Nandan Nilekani's Bold AI Vision: Why India Must Focus on Use Cases, Not Chips

At the NCAER India Policy Forum 2026, Infosys co-founder Nandan Nilekani delivered a compelling address that reframed India's position in the global Artificial Intelligence race. The NCAER, or National Council of Applied Economic Research, is a premier policy think tank in India that convenes this annual forum to bring together policymakers, industry leaders and academics to discuss the country's most pressing economic challenges. Nilekani argued that India should position itself as the "AI use-case capital of the world" rather than pursuing the more traditional ambition of becoming a chip manufacturing hub or a leader in building foundational large language models. His remarks, covered extensively by Businessworld, have ignited a crucial conversation about where India's true competitive advantage lies in the rapidly evolving AI landscape.

Why the 'Use-Case' Strategy Makes Sense for India

The global AI race is currently dominated by a few players in the United States and China, who are investing billions in developing cutting-edge chips and massive foundational models like GPT and Gemini. India, Nilekani noted, does not have the same deep-pocketed venture capital ecosystem or chip fabrication infrastructure to compete on that front. However, the nation has something far more valuable: a population of 1.4 billion people with pressing needs in agriculture, healthcare, education, and governance. Applying AI to solve these problems at scale is where India can achieve global leadership.

The Role of India's Digital Public Infrastructure in AI Adoption

Central to Nilekani's vision is the concept of leveraging existing digital public infrastructure to accelerate AI adoption. Systems like Aadhaar, UPI, and the Open Network for Digital Commerce are already generating vast amounts of data, and AI models can be trained on this data to create applications that are deeply integrated into the daily lives of Indian citizens. This bottom-up approach to AI adoption is fundamentally different from the top-down approach of building large models first and finding applications later, and it highlights a crucial strategic choice: India can either attempt to compete in the expensive race for chip dominance, or it can build an unassailable lead in the application layer, which aligns with its strengths in software development. The focus on practical applications is already visible across multiple sectors, with demand for AI talent reaching unprecedented levels, and a detailed look at where the AI jobs are in India reveals that industries ranging from healthcare to agriculture are actively seeking professionals who can build use-case-driven solutions.

A Million Small Businesses: Nilekani's Vision for AI-Driven Employment

One of the most striking aspects of Nilekani's address was his prediction that India could see the creation of "one million companies employing one person each" rather than a few large corporations generating massive employment, a decentralised model that aligns with the nature of AI applications where small, focused teams can build niche products. This vision suggests that the future of AI in India is not about building massive data centres but about empowering individuals to become entrepreneurs using AI as a tool, resonating with India's traditional strength in small-scale enterprise and its burgeoning startup ecosystem, which has produced numerous unicorns in recent years.

Startups as the Engine of India's AI Use-Case Revolution

Nilekani expressed strong confidence in India's startup ecosystem, suggesting it is the perfect laboratory for developing AI use-cases that could eventually be exported to the rest of the world through rapid experimentation and iteration on local problems. The country is already witnessing a surge in AI-focused startups across healthcare, agriculture, fintech, and logistics, and by focusing on use-cases, these companies can create intellectual property that is transferable to other emerging markets facing similar challenges, positioning India not just as a market for AI, but as a global leader in AI innovation.

Learning from China's Model Without Following the Same Path

China's rapid advancement in AI, driven by massive state-backed industrial policy, is often cited as a model for India, but Nilekani argued that India's path must be distinct, with its more market-driven economy and stronger democratic institutions better suited to a bottom-up, use-case-driven approach. By focusing on applications that run on affordable hardware and are accessible through smartphones, India can ensure that the benefits of AI reach the masses, including those in rural areas, creating a massive market opportunity while avoiding the capital-intensive race for chip dominance.

The Critical Need for Portable Social Security Benefits

Nilekani also highlighted the structural challenges of the new AI-driven economy, pointing out that the traditional model of formal sector employment with employer-provided social security benefits may become less relevant in a world of one-person companies and gig workers. He emphasised that social security benefits must become portable and accessible to individuals regardless of employment status, requiring policy frameworks that include universal health insurance, pension schemes, and other safety nets not tied to a single employer, with the government's efforts to create a unified labour market being steps in this direction.

