Oligopolization of the AI chip industry

In recent years, the rapid popularization of artificial intelligence has driven a sharp increase in demand for AI chips, ranging from cloud training, large model inference, to autonomous driving, robotics, and edge computing. Chips have become core infrastructure in a new round of industrial competition. However, what appears to be a flourishing AI revolution is actually pushing the market towards a highly concentrated oligopoly. Only a few companies can truly compete at this level, not just because of the extremely high technical difficulty, but also because the entire industry requires massive capital, long-term R&D, and deep control over critical supply chains. As computing power becomes part of national competitiveness and corporate survival, AI chips are no longer just products, but strategic assets that control the future order of the industry.

The AI chip industry is first and foremost an extremely capital-intensive field. Advanced chip design requires large R&D teams, highly complex hardware-software integration, and continuous iterative testing and verification processes. In the manufacturing phase, advanced processes rely on astronomical equipment costs, top-tier foundry capabilities, and mature packaging technologies. This means that even if a startup company has an innovative architecture, it may not have the resources to reach mass production. The capital threshold keeps most competitors out, naturally concentrating the market among a few financially strong enterprises.

A deeper obstacle lies in the technological barriers formed by patents and ecosystems. An AI chip cannot succeed on hardware alone; it must also be paired with compilers, development tools, software frameworks, drivers, and developer communities. Once leading companies establish a complete platform, customers find it difficult to switch because the cost of switching is extremely high—engineer training, model tuning, and system rebuilding all require significant re-investment. Patent protection combined with platform lock-in means that technological advantages are no longer just about being 'one step ahead' but instead about 'locking down the entire market.' As a result, even if latecomers introduce products with similar performance, they often struggle to shake the position of established giants.

The endgame of oligopolization is control over the supply chain

If technological leadership determines who gets the head start, then control over the supply chain truly decides who will have the last laugh. Today's competition in AI chips is no longer just about individual companies’ R&D races but rather about the ability to integrate entire supply chains. From advanced process foundries, HBM (High Bandwidth Memory), CoWoS (Chip-on-Wafer-on-Substrate) and other advanced packaging techniques, to servers, cooling systems, power supplies, and cloud deployment, every link can become a bottleneck. When key capacities are limited, companies that can secure capacity first, lock in supply, or even influence upstream and downstream configurations gain nearly monopolistic control over market discourse.

This also explains why the oligopoly in AI chips is not just a natural evolution of the market, but rather the result of three forces—technology, capital, and supply chain—working together. Giant companies expand their R&D lead with massive cash flows while incorporating key components and manufacturing resources into their own systems through long-term contracts, investments, partnerships, or even acquisitions. Over time, other companies may find it difficult to secure sufficient production capacity even if they have demand; even if they have products, they might not be able to enter the mainstream application market. This situation will make AI development increasingly reliant on a few platform providers, further deepening the concentration of power in the global tech industry.

From a broader perspective, the risks brought by the oligopoly in AI chips are not just about pricing and competition, but also involve industrial security and innovation vitality. When a few companies control the access to computing power, they can influence technological roadmaps, business rules, and even determine which countries and companies are capable of participating in the next wave of innovation. To avoid the AI ecosystem being completely dominated by a very small number of players in the future, policymakers need to focus not only on antitrust issues but also on how to enhance supply chain resilience, support alternative technology platforms, and cultivate more competitive design and manufacturing capabilities. Otherwise, the most critical infrastructure of the AI era may end up in the hands of a very few companies, thereby narrowing the scope for global innovation.

(Chip and Computing Power Series No. 38)

$Intel (INTC.US)$ $Advanced Micro Devices (AMD.US)$ $NVIDIA (NVDA.US)$ $MetaX Integrated Circuits (688802.SH)$

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