人工智能供应链中的全球巨头

Global giants in the AI supply chain Jon Frost, Kumar Rishabh and Vatsala Shreeti February 2026 BIS Bulletins are written by staff members of the Bank for International Settlements, and from time to timeby other economists, and are published by the Bank. The papers are on subjects of topical interest and aretechnical in character. The views expressed in them are those of their authors and not necessarily the viewsof the BIS. The authors are grateful to Iñaki Aldasoro, Pablo Hernández de Cos and Christian Upper forcomments, to Rudraksh Kansal, Adam Cap and Ilaria Mattei for research assistance, to Alison Arnot foreditorial review and to Nicola Faessler, Danielle Ritzema and Maja Viscek for administrative support. The editor of the BIS Bulletin series is Hyun Song Shin. This publication is available on the BIS website (www.bis.org). ©Bank for International Settlements 2026. All rights reserved. Brief excerpts may be reproduced ortranslated provided the source is stated. Global giants in the AI supply chain Key takeaways •Globally, the largest artificial intelligence (AI) firms are based in the United States, China, Chinese Taipei,Korea and the Netherlands.•These global AI giants account for an increasing share of total market capitalisation, capital expenditureand revenues in their respective jurisdictions.•For many AI giants – and particularly those from the United States and China – scope and scale gotogether as they expand the breadth of their activities into multiple layers in the AI supply chain. The promise of artificial intelligence (AI) hinges on the firms that build, operate and provide AI productsand services.1But AI is not provided through a single market. It rests on a supply chain made up of at leastfive layers: computing power (“compute”), infrastructure, data tools, models and applications (Gambacortaand Shreeti (2025)). Building the layers requires large upfront investment, but unit costs can fall as thescale grows. The economics of AI can also reward integration across different layers, as costs can fall whenfirms operate in different markets and benefit from complementarities. Taken together, these economies of scale and scope can favour the emergence of large AI firms. Evenamong the largest AI firms globally, only a few have combined the resources to invest heavily and thebreadth to operate across multiple layers of the supply chain. As AI use diffuses across sectors, these firmsare gaining macroeconomic heft in the global economy. In the last two decades, they have been steadilyinvesting and spending more on research and development (R&D) and, recently, on data centres andinformation technology (IT) manufacturing (Aldasoro et al (2026)). They are now in a position to set thepace of aggregate investment, the direction of R&D, the terms on which others access critical inputs andthe direction of innovation. When giants move, the ground can move with them. In this way, the decisionsof a handful of AI firms can have a significant impact on a range of macroeconomic outcomes. The global AI landscape: scale and breadth AI products and services are provided through a complex supply chain. At the base is computing poweror specialised hardware, most notably microprocessors and high bandwidth memory chips, designed tohandle the intensive computations required for training of and inference from AI models. Above this sitsthe infrastructure, including data centres and cloud services, to build, store and operate AI models. Thenext input layer is training data and data tools. These comprise vast, multimodal data sets spanning text, images, audio and video, sourced from both public and proprietary repositories. Computing power, cloudinfrastructure and data feed into the next layer – the market for foundation models. These are large, pre-trained AI models that can be adapted to a wide range of tasks. Finally, the top layer of the supply chainconsists of user-facing AI applications that leverage these models for specific uses. Firms that provide AI products and services are currently among the world’s most valuable companies.Graph 1 maps the top 20 AI firms worldwide (global AI giants) by supply chain presence and market value,based on Rishabh and Shreeti (2026a). Graph 1.A shows the breadth of their activities, measured by thenumber of layers of the AI supply chain the firm is active in. A firm can be active in a particular layer of thesupply chain either by selling products and services to others or by building them for internal use.Graph 1.B shows these firms’ valuations, as measured by market capitalisation at the end of 2025. Four patterns stand out. First, among the top 20 global AI firms, the top seven are all publicly listedfirms based in the United States (US). Together they account for more than twice the market value of thenext 13 AI firms. Second, many firms with a big presence in AI have a broad span of activities. This isparticularly true for US-based AI giants (Nvidia, Apple, Al