The Rise of AI as an Economic Force
Artificial Intelligence (AI) is no longer just an emerging technology; it has become the defining economic force of the 21st century. It influences economic competitiveness, scientific discovery, military capability, and national power. Understanding its economics is essential for effective policymaking.
As Lionel Robbins once said, economics is the science of allocating scarce resources among competing ends. This principle applies equally to the economics of AI. Every country must decide where to deploy limited capital, talent, and institutional capacity to maximize returns while managing risk. For India, this means identifying where value is created within the AI economy and, more importantly, where it has a genuine comparative advantage.
Understanding the AI Ecosystem
A useful way to think about AI is as a four-layer system. At the top is the application layer, where economic value is realized through AI copilots, healthcare diagnostics, financial analytics, autonomous systems, and manufacturing optimization. Beneath it lies the model layer — the AI "brains" comprising foundation models, LLMs, and multimodal systems developed by firms like OpenAI, Meta, and Google DeepMind.
The third layer is talent: the engineers, researchers, and academics who build, deploy, and continuously improve AI systems. At the foundation sits the infrastructure layer, encompassing electricity, data centers, cloud computing, networking, cooling technologies, and storage, as well as advanced semiconductors that power AI computation. A successful AI strategy must determine how scarce resources should be allocated across these four layers to maximize economic returns while advancing broader social welfare.
Insights from Global AI Rankings
Insights from the Stanford AI Index and the Global AI Vibrancy (GAIV) framework offer a useful starting point. The GAIV framework evaluates countries across indicators spanning research, infrastructure, education, policy, governance, and public engagement. In the latest rankings, India placed fourth globally, behind only the US, China, and the UK, and ahead of several advanced economies. This is encouraging, but rankings alone do not reveal the optimal economic model for India. They do, however, help identify where India’s comparative advantages lie.
Infrastructure: A Critical Component
Consider infrastructure first. AI is extraordinarily energy-intensive. Data centers and compute clusters require reliable and abundant electricity. India is making meaningful progress, with an ambitious target to achieve 500 GW of non-fossil-fuel power capacity by 2030. While challenges surrounding grid reliability and distribution persist, India’s ability to scale both conventional and renewable energy could become a major competitive advantage.
India is also well-positioned geopolitically to emerge as a relatively safe destination for data centers and AI factories. However, the picture is less favorable in semiconductors. The first phase of the AI hardware race has been dominated by the US, Taiwan, and China. Firms such as Nvidia, AMD, and TSMC have established formidable technological leads. India’s semiconductor ambitions remain important for long-term resilience, but catching up in frontier chip manufacturing will require immense capital, technological capability, and time.
Talent: India's Greatest Advantage
India’s strongest advantage lies in the talent layer. It possesses one of the largest reservoirs of engineering and digital talent and is increasingly becoming a significant contributor to AI research. Its education system produces millions of STEM graduates, while its software services industry can be redirected towards AI-driven services at relatively low marginal cost.
The evidence extends beyond workforce scale. India ranks third in several AI innovation metrics, behind only the US and China. It leads in AI conference citations and is among the largest contributors to journal publications. These indicators suggest India is no longer merely adopting technologies developed elsewhere; it is participating in the creation, refinement, and dissemination of AI knowledge.
The Model Layer: A Growing Challenge
The greatest challenge lies in the model layer. Frontier AI development is becoming increasingly concentrated among a handful of firms with access to extraordinary amounts of capital, compute, and talent. According to the latest AI Index, the US produced 59 notable AI models in 2025, while China produced 35. OpenAI alone released 20 notable models, Google 14, and Alibaba 11, underscoring how concentrated frontier AI has become.
The economics of frontier AI are daunting. Training cutting-edge models requires investments in billions of dollars. Training costs have risen from a few million dollars just a few years ago to well above $100 million per model, while future generations may require several billion dollars. The supporting infrastructure investments are even larger. This financial gap is stark. In 2025, private AI investment in the US reached $285.9 billion, compared with $12.4 billion in China. India’s IndiaAI Mission has committed roughly $1.2 billion to develop domestic AI capabilities. Given the realities, it is difficult to imagine India matching the financial firepower or risk appetite of the leading AI powers.
Implementation: The New Frontier
Further, as AI adoption accelerates globally, organizations increasingly require engineers, cloud specialists, data scientists, and deployment experts who can integrate AI into business processes. Organizational AI adoption globally has reached 88% already, while generative AI achieved population-level adoption faster than either the personal computer or the internet.
India’s global capability centers (GCCs) exemplify this opportunity. Once viewed as cost-saving back offices, GCCs are rapidly evolving into centers for product development, advanced analytics, cloud engineering, cybersecurity, and AI deployment. India today hosts over 1,800 GCCs employing nearly two million professionals. As enterprises integrate AI into their operations, this ecosystem could become one of India’s most vital strategic assets.
Strategic Focus on Comparative Advantages
The appropriate economic model for India is thus not to blindly replicate the frontier AI strategies of the US or China. Instead, it should deepen its capabilities in areas where it enjoys a comparative advantage: talent, infrastructure, and AI implementation. India is uniquely positioned to become a leading producer of AI talent, a major contributor to AI research, and a critical hub for AI deployment. In the economics of AI, success will not come from competing everywhere, but from competing where India can win.
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