India’s artificial intelligence (AI) journey is entering a transformative phase, with the potential to address real-world challenges at an unprecedented scale. Infosys Chairman Mr. Nandan Nilekani, one of India’s most prominent technology visionaries, recently shared his perspective on how India’s population, diversity, and digital infrastructure create an unparalleled foundation for frugal engineering and AI-driven innovation.

Speaking at an event hosted by Walmart Global Tech on August 29, 2025, Nilekani emphasised that the country is uniquely positioned to build solutions that are not only technologically advanced but also inclusive, affordable, and scalable. His speech focused on how India can use AI not as a luxury but as a practical tool to improve everyday lives.

AI and frugal engineering: A unique Indian approach

Frugal engineering refers to designing products and solutions that are cost-effective, simple, and highly scalable. In India, where millions of people live in rural and semi-urban areas with limited resources, frugal engineering ensures that technology adoption is not restricted to the elite. According to Nilekani, India’s size and diversity demand solutions that can work for large populations at minimal costs.

He drew attention to the fact that while the West often builds for high-value, niche markets, India’s focus should be on frugal innovation, which delivers value across income groups. For example, building AI tools that can run on low-cost smartphones or providing services in regional languages makes technology truly democratic.

Three pillars of India’s AI growth

Mr. Nilekani identified three major domains where India is poised to excel in AI adoption:

1. Global Capability Centres (GCCs):
   India hosts thousands of GCCs for multinational corporations. These centres are now leading AI transformation programmes, creating tools and processes that improve efficiency across parent enterprises worldwide. GCCs provide India with a unique vantage point in global AI development, ensuring that the country remains at the centre of corporate AI adoption.

2. Information Technology (IT) Service Providers:
   Indian IT companies such as Infosys, TCS, and Wipro are helping clients globally in their AI journeys. By building, training, and deploying AI solutions, these IT firms ensure that AI adoption is cost-effective while addressing industry-specific challenges. This positions India as not just a consumer of AI but also as a key enabler in the international technology landscape.

3. Digital Public Infrastructure:
   Perhaps India’s greatest strength lies in its digital public infrastructure (DPI). Systems such as Aadhaar and UPI are prime examples of population-scale innovations that are both simple and powerful. Nilekani emphasised that such infrastructure provides a strong foundation for scalable AI applications. With Aadhaar enabling universal identification and UPI powering real-time digital payments, AI can be built on top of these trusted systems for maximum reach.

Practical examples: AI in action

To illustrate the real-world impact of AI, Nilekani cited the example of a farmer in Bihar receiving real-time farming advice in his local language. By leveraging small language models (SLMs) trained specifically for Indian languages and contexts, farmers can access personalised, timely, and relevant insights. This approach ensures that AI is not just a buzzword but a practical solution for critical issues such as agriculture, healthcare, and education.

Aadhaar and UPI: Benchmarks of innovation

Nilekani revisited India’s two most successful innovations—Aadhaar and UPI—to demonstrate how simplicity, scalability, and inclusion can create groundbreaking impact.

• Aadhaar: With just four key identification fields, Aadhaar was designed for minimalism and efficiency. Its architecture allowed for the enrolment of 1.5 million people daily, enabling near-universal digital identity across India. This became the backbone for multiple government and private sector services.

• UPI: Built with an interoperable and privacy-protected API, UPI enabled real-time payments across banks and platforms. Its single-page design made it simple for users of all literacy levels. Today, UPI processes billions of transactions monthly and has become a global reference model for inclusive payments.

These systems are now being seen as blueprints for AI adoption—simple, inclusive, and scalable solutions that can reach every citizen.

Small language models (SLMs): India’s next big bet

Globally, companies are competing to build ever-larger large language models (LLMs), which require significant resources. However, Nilekani suggested that India could lead by focusing on small language models (SLMs).

These models are:

• Cost-effective – requiring less computational power.

• Locally relevant – trained on regional data and languages.

• Scalable – able to serve millions of people in resource-constrained environments.

By developing SLMs, India can provide AI for the masses, ensuring accessibility even for those with low-end devices or limited internet connectivity.

Inclusion and accessibility: The Indian way

Nilekani strongly emphasised that inclusion must be at the heart of AI development. Unlike developed countries where technology adoption often starts with high-income groups, India’s path must prioritise rural communities, low-income households, and non-English speakers.

For example, AI-driven solutions in healthcare could provide remote diagnostics, AI in education could help with personalised tutoring, and AI in agriculture could optimise crop yields. All of this depends on making solutions affordable, multilingual, and easy to use.

Global relevance of India’s AI model

Nilekani also pointed out that India’s approach is not just relevant domestically but could become a global model for developing nations. Countries in Africa, Southeast Asia, and Latin America share similar challenges—large populations, resource constraints, and diverse languages. By building solutions that work in India, the country can export its AI expertise to other regions.

The road ahead: Balancing speed with responsibility

While AI holds immense promise, Nilekani acknowledged the importance of responsible deployment. AI must be used in ways that safeguard privacy, fairness, and transparency. With India’s proven track record of balancing scale with trust through Aadhaar and UPI, Nilekani expressed confidence that the nation can become a global leader in ethical AI adoption.

✅ In summary, India is uniquely positioned to lead the world in AI adoption through frugal engineering, digital infrastructure, and inclusive design. By focusing on scalability, affordability, and accessibility, India can turn AI into a tool that transforms millions of lives, not just a privileged few. Nandan Nilekani’s vision underscores the importance of building simple, inclusive, and locally relevant AI solutions, making India not just a participant but a pioneer in the AI-driven future.

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