Nvidia is a global leader in accelerated computing and AI hardware.
Renowned for its graphics processing units (GPUs), Nvidia has helped transform industries, powering everything from cutting-edge gaming and lifelike visual experiences to high-performance computing and the rapid advancement of generative AI.
Go deeper with GlobalData
Access deeper industry intelligence
Experience unmatched clarity with a single platform that combines unique data, AI, and human expertise.
GlobalData estimates that the total AI market will be valued at $642bn in 2029, having grown from $131bn in 2024 at a compound annual growth rate of 37%. The generative AI segment is forecast to record a CAGR of 93% over the same period. As spending on generative AI increases, so will the demand for efficient training and inference chips. Nvidia has thus far cornered the AI chip market, but its forerunner position is at risk of being weakened.
How Nvidia’s long-term investment paid off
Founded in 1993, Nvidia started as a GPU designer for video games and 3D graphics. GPUs can run thousands of calculations in parallel, resulting in smooth and efficient image rendering. Nvidia carefully crafted a whole ecosystem around its chips, including CUDA, a software platform created in 2006 that allowed developers to program GPUs for applications beyond just graphics. This created a strong network of developers, scientists, and researchers.
The rise of generative AI since the launch of ChatGPT in November 2022 has turbocharged Nvidia’s growth and influence. As demand for advanced AI capabilities skyrocketed, Nvidia’s powerful GPUs became essential for training large language models (LLMs), a process that benefits enormously from parallel computation. The surge in AI adoption has fueled record revenues for Nvidia and cemented its monopoly on AI chip design.
Nvidia currently possesses nearly 90% market share in AI chip design, and in 2024, it reported annual revenue of $61bn, up 126% from the previous year. Meanwhile, the company’s stock price has risen more than 1,400% over the past five years. In October 2025, it became the first public company valued at $5trn, having become the first to pass the $4trn milestone just three months earlier.
US Tariffs are shifting - will you react or anticipate?
Don’t let policy changes catch you off guard. Stay proactive with real-time data and expert analysis.
By GlobalDataNvidia’s crown is askew
Despite successfully riding the generative AI tidal wave thus far, Nvidia now faces threats from competitors. OpenAI, which has been almost wholly dependent on Nvidia GPUs, has diversified its supply, making multibillion-dollar deals with Broadcom and AMD in October 2025. Diversifying its supply of chips is an astute move by OpenAI, forcing market competition that will ultimately lower chip prices and incentivise new and competitive chip designs.
OpenAI is purchasing 10 gigawatts (GW) of custom AI accelerators from Broadcom and 6GW of GPU capacity from AMD. To put the enormous scale into context, 10GW is equivalent to approximately 10 million GPUs. Assuming a conservative $30,000 per GPU, that translates to $300bn in GPU chip sales. The deals have boosted the share prices of both Broadcom and AMD.
In the final days of October 2025, another competitor entered the fray.
Qualcomm announced the launch of its own AI chips; the AI200 series will be released in 2026, and the AI250 in 2027. These chips will be especially designed for inferencing tasks as opposed to training. Until now, Qualcomm has concentrated its chip efforts on the smartphone, laptop, and tablet markets. This move towards the AI chip market marks a strategic shift from its core business and adds another pressure point for Nvidia.
Limited number of top customers exposes weak links
Despite its staggering revenue growth, Nvidia’s monopoly is built on shaky ground. Of its total revenue, nearly 50% comes from just four customers and 85% from just six companies. Nvidia does not disclose the names of its largest customers, but they are likely to include Amazon, Google, Meta, and Microsoft.
With large sums of revenue dependent on so few buyers, shifts in market dynamics can have rapid consequences. Should leading customers diversify their chip supply to the likes of Broadcom, AMD, and Qualcomm and reduce reliance on Nvidia, the chip designer will find itself in a vulnerable position.
Nvidia has already had its customer base slashed following US restrictions on its sales to China, a once very lucrative market. The extent of US restrictions on Nvidia has ebbed and flowed, with certain exceptions being made to permit the sale of less advanced chips to China. Nevertheless, China is now refusing the import of all Nvidia chips as a means of encouraging self-reliance and home-grown alternatives. In October 2025, Nvidia reported that revenue from the Chinese market had fallen to zero. Historically, China accounted for approximately one-fifth of Nvidia’s revenues.
The fight back
To maintain its position, Nvidia must build stronger links with its customers. It has already announced significant investments in OpenAI and Nokia, valued at $100bn and $1bn, respectively. These investments are intended to be circular, prompting these companies to purchase Nvidia chips to run their infrastructure.
Nvidia has also invested in CoreWeave, having reportedly purchased over 24 million shares in the AI-specialised cloud computing company. Coreweave is another important customer, running much of its cloud infrastructure on Nvidia GPUs.
Beyond AI, Nvidia is extending into the quantum computing market. Although it is not developing its own quantum computers, Nvidia has partnered with several quantum computing hardware companies such as Infleqtion, IonQ, PsiQuantum, Quantinuum, and Rigetti. Nvidia is developing auxiliary products such as CUDA-Q, a programming platform enabling the development of hybrid classical-quantum applications.
On October 28, 2025, Nvidia revealed NVQLink, an interconnect designed to directly link and permit high-speed data transfers between quantum chips and GPU-accelerated supercomputers. Enabling the two to communicate with each other instantaneously is expected to remove a longstanding barrier to running large hybrid algorithms that rely on fast feedback between quantum and classical computers.
The launch of NVQLink will also hasten the convergence of quantum computing and AI by permitting AI processors to control and optimise quantum systems in real-time. These developments will not be revenue-generators for Nvidia in the near term, but will provide security as it attempts to gain a firm foothold in emerging tech markets.
