Analysis of the Adequacy of Employees Skills for the Adoption of Artificial Intelligence in Central and Eastern European Countries

Nicolae Istudor, Aura-Gabriela Socol (), Marius Marinas and Cristian Socol
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Nicolae Istudor: Bucharest University of Economic Studies, Romania
Aura-Gabriela Socol: Bucharest University of Economic Studies, Romania
Cristian Socol: Bucharest University of Economic Studies, Romania

The AMFITEATRU ECONOMIC journal, 2024, vol. 26, issue 67, 703

Abstract: The adoption of Artificial Intelligence (AI) technologies is reshaping the labour market, involving the enhancement of employees' digital skills and the acquisition of a mix of hard and soft skills. In this study, our objective was to identify, in an original way, the potential for adaptation to AI among company personnel in Central and Eastern European countries (CEE) based on four criteria and 17 analysis variables. Given the complexity of the research, we used three specific research methods for Multiple-criteria decision-making to identify the most important variables that influence rapid adaptation to AI and to classify the countries in the sample according to their level of performance. Based on the results obtained, we argue that any skills development strategy for AI should target upskilling and reskilling programmes aimed at developing above-average hard and soft skills. While increasing the number of graduates specialising in educational fields related to AI is essential in the new stage of the industrial revolution, the potential of this resource is under-utilised, both due to brain drain and slow technological progress, as well as the migration of technological start-ups. For larger countries, the development of technological enclaves to attract specialised human resources and technology companies is the only way to boost their technological revolution.

Keywords: Artificial Intelligence (AI); soft skills; hard skills; upskilling; reskilling; Multicriteria Decision Analysis (MCDM); Industry 5.0 (search for similar items in EconPapers)
JEL-codes: J24 M51 O15 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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