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Experts have proposed an ambitious "Reforms 3.0" roadmap aimed at transforming India into a high-growth economy by sustaining a "Bharat Rate of Growth" of over 8% annually during the coming decade through large-scale adoption of Artificial Intelligence (AI), digital public infrastructure, and research-driven innovation.

What is Reforms 3.0?

Reforms 3.0 is a proposed policy framework that views Artificial Intelligence (AI) as a strategic national infrastructure rather than merely a commercial technology. Similar to the transformative economic liberalisation of 1991, the roadmap seeks to position AI as the next engine of economic growth by democratizing access to advanced computing resources, promoting indigenous innovation, and strengthening India's technological sovereignty.

The proposal advocates making open-source Large Language Models (LLMs) widely available and providing free AI processing tokens to leading universities, research institutions, and educational institutions to accelerate innovation across sectors.

Need for Reforms 3.0

The proposal highlights that India's investment in Research and Development (R&D) remains significantly below global standards.

India currently spends only 0.65% of GDP on R&D, compared to:

• China: 2.4%
• United States: 3.5%
• South Korea: 4.9%
• Israel: 5.4%

This low investment constrains technological innovation and limits India's ability to compete in frontier technologies such as Artificial Intelligence.

The report estimates that providing free AI access to India's leading universities, laboratories, and selected schools would require an annual expenditure of nearly USD 2 billion, equivalent to only 0.06% of GDP, which is substantially lower than existing expenditure on food and fertilizer subsidies.

Growth Opportunities

The roadmap argues that widespread access to AI can become a major driver of productivity and long-term economic growth.

Key opportunities include:

• Achieving a sustained GDP growth rate exceeding 8% through AI-enabled productivity gains.
• Building a highly skilled digital workforce by subsidising access to AI tools instead of focusing solely on conventional subsidies.
• Leveraging India's 1.4 billion-user digital market to negotiate favourable cloud computing partnerships with global technology companies.
• Promoting AI data sovereignty through deployment of open-source AI models hosted entirely within India.
• Creating a sustainable funding model where enterprise users subsidise free AI access for educational and public institutions.

India's Existing Digital Strengths

The proposed reforms build upon India's strong digital public infrastructure developed over the past decade.

Major achievements include:

• Aadhaar, covering approximately 1.38 billion citizens.
• Unified Payments Interface (UPI), processing nearly 250 billion transactions annually, accounting for almost half of the world's real-time digital payments.
• Significant reduction in mobile data costs from nearly USD 3 per GB to around USD 0.10 per GB, making digital services widely accessible.
• Emergence of indigenous AI models such as Sarvam, demonstrating India's capability to develop Large Language Models tailored to Indian languages.

Challenges

Despite its potential, the proposed roadmap faces several important challenges.

These include:

• Heavy dependence on expensive foreign AI hardware, particularly GPUs.
• High capital costs associated with developing sovereign computing infrastructure.
• Complex negotiations with global cloud service providers.
• Cybersecurity risks such as prompt injection attacks and AI hallucinations.
• Need for substantial engineering capacity to maintain large-scale AI infrastructure.
• Political and fiscal challenges in reallocating public expenditure towards digital infrastructure.

Way Forward

The report recommends several policy measures to operationalise the vision.

These include:

• Diversifying computing infrastructure through a 40:30:30 hardware strategy, reducing dependence on a single technology provider.
• Formulating a National AI Token Policy to provide affordable AI computing resources.
• Launching pilot programmes providing free AI tokens to premier institutions such as IITs and IISc.
• Developing foundational AI models in all 22 Scheduled Languages to improve accessibility.
• Recognising AI computing infrastructure as a strategic national asset, similar to investments in the space and nuclear sectors.