Company in the spotlight – the rise and rise of Nvidia

On Tuesday, Nvidia once again overtook Microsoft to become the world's most valuable listed company, with the artificial intelligence (AI) chipmaker's market capitalisation of $3.444 trillion eclipsing the software giant's $3.441 trillion valuation.

In the span of three decades, Nvidia has evolved from a niche graphics card manufacturer into one of the most influential technology companies in the world. Nvidia is not only a cornerstone of the gaming industry but also the undisputed leader in AI hardware and software.

Its rise is a story of visionary leadership, relentless innovation, and strategic positioning at the heart of the AI revolution. Nvidia’s success is not just about having an excellent product, it’s about the deployment of this product into an evolving ecosystem that keep its customers locked in.

A brief history

Founded in 1993 by Jensen Huang, Chris Malachowsky and Curtis Priem, Nvidia initially focused on producing graphics processing units (GPUs) for the burgeoning PC gaming market. Its breakthrough came in 1999 with the launch of the GeForce 256, which it dubbed the world’s first GPU. This innovation revolutionised 3D graphics and set the stage for Nvidia’s dominance in gaming.

Over the next two decades, Nvidia expanded its reach into professional visualisation, automotive computing, and high-performance computing. The real turning point came in the 2010s, when researchers discovered that GPUs were ideally suited for training deep-learning models. Nvidia capitalised on this by investing heavily in AI infrastructure, launching its CUDA programming platform, and acquiring key assets such as Mellanox Technologies. By the early 2020s, Nvidia had become the backbone of the AI boom.

The competitive edge

Nvidia’s dominance is not just about powerful chips – It’s about the synergy between hardware, software, and ecosystem. At the hardware level, Nvidia’s GPUs, such as the H100 and A100, are the gold standard for AI training and inference. These chips offer unmatched performance, scalability, and energy efficiency, making them the preferred choice for data centres, research labs, and cloud providers.

But what truly sets Nvidia apart is its software. The CUDA platform, launched in 2006, allows developers to write code that fully exploits the parallel processing power of GPUs. This has created a massive developer ecosystem and a high switching cost for competitors. Complementing CUDA are libraries such as cuDNN for deep learning, TensorRT for inference optimisation, and the Omniverse platform for 3D simulation and collaboration.

Nvidia’s ecosystem strategy extends to partnerships with cloud providers, universities, and enterprises. Its DGX systems, which bundle hardware and software into turnkey AI solutions, are widely used in scientific research and enterprise AI deployments. This vertical integration gives Nvidia a moat that few competitors can cross. This has led to a commanding market share across its core segments of AI, gaming, and data centres, thanks to its relentless innovation and ecosystem lock-in.

Nvidia now controls an estimated 90% of the AI chip market. Its GPUs are used in nearly every major AI model, from OpenAI’s GPT series to Google DeepMind’s AlphaFold. In gaming, Nvidia continues to dominate with its GeForce line, although competition from AMD has intensified. In professional visualisation and automotive computing, Nvidia maintains a strong presence, particularly through its DRIVE platform for autonomous vehicles.

Threats to dominance

Nvidia's first-quarter 2025 results showcased its continued dominance in AI and data centre computing. The company reported $44.1bn in revenue, marking a 69% year-over-year increase. The data centre segment was the standout performer, generating $39.1bn, a 73% jump from the previous year. However, despite its commanding position, Nvidia faces several emerging threats that could challenge its dominance in the years ahead.

• Geopolitical tensions and export restrictions. US government restrictions on exporting advanced chips to China have already impacted Nvidia’s ability to serve one of its largest markets. These policies could tighten further, forcing the company to redesign products and potentially lose market share to domestic Chinese competitors.
• Custom silicon from tech giants. Companies such as Google, Amazon, and Microsoft are increasingly developing their own AI chips to reduce reliance on Nvidia. While these custom ASICs are often tailored for specific workloads, they pose a long-term threat to Nvidia’s dominance in cloud AI infrastructure.
• Rising competition from AMD and Intel. AMD’s MI300 series and Intel’s Gaudi chips are gaining traction, particularly in price-sensitive markets. While they have yet to match Nvidia’s ecosystem, they are closing the performance gap and could erode market share over time.
• Market saturation and AI investment slowdown. There are concerns that the AI boom may plateau by 2026, especially if enterprise adoption slows or regulatory scrutiny increases. A slowdown in AI infrastructure spending could impact the company’s growth trajectory, particularly in the key data centre segment.
• Software ecosystem fragmentation. While CUDA remains dominant, open-source alternatives such as AMD’s ROCm and Intel’s oneAPI are gaining traction. If developers begin to shift away from CUDA, NVIDIA’s software moat could weaken.

Tech companies have faced various restrictions over the years, often driven by concerns over competition, national security, and data privacy. There are several key risks that apply to the wider technology industry. These include:

• Antitrust crackdowns: regulators have targeted Apple, Google, Amazon, and Meta for alleged monopolistic practices.
• Data localisation laws: countries such as India and China have imposed strict rules requiring foreign technology companies to store user data within national borders.
• Export controls: the US has previously restricted Huawei from accessing American semiconductor technology, citing national security concerns.
• Digital taxation: governments have introduced digital taxes on technology giants to ensure they contribute fairly to local economies.

• Supply chain vulnerabilities: geopolitical tensions and semiconductor shortages could disrupt production and delivery.
• Technology disruption: emerging technologies such as quantum computing might shift demand away from traditional GPUs.

A titan at the peak of its power

Nvidia’s rise is one of the most remarkable success stories in modern technology. Its success has been down to the fact that it has consistently stayed ahead of the curve through innovation, strategic foresight, and ecosystem control.

Yet, as it stands at the pinnacle of the tech world, Nvidia must navigate a complex landscape of geopolitical risks, rising competition and shifting market dynamics. Whether it can maintain its dominance will depend on its ability to adapt, diversify, and continue to deliver transformative technologies.

This article is not advice or a recommendation to buy, sell or hold any investment. No view is given on the present or future value or price of any investment, and investors should form their own view on any proposed investment.