data centres require significantly higher electricity consumption compared with traditional cloud infrastructure.
• Large-scale AI expansion may increase pressure on:
• Power systems,
• Water resources,
• Climate commitments.
• India must balance AI growth with its Net Zero target of 2070.

Semiconductor Supply Chain Vulnerability:

• Advanced AI requires specialised semiconductor chips, but India currently lacks advanced semiconductor fabrication capability.
• Dependence on global chip supply chains creates vulnerability due to:
• Geopolitical tensions,
• Export restrictions,
• Supply disruptions.
• The India Semiconductor Mission aims to build a stronger domestic semiconductor ecosystem and reduce import dependence.

Political Economy of Subsidy Reform:

• Shifting resources from traditional subsidies towards AI and knowledge infrastructure may face political resistance.
• Reducing existing welfare expenditure can create social and political challenges, especially in rural areas.

Tokenisation Bias in AI:

• Current Large Language Models (LLMs) often process Indian languages less efficiently than English.
• This creates a token cost disadvantage, increasing computing requirements and making AI access more expensive for Indic languages.

Deficit in Algorithmic Governance:

• AI deployment is advancing faster than legal and regulatory frameworks.
• Major governance concerns include:
• Data protection,
• Algorithmic bias,
• Deepfake regulation,
• AI accountability,
• Intellectual Property Rights (IPR) related to training data.
• Effective implementation of the Digital Personal Data Protection Act, 2023 remains important for responsible AI governance.

Last-Mile AI Infrastructure Challenge:

• Delivering AI services beyond major cities requires strong:
• Edge computing networks,
• 5G connectivity,
• Optical fibre infrastructure.
• Uneven digital connectivity in rural areas can limit inclusive AI adoption.

India’s Existing Initiatives Supporting AI Economy:

Major Government Programmes:

• IndiaAI Mission: Builds AI innovation ecosystem, computing access, startups and responsible AI development.
• India Semiconductor Mission: Develops semiconductor manufacturing, design and supply chain capabilities.
• National Supercomputing Mission: Expands high-performance computing capacity.
• BHASHINI: Promotes language translation technologies for Indian languages.
• Digital Public Infrastructure: Provides scalable digital platforms for public services.

Way Forward:

Building an Inclusive AI-powered Economy:

• India should focus on affordable AI access, indigenous innovation and responsible governance rather than only technology adoption.
• Government’s role should be to create enabling policies, regulatory frameworks and infrastructure so that private innovation can scale.
• A combination of:
• Skilled human capital,
• Strong digital infrastructure,
• Domestic AI capability,
• Stable policy environment,
• can help India achieve sustained high growth.

UPSC Value Addition:

Important Concepts:

• Artificial Intelligence: Technology enabling machines to perform tasks requiring human-like intelligence such as learning, reasoning and decision-making.
• Public Digital Infrastructure: Shared digital platforms created for large-scale public and economic use.
• Sovereign AI: National capability to develop, control and deploy AI systems with reduced external dependence.
• Cognitive Infrastructure: Knowledge-based infrastructure involving data, computing power, research and innovation.
• AI Governance: Framework of laws, ethics and institutions ensuring safe and accountable AI use