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Mapping technological innovation dynamics in artificial intelligence domains: Evidence from a global patent analysis

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  • Na Liu
  • Philip Shapira
  • Xiaoxu Yue
  • Jiancheng Guan

Abstract

Artificial intelligence (AI) is emerging as a technology at the center of many political, economic, and societal debates. This paper formulates a new AI patent search strategy and applies this to provide a landscape analysis of AI innovation dynamics and technology evolution. The paper uses patent analyses, network analyses, and source path link count algorithms to examine AI spatial and temporal trends, cooperation features, cross-organization knowledge flow and technological routes. Results indicate a growing yet concentrated, non-collaborative and multi-path development and protection profile for AI patenting, with cross-organization knowledge flows based mainly on interorganizational knowledge citation links.

Suggested Citation

  • Na Liu & Philip Shapira & Xiaoxu Yue & Jiancheng Guan, 2021. "Mapping technological innovation dynamics in artificial intelligence domains: Evidence from a global patent analysis," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-20, December.
    • Handle: RePEc:plo:pone00:0262050
    DOI: 10.1371/journal.pone.0262050
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    References listed on IDEAS

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    Cited by:

    1. Podrecca, Matteo & Culot, Giovanna & Tavassoli, Sam & Orzes, Guido, 2024. "Artificial intelligence for climate change: a patent analysis in the manufacturing sector," Papers in Innovation Studies 2024/12, Lund University, CIRCLE - Centre for Innovation Research.
    2. Jaehyuk Park, 2024. "Analyzing the direct role of governmental organizations in artificial intelligence innovation," The Journal of Technology Transfer, Springer, vol. 49(2), pages 437-465, April.

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