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Abstract

Economic activities based on the invention, production, and distribution of artificial intelligence (AI) technologies have recently emerged worldwide. Yet, little is known about the innovative activities, location, and growth performance of AI innovators. This chapter aims to map and analyze the global innovative landscape of AI by exploring 155,000 patents identified as AI-related by means of text-mining techniques. It highlights the emergence and evolution of AI technologies and identifies AI hotspots across the world. It explores the scale and pervasiveness of AI activities across sectors and evaluates the economic performance of AI innovators using firm accounting information. Finally, it assesses recent trends in venture capital investments towards AI as financial support to promising AI startups.

Findings of this chapter reveal a tremendous increase in AI patenting activities since 2013 with a significant boom in 2015–2016. While most of AI patenting activities remain concentrated in the sectors of software programming and manufacturing of electronic equipment and machinery, there are clear signs of cross-fertilization towards (nontech) sectors. The market of AI patenting firms is very vibrant and characterized by a large increase of new and small players with economic performances above industry average. This trend is also reflected by the recent increase in venture capital towards AI startups.

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Correspondence to Giacomo Damioli .

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Van Roy, V., Vertesy, D., Damioli, G. (2020). AI and Robotics Innovation. In: Zimmermann, K. (eds) Handbook of Labor, Human Resources and Population Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-57365-6_12-1

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  • DOI: https://doi.org/10.1007/978-3-319-57365-6_12-1

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  • Print ISBN: 978-3-319-57365-6

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Chapter history

  1. Latest

    AI and Robotics Innovation
    Published:
    12 February 2020

    DOI: https://doi.org/10.1007/978-3-319-57365-6_12-2

  2. Original

    AI and Robotics Innovation
    Published:
    14 January 2020

    DOI: https://doi.org/10.1007/978-3-319-57365-6_12-1