Why Foundation Models Are Not the Only Path to AI Leadership

A significant part of Nilekani's argument rests on the idea that building large language models is not the only way to lead in AI, as foundational models are essentially tools whose true value is created in the applications built on top of them. By focusing on the application layer, India can avoid the enormously expensive and capital-intensive race to train foundation models and instead leverage open-source models and APIs to build powerful, customised solutions, creating more jobs and yielding higher returns on investment. For those looking to enter the field, a comprehensive guide on top AI jobs in India paying up to Rs 80 LPA highlights that roles like Prompt Engineers and GenAI Developers, focused on applying existing models, are among the most in-demand.

Agriculture and Healthcare: The Prime Use-Cases for India

Nilekani and other leaders at the forum emphasised that the most impactful AI applications for India would be in sectors directly affecting the majority of the population, including agriculture where AI can provide real-time advice on weather, crop diseases, and market prices, and healthcare where AI can help bridge the gap in specialist availability. These are not hypothetical scenarios, as pilots and startups are already making progress in these areas, and by showcasing success here, India can build a global brand for "AI for Good" and create a repository of solutions adaptable to other developing nations.

The Importance of Data Sovereignty and Local AI Models

Another critical aspect of Nilekani's vision is the need for India to control its own data and AI models, as relying exclusively on foreign foundation models could create dependencies in sensitive areas like governance and defence. By building local AI applications trained on Indian data and fine-tuned for Indian languages and contexts, India can achieve greater technological sovereignty, requiring investment in Indian-language datasets and research but yielding applications that truly work for Indian users and can be trusted with sensitive information.

The Skill Gap: Preparing India's Workforce for the Use-Case Economy

Nilekani's vision hinges on the availability of a skilled workforce capable of building and deploying AI applications, and while India produces millions of graduates each year, there is a recognised gap between academic curricula and industry requirements that demands interdisciplinary learning. The good news is that the barrier to entry for AI application development is lower than ever, with open-source tools, cloud computing, and online courses enabling individuals to acquire necessary skills in months, though the scale and pace of government and private skilling initiatives must accelerate to meet demand.

How India's AI Use-Case Strategy Compares to Global Trends

Globally, there is a growing recognition that the true value of AI will be realised through applications, and India's strategy is well-aligned with this trend, positioning it to attract investment and partnerships from countries and companies looking to learn from its experience. The focus on use-cases also makes India a more resilient player in the global AI landscape, as strategic autonomy in adapting and building alternatives using its own talent and data is a significant advantage in an increasingly uncertain world order.

The Policy Imperatives for Realising Nilekani's Vision

For Nilekani's vision to become a reality, several policy imperatives must be addressed, including continued investment in digital public infrastructure, regulatory frameworks that encourage innovation, education system reform, and modernisation of social security systems. The NCAER India Policy Forum provided an ideal platform for such discussions, where policymakers, academics, and industry leaders debated these issues, and Nilekani's address was a call to action for all stakeholders to build an AI ecosystem that is inclusive, innovative, and globally competitive.

Conclusion: Building the AI Use-Case Capital of the World

Nandan Nilekani's address at the NCAER India Policy Forum 2026 offers a compelling and pragmatic vision for India to become the "AI use-case capital of the world," leveraging its strengths in digital infrastructure, startup culture, and domestic market diversity to avoid the pitfalls of competing in capital-intensive chip manufacturing. This strategy of applying AI to solve real-world problems, potentially creating a million small businesses in the process, is a sustainable and equitable model that requires concerted effort from policymakers, educators, and entrepreneurs but could position India as a global leader in innovation that improves lives for decades to come.

About the Author & Admin ✍️

AI Researcher • Evaluator & Tester • Blogger • Domain Investor & Analyst • Web Developer • Digital Content Creator • News Editor & Publisher • 37+ Years of Experience in Technology, Sociology & Digital Media