AI Watch: Adoption of Autonomous Machines

This report provides an empirical analysis of the drivers of and barriers to adoption of autonomous machines (AM) technologies by European companies. It also analyses the impact of adopting this technology on firm productivity. Using 2020 survey data from 9 640 firms located in EU27, Norway, Iceland...

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Main Authors: CARBALLA SMICHOWSKI Bruno, DE NIGRIS Sarah, DUCH BROWN Nestor, MORENO MARÍA Adrián
Language:English
Published: Publications Office of the European Union 2023
Subjects:
Online Access:https://publications.jrc.ec.europa.eu/repository/handle/JRC132723
https://doi.org/10.2760/459292
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spelling ftjrc:oai:publications.jrc.ec.europa.eu:JRC132723 2023-09-05T13:20:34+02:00 AI Watch: Adoption of Autonomous Machines CARBALLA SMICHOWSKI Bruno DE NIGRIS Sarah DUCH BROWN Nestor MORENO MARÍA Adrián 2023 Online https://publications.jrc.ec.europa.eu/repository/handle/JRC132723 https://doi.org/10.2760/459292 eng eng Publications Office of the European Union JRC132723 2023 ftjrc https://doi.org/10.2760/459292 2023-08-23T22:28:22Z This report provides an empirical analysis of the drivers of and barriers to adoption of autonomous machines (AM) technologies by European companies. It also analyses the impact of adopting this technology on firm productivity. Using 2020 survey data from 9 640 firms located in EU27, Norway, Iceland and the UK, we show that AM adoption is driven by several factors and has heterogeneous effects on companies depending on their characteristics. Regarding the drivers of adoption, we find that firm size, employee knowledge of artificial intelligence (AI) and the joint adoption of AM with complementary technologies increase a firm’s probability of adopting AM. Concerning barriers to adoption, we make three main findings. First, the most relevant barriers (cost of adoption and, to a lesser extent, lack of skills and data access) are different for large firms. For the latter, liability and reputation risks, as well as data access, are the most important obstacles. Second, certain types of obstacles (namely liability and reputation risks, data access and lack of funding) are more likely to be present in certain sectors of activity. Third, the more complementary technologies a firm adopts, the lower its probability of facing obstacles to AM adoption. Finally, we find that AM adoption boosts firm productivity. This effect is higher for firms that start out with lower productivity, which suggests that there is a decreasing marginal return to AM adoption in terms of productivity. JRC.T.1 - Digital Economy Other/Unknown Material Iceland Joint Research Centre, European Commission: JRC Publications Repository Norway
institution Open Polar
collection Joint Research Centre, European Commission: JRC Publications Repository
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language English
description This report provides an empirical analysis of the drivers of and barriers to adoption of autonomous machines (AM) technologies by European companies. It also analyses the impact of adopting this technology on firm productivity. Using 2020 survey data from 9 640 firms located in EU27, Norway, Iceland and the UK, we show that AM adoption is driven by several factors and has heterogeneous effects on companies depending on their characteristics. Regarding the drivers of adoption, we find that firm size, employee knowledge of artificial intelligence (AI) and the joint adoption of AM with complementary technologies increase a firm’s probability of adopting AM. Concerning barriers to adoption, we make three main findings. First, the most relevant barriers (cost of adoption and, to a lesser extent, lack of skills and data access) are different for large firms. For the latter, liability and reputation risks, as well as data access, are the most important obstacles. Second, certain types of obstacles (namely liability and reputation risks, data access and lack of funding) are more likely to be present in certain sectors of activity. Third, the more complementary technologies a firm adopts, the lower its probability of facing obstacles to AM adoption. Finally, we find that AM adoption boosts firm productivity. This effect is higher for firms that start out with lower productivity, which suggests that there is a decreasing marginal return to AM adoption in terms of productivity. JRC.T.1 - Digital Economy
author CARBALLA SMICHOWSKI Bruno
DE NIGRIS Sarah
DUCH BROWN Nestor
MORENO MARÍA Adrián
spellingShingle CARBALLA SMICHOWSKI Bruno
DE NIGRIS Sarah
DUCH BROWN Nestor
MORENO MARÍA Adrián
AI Watch: Adoption of Autonomous Machines
author_facet CARBALLA SMICHOWSKI Bruno
DE NIGRIS Sarah
DUCH BROWN Nestor
MORENO MARÍA Adrián
author_sort CARBALLA SMICHOWSKI Bruno
title AI Watch: Adoption of Autonomous Machines
title_short AI Watch: Adoption of Autonomous Machines
title_full AI Watch: Adoption of Autonomous Machines
title_fullStr AI Watch: Adoption of Autonomous Machines
title_full_unstemmed AI Watch: Adoption of Autonomous Machines
title_sort ai watch: adoption of autonomous machines
publisher Publications Office of the European Union
publishDate 2023
url https://publications.jrc.ec.europa.eu/repository/handle/JRC132723
https://doi.org/10.2760/459292
geographic Norway
geographic_facet Norway
genre Iceland
genre_facet Iceland
op_relation JRC132723
op_doi https://doi.org/10.2760/459292
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