For AI, India can build on the Aadhaar-UPI model

Source: The post “For AI, India can build on the Aadhaar-UPI model” has been created, based on “For AI, India can build on the Aadhaar-UPI model” published in “Indian express” on 11th December 2025.

UPSC Syllabus: GS Paper-3- Science and technology

Context: India has demonstrated its ability to deploy technology at a population scale through initiatives like Aadhaar and UPI, which provided secure digital identity and payment systems to millions of citizens. Artificial Intelligence (AI) now offers India an opportunity to leapfrog into a knowledge-driven, inclusive, and green economy, provided the country undertakes the right measures.

Challenges in Building India’s AI Ecosystem:

1. Data Privacy and Security Risks: Handling sensitive citizen data while ensuring privacy and avoiding misuse remains a significant challenge.
2. Infrastructure Limitations: Rapidly expanding AI-ready computing infrastructure, particularly with green energy sources, requires heavy investment and long-term planning.
3. Skilled Workforce Gap: There is a shortage of professionals trained in AI, machine learning, and related technologies, which could slow adoption.
4. Regulatory and Governance Issues: Ensuring compliance with laws, preventing monopolistic practices, and maintaining accountability of AI systems can be complex.
5. Digital Inclusion: Making AI tools accessible and usable by citizens in rural areas and regional languages is challenging but essential for inclusivity.

Key Measures for India’s AI Leadership:

1. Digital Sovereignty and Regulation: India must ensure that AI systems operate under Indian laws and strategic priorities.
   1. Foundation models should be trained, hosted, and regulated within the country to maintain data security, algorithmic accountability, and national security.
   2. This approach balances corporate innovation seen in the West and state-controlled AI models like China.
2. Green AI Infrastructure: India should rapidly expand its computing capacity to host large AI models.
   1. Development of data centres powered by renewable energy such as solar, wind, and green hydrogen can anchor new investment and reduce carbon emissions.
   2. This will promote green industrial growth, including innovation in semiconductors, power electronics, and cooling technologies, and position India at the green frontier of AI development.
3. Inclusive AI Access for Citizens: Every Indian should have a multilingual AI agent that they control, which can assist them in daily life.
   1. For example, farmers can use it for weather and crop advice, students for learning support, and patients for healthcare management.
   2. These agents must be private, transparent, and accountable, with data securely stored under user control.
   3. Building these systems will require open standards, privacy safeguards, and collaboration between government, academia, and startups.
4. Economic and Workforce Implications: While AI may automate some service, coding, and back-office roles, it will also create new opportunities in data infrastructure, model development, and domain-specific AI applications.
   1. Early investment can allow India to capture higher-value AI services, similar to how China leveraged the clean-energy revolution to dominate global supply chains.

Conclusion: By focusing on AI under Indian law, green infrastructure, inclusive citizen access, and workforce readiness, India can create a sustainable, globally competitive, and inclusive AI economy. The principles that made Aadhaar and UPI successful scalability, inclusion, and reliability can serve as a guiding framework for developing India’s AI ecosystem while addressing challenges.

Question: India has the potential to become a global leader in artificial intelligence by building on its digital infrastructure experience. Discuss the key measures needed to achieve this, the challenges involved, and their implications for inclusive growth and sustainability.