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Advancing the measurement of investments in artificial intelligence

Author

Listed:
  • François Fonteneau
  • Jeff Mollins
  • Sara Marchi
  • Lucia Russo
  • Angélina Gentaz
  • Melhem Daoud
  • Antoine-Alexandre André

Abstract

This working paper presents a methodology for estimating public and private artificial intelligence (AI) investments in European Union (EU) Member States, focusing on assets and capabilities. It categorises investments into four groups: skills, research and development, data and equipment, and other intellectual property products. Using publicly available national accounts and sector-specific sources, AI investments are estimated by applying AI intensity coefficients derived from patent data, academic programmes, and workforce statistics. The estimates highlight how AI investments are distributed across EU countries. The methodology also disaggregates investments in areas such as information and communication technologies, specialist remuneration, corporate training, software and databases, and telecommunications equipment. This work supports efforts to measure the evolving AI investment landscape in the EU.

Suggested Citation

  • François Fonteneau & Jeff Mollins & Sara Marchi & Lucia Russo & Angélina Gentaz & Melhem Daoud & Antoine-Alexandre André, 2025. "Advancing the measurement of investments in artificial intelligence," OECD Artificial Intelligence Papers 47, OECD Publishing.
    • Handle: RePEc:oec:comaaa:47-en
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    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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