Nvidia’s dollar five-trillion leap and the new power calculus

Nvidia’s surge past the USD 5 trillion valuation mark has become more than a milestone in corporate history. It is a signal of a deeper global realignment. The company’s extraordinary acceleration—from USD 1 trillion in 2023 to USD 5 trillion within two years—reflects how high-performance computing has moved to the centre of economic competitiveness.

Earlier, it took nearly thirty years since inception for the company to cross the trillion-dollar market cap. At the same time, the rapid journey from USD 4 to USD 5 trillion came in only 78 trading sessions.

This unprecedented rise also highlights a new paradigm: compute power has become the primary currency of the digital era. Control over advanced silicon now shapes industrial capability, national strategy, and geopolitical leverage, placing companies like Nvidia at the heart of global influence.

At the same time, the scale and speed of this valuation raise critical questions about the sustainability of the AI boom, the long-term pricing of technological potential, and the strategic implications for emerging digital economies such as India.

Nvidia’s move past USD 5 trillion firmly positions it alongside global technology giants, surpassing Apple and Microsoft in valuation. The company now represents nearly 8% of the S&P 500, while the Magnificent Seven—Apple, Amazon, Alphabet, Meta, Microsoft, Nvidia and Tesla—account for 37% of total index value. The AI fervour has lifted related stocks. Yet Nvidia’s valuation exceeds that of AMD, Broadcom, Intel, and TSMC combined.

Such extreme concentration means Nvidia’s stock movements can significantly influence global indices.

Divergent Bull and Bear Perspectives

Investor sentiment remains split between optimism and caution. Bullish investors argue that Nvidia stands at the beginning of a multi-decade computing cycle. AI workloads are expanding, robotics and industrial automation are accelerating, and nations are preparing for significant investments in massive AI infrastructure. If AI delivers sustained productivity gains, current valuations may prove conservative.

Bearish analysts, however, warn of bubble-like dynamics. Market valuations now exceed those seen during the dot-com era. The speed of capital deployment is unprecedented, payback periods remain uncertain, and competition from alternative chip architectures could reshape demand. Additionally, over-capacity risks in data centres and shifting regulatory frameworks could moderate long-term growth.

Both views have merit. Growth is likely to remain substantial, although volatility is inevitable in such rapid transformation cycles.

Core Engines of Growth and Competitive Moats

The pillar of Nvidia’s rise is performance leadership. Its GPUs dominate the market for training and inference of large AI models. Nvidia’s key products, including Hopper and Blackwell GPUs, remain far ahead in performance. Industry estimates put its data centre market share above 90%. This gap with other chip companies forces customers to “wait until supply arrives” for Nvidia chips.

Equally important is its software ecosystem. Compute Unified Device Architecture (CUDA), the parallel computing platform Nvidia began developing in 2006, has become the de facto environment for AI development. It supports millions of developers, and a wide array of research frameworks, enterprise applications, and industrial workflows are deeply tied into it. This makes the cost and complexity of shifting to alternative architectures high for most enterprises.

CUDA is widely considered Nvidia’s “biggest moat”, with customers locked in.

Finally, Nvidia’s product cadence supports its leadership. It continues to release new architectures at a rapid pace, keeping ahead of performance curves and sustaining a pipeline of demand even amid supply constraints. Its partnerships with major cloud providers and AI companies, such as OpenAI, ensure that its chips are available at scale; however, access remains competitive and capacity-constrained in many markets.

AI Infrastructure Expansion at Scale

Nvidia’s valuation aligns with another historic trend: one of the largest digital infrastructure build-outs. This is not a cyclical expansion but a structural shift toward a compute-first economic model.

The eight major global Cloud Service Providers—Google, AWS, Meta, Microsoft, Oracle, Tencent, Alibaba, and Baidu—are expected to spend over USD 420 billion in 2025, with the total projected to surpass USD 520 billion in 2026. Global AI infrastructure spending across data centres, chips, power systems, and cooling technologies could reach a massive USD 3–4 trillion by 2030.

The effect is that Nvidia’s growth feeds, and is in turn fed by, an AI “supercycle.”

Geopolitics and the Technology Balance of Power

Nvidia sits at the intersection of economic competition and geopolitical strategy. Advanced chips (and rare earths) are now viewed as strategic national assets to derive power balance gains. The US export approach to AI chips and semiconductor technology underscores this shift. China, which was once a major market for Nvidia’s highest-end GPUs, now receives tailored versions due to export controls, thereby accelerating domestic capabilities.

The US CHIPS Act, European industrial programs, China’s domestic semiconductor drive, and India Semiconductor Mission reflect a new mindset. Almost all of Nvidia’s top GPUs require US approval to ship abroad. The permission to export chips has shifted from the previous rule-based to a more discretionary model of technology governance, where countries must now demonstrate ongoing alignment with the current US administration. This creates uncertainties.

Nvidia’s strategy and growth now rely on these shifting geopolitical dynamics.

India’s Strategic Imperatives

For allied markets like India, this geopolitical dynamic presents constraints and yet strategic opportunities. The challenge is balancing access, capability building, and national goals for technology independence.

India’s AI ambitions are rising rapidly. Significant investments in digital infrastructure, such as Google’s USD 15 billion investment announcement, semiconductor capacity, and AI talent development have been initiated, but they dwarf in the face of massive investments by the US Big Techs. The government’s Semiconductor Mission has attracted interest from both foreign and domestic companies, including Foxconn, Micron, HCL, Tata, and Vedanta, in assembly and design. Indian IT providers are integrating generative AI into enterprise delivery. Start-ups are experimenting with language models and digital platforms for healthcare, education, and financial services. Telecom providers are embedding AI into networks and operations.

However, AI transformation depends on access to compute power. India remains heavily reliant on international semiconductor technology and global supply chains. While recent policy adjustments from the US have eased some barriers, predictable access to leading-edge computing remains a priority for Indian enterprises.

Nvidia is increasingly present in India’s ecosystem. It has deepened partnerships with major conglomerates (Reliance, Tata) to deploy AI data centres and has signed commitments with Indian data centres to supply GPUs and AI hardware. It has also joined the India Deep Tech Alliance as a founder member to mentor the emerging startups.

Yet India’s long-term opportunity lies in building domestic capability. India currently has no operational silicon foundry. Building domestic capabilities will require an enormous amount of time, which India can hardly afford.

For India, Nvidia’s rise reinforces a critical strategic message: compute capacity is now an essential national resource. The next phase will require sustained investment in semiconductor research and development (R&D), as well as partnerships for fabrication, power infrastructure, and digital policy clarity.

Nvidia’s journey to USD 5 trillion captures the growing interplay between technology, policy, and national strategy. For business and government leaders, the signal is clear. Nations and companies that secure access, develop talent, and build innovation ecosystems will shape the next chapter of global growth.

India stands at a critical inflexion point. Harnessing the AI wave requires continued focus on capability building, infrastructure scale-up, and strategic partnerships.

The author, Jaideep Ghosh, is a former Partner at KPMG in India.
(Views are personal.)