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The "Gold Rush" in AI and Robotics Patenting Activity. Do innovation systems have a role?

Giovanni Guidetti, Riccardo Leoncini, Mariele Macaluso

TL;DR

A novel distinction between traditional robotics and robotics embedding AI functionalities is introduced, using patent data and a time-series econometric approach to examine whether these domains share common long-run dynamics and how their trajectories differ across major innovation systems.

Abstract

This paper studies patenting trends in artificial intelligence (AI) and robotics from 1980 to 2019. We introduce a novel distinction between traditional robotics and robotics embedding AI functionalities. Using patent data and a time-series econometric approach, we examine whether these domains share common long-run dynamics and how their trajectories differ across major innovation systems. Three main findings emerge. First, patenting activity in core AI, traditional robots, and AI-enhanced robots follows distinct trajectories, with AI-enhanced robotics accelerating sharply from the early 2010s. Second, structural breaks occur predominantly after 2010, indicating an acceleration in the technological dynamics associated with AI diffusion. Third, long-run relationships between AI and robotics vary systematically across countries: China exhibits strong integration between core AI and AI-enhanced robots, alongside a substantial contribution from universities and the public sector, whereas the United States displays a more market-oriented patenting structure and weaker integration between AI and robots. Europe, Japan, and South Korea show intermediate patterns.

The "Gold Rush" in AI and Robotics Patenting Activity. Do innovation systems have a role?

TL;DR

A novel distinction between traditional robotics and robotics embedding AI functionalities is introduced, using patent data and a time-series econometric approach to examine whether these domains share common long-run dynamics and how their trajectories differ across major innovation systems.

Abstract

This paper studies patenting trends in artificial intelligence (AI) and robotics from 1980 to 2019. We introduce a novel distinction between traditional robotics and robotics embedding AI functionalities. Using patent data and a time-series econometric approach, we examine whether these domains share common long-run dynamics and how their trajectories differ across major innovation systems. Three main findings emerge. First, patenting activity in core AI, traditional robots, and AI-enhanced robots follows distinct trajectories, with AI-enhanced robotics accelerating sharply from the early 2010s. Second, structural breaks occur predominantly after 2010, indicating an acceleration in the technological dynamics associated with AI diffusion. Third, long-run relationships between AI and robotics vary systematically across countries: China exhibits strong integration between core AI and AI-enhanced robots, alongside a substantial contribution from universities and the public sector, whereas the United States displays a more market-oriented patenting structure and weaker integration between AI and robots. Europe, Japan, and South Korea show intermediate patterns.
Paper Structure (15 sections, 2 equations, 10 figures, 11 tables)

This paper contains 15 sections, 2 equations, 10 figures, 11 tables.

Table of Contents

  1. Introduction
  2. Conceptual Framework
  3. Data Source and Empirical Strategy
  4. Data Collection
  5. Data Construction and Final Dataset
  6. Descriptive Statistics
  7. Empirical strategy
  8. Stationarity Analysis, Structural Breaks and the Short-Run Dynamics of Time Series
  9. Cointegration analysis
  10. Empirical Results
  11. Stationarity Analysis
  12. Structural Breaks
  13. Cointegration Analysis
  14. Discussion of Empirical Findings
  15. Conclusion

Figures (10)

  • Figure 1: Distribution of AI-related Keywords in Patent Titles, by Technological Domain
  • Figure 2: Distribution of AI-related Keywords in Patent Abstracts, by Technological Domain
  • Figure 3: Total Number of Patent Families by Filing Year
  • Figure 4: Evolution of Patent Stocks by CPC Section
  • Figure 5: Robot-Related Patent Families by Filing Year
  • ...and 5 more figures