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TES analysis of AI Worldwide Ecosystem in 2009-2018

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Abstract

This report analyses and compares countries and regions in the evolving international industrial and research landscape of Artificial Intelligence (AI). The evidence presented is based on a unique database covering the years 2009-2018. The database has been specifically built from a multitude of sources to provide scientific evidence and monitor the AI landscape worldwide. Companies, universities, research institutes and governmental authorities with an active role in AI are identified and analysed in an aggregated fashion. The report presents a wide variety of indicators, allowing us to expand our knowledge on issues such as: the size of the AI ecosystem globally and at country level; which are the main global competitors of the EU; what is the level of industrial involvement per country; what are the firms’ demographics, profiling of economic agents according to their strengths in innovation and take-up of AI, including their patenting performance; and the degree of internal and external collaborations between EU and non-EU firms and research institutions. The analysis of the AI activities developed by agents in the studied territories provides interesting insights on their areas of specialisation, highlighting the strengths of the EU and its Member States in the global landscape. Each section offers a focus on EU Member States.

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  • Sofia Samoili & Riccardo Righi & Melisande Cardona & Montserrat Lopez-Cobo & Miguel Vazquez-Prada Baillet & Giuditta De-Prato, 2020. "TES analysis of AI Worldwide Ecosystem in 2009-2018," JRC Research Reports JRC120106, Joint Research Centre.
    • Handle: RePEc:ipt:iptwpa:jrc120106
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    1. Sebnem Kalemli-Ozcan & Bent Sorensen & Carolina Villegas-Sanchez & Vadym Volosovych & Sevcan Yesiltas, 2015. "How to Construct Nationally Representative Firm Level Data from the Orbis Global Database: New Facts and Aggregate Implications," NBER Working Papers 21558, National Bureau of Economic Research, Inc.
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    5. Sørensen, Bent E & Kalemli-Özcan, Sebnem & Volosovych, Vadym & Villegas-Sanchez, Carolina & Yesiltas, Sevcan, 2015. "How to construct nationally representative firm level data from the ORBIS global database," CEPR Discussion Papers 10829, C.E.P.R. Discussion Papers.
    6. Miguel Seabra, 2014. "Portugal's research funding is secure," Nature, Nature, vol. 507(7492), pages 306-306, March.
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    Cited by:

    1. Sofia Samoili & Montserrat Lopez Cobo & Emilia Gomez & Giuditta De Prato & Fernando Martinez-Plumed & Blagoj Delipetrev, 2020. "AI Watch. Defining Artificial Intelligence. Towards an operational definition and taxonomy of artificial intelligence," JRC Research Reports JRC118163, Joint Research Centre.
    2. Riccardo Righi & Montserrat Lopez-Cobo & Georgios Alaveras & Sofia Samoili & Melisande Cardona & Miguel Vazquez-Prada Baillet & Lukasz Ziemba & Giuditta De-Prato, 2020. "Academic Offer of Advanced Digital Skills in 2019-20. International Comparison. Focus on Artificial Intelligence, High Performance Computing, Cybersecurity and Data Science," JRC Research Reports JRC121680, Joint Research Centre.
    3. DE NIGRIS Sarah & CRAGLIA Massimo & NEPELSKI Daniel & HRADEC Jiri & GOMEZ-GONZALES Emilio & GOMEZ GUTIERREZ Emilia & VAZQUEZ-PRADA BAILLET Miguel & RIGHI Riccardo & DE PRATO Giuditta & LOPEZ COBO Mont, 2020. "AI Watch : AI Uptake in Health and Healthcare, 2020," JRC Research Reports JRC122675, Joint Research Centre.

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    Keywords

    artificial intelligence; techno-economic analysis; digital transformation; AI landscape; AI thematic area; network of collaborations; AI industry;
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