[Answered] Evaluate how transitioning to an AI-driven economy can propel India past structural growth traps. What institutional interventions are required to achieve this?

Introduction

With the ₹1 lakh crore Research, Development and Innovation (RDI) Scheme in Budget 2026–27 and the Economic Survey 2025–26 identifying AI as a productivity multiplier, India’s next growth acceleration increasingly depends on AI-led structural transformation.

How AI Can Propel India Beyond Structural Growth Traps

1. Escaping the Middle-Income Trap: Shift from low-value IT outsourcing to AI products, patents and proprietary foundation models. Capture greater value through intellectual property rather than labour arbitrage, supports transition towards a knowledge economy. Example: BharatGen Param-2.
2. Raising Productivity Across Sectors: AI enhances Total Factor Productivity (TFP) in agriculture, manufacturing and services. Enables predictive maintenance, precision farming, smart logistics and improves competitiveness of MSMEs. Example: AI-based crop advisory.
3. Transforming Manufacturing: AI-driven automation improves quality control, supply-chain optimisation and inventory management. Complements PLI and Make in India by increasing industrial efficiency, facilitates Industry 4.0 adoption. Example: Smart factories.
4. Strengthening Digital Public Infrastructure: Integrating AI with Aadhaar, UPI, ONDC and Bhashini enables intelligent public service delivery. Improves administrative efficiency and reduces governance costs. Supports minimum government, maximum governance.
5. Revolutionising Healthcare: AI supports early diagnosis, disease surveillance and telemedicine. Addresses shortage of specialists in rural India, reduces healthcare inequalities. Example: TB screening AI.
6. Strengthening National Security: Indigenous AI reduces dependence on foreign digital ecosystems. Enhances cyber security, defence analytics and intelligence, supports technological sovereignty. Example: Defence AI.
7. Climate and Agricultural Resilience: AI enables precision irrigation, weather forecasting and disaster prediction, supports climate-smart agriculture. Example: Flood prediction.
8. Boosting India’s Global Competitiveness: AI leadership strengthens India’s role in trusted technology partnerships. Expands AI exports and Global Capability Centres (GCCs). Supports India’s Digital Global South leadership. Example: IndiaAI Mission.

Structural Bottlenecks Limiting AI-led Growth

1. Low Gross Expenditure on R&D (GERD) (~0.64% of GDP).
2. Dependence on imported GPUs and foreign cloud infrastructure.
3. Shortage of frontier AI researchers.
4. Limited availability of high-quality indigenous datasets.
5. Digital divide across regions.
6. Regulatory uncertainty around AI governance.
7. MSMEs’ limited AI adoption.
8. Fragmented academia-industry collaboration.

Institutional Interventions Required

1. Expand Sovereign Compute Infrastructure: Scale the IndiaAI Compute Portal with affordable GPU access. Establish regional AI supercomputing centres, encourage multi-vendor hardware ecosystem. Example: NVIDIA-AMD-TPU mix.
2. Increase Public and Private R&D Investment: Operationalise the ₹1 lakh crore RDI Scheme, target GERD above 2% of GDP and encourage corporate AI laboratories. Example: Deep-tech grants.
3. Build AI Talent Ecosystem: Universal AI literacy in schools and universities. AI Centres of Excellence in IITs, IIITs and NIT, reskilling through Skill India. Example: AI fellowships.
4. Develop Sovereign Foundation Models: Promote multilingual LLMs trained on Indian datasets. Reduce dependence on foreign APIs, strengthen digital sovereignty. Example: BharatGen.
5. Integrate AI with Digital Public Infrastructure: Build AI applications on UPI, ONDC, Ayushman Bharat Digital Mission and Bhashini, enable citizen-centric governance. Example: Smart public services.
6. Create a Robust AI Regulatory Framework: Operationalise the IndiaAI Safety Institute. Ensure algorithmic transparency, accountability and privacy. Align with the Digital Personal Data Protection Act. Example: Responsible AI.
7. Support AI Adoption by MSMEs: AI vouchers, cloud credits and tax incentives. Common AI testing facilities and digital extension services. Example: Cluster innovation.
8. Strengthen Global Partnerships: Collaborate through Quad, GPAI and trusted AI alliances. Facilitate semiconductor and compute cooperation. Example: India-US AI partnership.

Way Forward

1. Launch a National AI Token Policy for affordable compute access.
2. Establish AI Innovation Zones linked with industrial corridors.
3. Promote open-source Indic AI ecosystems.
4. Create sovereign AI cloud infrastructure.
5. Encourage AI-driven public procurement.
6. Institutionalise ethical AI audits and regulatory sandboxes.
7. Expand AI applications in agriculture, health, judiciary and education.
8. Adopt outcome-based AI funding linked to patents, startups and productivity gains.

Conclusion

Echoing Dr. A.P.J. Abdul Kalam’s India 2020, technological self-reliance must underpin national development. AI-led reforms can transform India’s demographic dividend into enduring productivity, innovation and inclusive global leadership.