IDEAS home Printed from https://ideas.repec.org/b/bis/bisbps/154.html

The AI supply chain

Author

Listed:
  • Leonardo Gambacorta
  • Vatsala Shreeti

Abstract

The rapid advancement of artificial intelligence (AI) relies on a complex supply chain comprising five key layers: hardware, cloud infrastructure, training data, foundation models and AI applications. This paper examines the market structure of each layer and highlights the economic forces shaping them: rapid technological change, high fixed costs, economies of scale, network effects and, in some cases, strategic behaviour by dominant firms. We also highlight the expanding influence of big tech companies across the AI supply chain. We discuss the challenges for consumer choice, innovation, operational resilience, cyber security and financial stability.

Suggested Citation

  • Leonardo Gambacorta & Vatsala Shreeti, 2025. "The AI supply chain," BIS Papers, Bank for International Settlements, number 154.
    • Handle: RePEc:bis:bisbps:154
    as

    Download full text from publisher

    File URL: http://www.bis.org/publ/bppdf/bispap154.pdf
    File Function: Full PDF document
    Download Restriction: no
    File URL: http://www.bis.org/publ/bppdf/bispap154.htm
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Stephanie Assad & Robert Clark & Daniel Ershov & Lei Xu, 2024. "Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market," Journal of Political Economy, University of Chicago Press, vol. 132(3), pages 723-771.
    2. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2020. "Artificial Intelligence, Algorithmic Pricing, and Collusion," American Economic Review, American Economic Association, vol. 110(10), pages 3267-3297, October.
    3. Andrei Hagiu & Julian Wright, 2023. "Data‐enabled learning, network effects, and competitive advantage," RAND Journal of Economics, RAND Corporation, vol. 54(4), pages 638-667, December.
    4. Aldasoro, I. & Gambacorta, L. & Korinek, A. & Shreeti, V. & Stein, M., 2025. "Intelligent financial system: How AI is transforming finance," Journal of Financial Stability, Elsevier, vol. 81(C).
    5. Schaefer, Maximilian & Sapi, Geza, 2023. "Complementarities in learning from data: Insights from general search," Information Economics and Policy, Elsevier, vol. 65(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Aldasoro, I. & Gambacorta, L. & Korinek, A. & Shreeti, V. & Stein, M., 2025. "Intelligent financial system: How AI is transforming finance," Journal of Financial Stability, Elsevier, vol. 81(C).
    2. Danielsson, Jon & Uthemann, Andreas, 2025. "Artificial intelligence and financial crises," Journal of Financial Stability, Elsevier, vol. 80(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hagiu, Andrei & Wright, Julian, 2025. "Artificial intelligence and competition policy," International Journal of Industrial Organization, Elsevier, vol. 103(PA).
    2. Shengyu Cao & Ming Hu, 2026. "Collusive Pricing Under LLM," Papers 2601.01279, arXiv.org, revised Mar 2026.
    3. Frédéric Marty & Thierry Warin, 2025. "Algorithmic Pricing and Competition: Balancing Efficiency and Consumer Welfare," Working Papers halshs-05199988, HAL.
    4. Hemant Bhargava & Antoine Dubus & David Ronayne & Shiva Shekhar, 2026. "The Strategic Value of Data Sharing in Interdependent Markets," Management Science, INFORMS, vol. 72(2), pages 1472-1488, February.
    5. Daniel Garcia & Juha Tolvanen & Alexander K. Wagner, 2026. "Strategic Responses to Algorithmic Recommendations: Evidence from Hotel Pricing," Management Science, INFORMS, vol. 72(1), pages 609-626, January.
    6. Danielsson, Jon & Uthemann, Andreas, 2025. "Artificial intelligence and financial crises," Journal of Financial Stability, Elsevier, vol. 80(C).
    7. Hangcheng Zhao & Ron Berman, 2025. "Algorithmic Collusion of Pricing and Advertising on E-commerce Platforms," Papers 2508.08325, arXiv.org, revised Oct 2025.
    8. Eshwar Ram Arunachaleswaran & Natalie Collina & Sampath Kannan & Aaron Roth & Juba Ziani, 2024. "Algorithmic Collusion Without Threats," Papers 2409.03956, arXiv.org, revised Dec 2024.
    9. Abada, Ibrahim & Lambin, Xavier & Tchakarov, Nikolay, 2024. "Collusion by mistake: Does algorithmic sophistication drive supra-competitive profits?," European Journal of Operational Research, Elsevier, vol. 318(3), pages 927-953.
    10. Aldasoro, I. & Gambacorta, L. & Korinek, A. & Shreeti, V. & Stein, M., 2025. "Intelligent financial system: How AI is transforming finance," Journal of Financial Stability, Elsevier, vol. 81(C).
    11. Enoch Hyunwook Kang, 2026. "Reasonably reasoning AI agents can avoid game-theoretic failures in zero-shot, provably," Papers 2603.18563, arXiv.org, revised Apr 2026.
    12. Jon Danielsson & Andreas Uthemann, 2024. "Artificial intelligence and financial crises," Papers 2407.17048, arXiv.org, revised Jul 2025.
    13. Lambin, Xavier & Raizonville, Adrien, 2025. "From black box to glass box: algorithmic explainability as a strategic decision," Information Economics and Policy, Elsevier, vol. 71(C).
    14. Gillian K. Hadfield & Andrew Koh, 2025. "An Economy of AI Agents," Papers 2509.01063, arXiv.org.
    15. Liying Qiu & Yan Huang & Param Vir Singh & Kannan Srinivasan, 2025. "Personalization, Consumer Search, and Algorithmic Pricing," Marketing Science, INFORMS, vol. 44(6), pages 1278-1298, November.
    16. Giacomo Calzolari & Anatole Cheysson & Riccardo Rovatti, 2025. "Machine Data: Market and Analytics," Management Science, INFORMS, vol. 71(10), pages 8230-8251, October.
    17. Bruno Carballa Smichowski & Yassine Lefouili & Andrea Mantovani & Carlo Reggiani, 2025. "Data Sharing or Analytics Sharing ?," Working Papers hal-04956937, HAL.
    18. Maximilian Schaefer, 2025. "When Should we Expect Non-Decreasing Returns from Data in Prediction Tasks?," Papers 2503.03602, arXiv.org.
    19. Youngjin Yoo & Ola Henfridsson & Jannis Kallinikos & Robert Gregory & Gordon Burtch & Sutirtha Chatterjee & Suprateek Sarker, 2024. "The Next Frontiers of Digital Innovation Research," Information Systems Research, INFORMS, vol. 35(4), pages 1507-1523, December.
    20. Carballa-Smichowski, Bruno & Duch-Brown, Néstor & Höcük, Seyit & Kumar, Pradeep & Martens, Bertin & Mulder, Joris & Prüfer, Patricia, 2025. "Economies of scope in data aggregation: Evidence from health data," Information Economics and Policy, Elsevier, vol. 71(C).

    More about this item

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bis:bisbps:154. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Martin Fessler (email available below). General contact details of provider: https://edirc.repec.org/data/bisssch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.