| Title: | AI automation and technologies within industries across Europe : current size and expected growth |
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| Authors: | ID Grdović Gnip, Ana (Author) |
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| Files: |  RAZ_Grdovic_Gnip_Ana_2025.pdf (635,50 KB)
MD5: F3B6DE6D580792CCDC24EE384B383DF6
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| Language: | English |
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| Work type: | Unknown |
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| Typology: | 1.12 - Published Scientific Conference Contribution Abstract |
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| Organization: | FM - Faculty of Management
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| Abstract: | This paper examines the current landscape of artificial intelligence (AI) automation and technologies across various industries in Europe, utilizing descriptive statistics derived from Eurostat data. By analyzing the proportions of AI adoption within key sectors, the aim is to provide a comprehensive overview of the present state of AI integration in European industries. This is relevant from the perspective of its possible economic effects. The existing litareture that focuses on the effects of automation technologies on employment is rather inconsistent and inconclusive (Filippi et al, 2023). According to Bowles (2014) 54 % of European workers are at risk of substitution (by applying the occupation-based approach), while according to Pouliakas (2018) only 13.9 % of workers will face a risk higher than 70 % (by applying the task-based approach). Moreover, McGuinness et al 2021, show how 16 % of adult European workers have recently experienced a skills-displacing technological change, i.e., some changes in the use of technologies (e.g., machinery and ICT systems) in the last five years and thus concludes that several of their skills will become outdated in the next five years. Josten and Lordan (2020) predicted that by 47% of European jobs will be automatable (of which 35% are fully automatable), while 40% of them are not expected to be automated. Anyhow, the probability of automation varies considerably across industries. The service sector is generally less threatened by automation (Pajarinen et al, 2015), no matter the fact that wholesale and retail trade have a high probability of automation (Nedeloska and Quintini, 2018). Several studies conclude that (besides services) industries with a low probability of automation (lower than 40 %) include: education, health and social work, arts, sport and entertainment, management, business and finance, public administration and public utility services (Illessy et al, 2021, Yamashita nad Cummins, 2021; among others). Furthermore, this paper explores projected growth trajectories for AI usage, highlighting anticipated advancements and the potential for increased efficiency and innovation. Basically, an independent survey conducted in 2024 by the German Reichelt elektronics on the current status and potential of technologies (such as AI, ML, big data, robotics and IoT) and their use in European industrial companies shows that many European companies in the industrial sector (60%) believe that production will be fully automated in five years’ time. In addition, more than two thirds of the European industry (68%) consider automation to be essential in order to remain competitive. Therefore this paper also discusses the challenges and hurdles that may impede the widespread adoption of AI technologies, including regulatory, ethical, and infrastructural considerations, while seeking to understand the dynamics of AI implementation in Europe and its implications for future economic development. |
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| Keywords: | automation, AI technologies, productivity, Europe |
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| Year of publishing: | 2025 |
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| Number of pages: | Str. 217-218 |
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| PID: | 20.500.12556/RUP-21619  |
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| UDC: | 004.89 |
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| ISSN on article: | 2712-3766 |
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| DOI: | 10.26493/978-961-293-470-5 |
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| COBISS.SI-ID: | 246900995 |
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| Publication date in RUP: | 28.08.2025 |
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| Views: | 583 |
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| Downloads: | 8 |
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| Metadata: |    |
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