Intelligent Management and Artificial Intelligence: Trends, Challenges, and Opportunities, Vol.1

Proceedings on 28th European Conference on Artificial Intelligence ECAI 2025 – InMan Workshop

ISBN (online): 978-83-8419-028-9 OAI    DOI: 10.18276/978-83-8419-028-9-07
CC BY-SA   Open Access 

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ARTIFICIAL INTELLIGENCE IN THE EMPLOYMENT PROCESS IN HIGH-TECH COMPANIES IN EUROPEAN UNION REGIONS. CURRENT STATE OF KNOWLEDGE AND NEEDS FOR FURTHER RESEARCH

Autorzy: Aneta Sokół ORCID
University of Szczecin

Karolina Drela ORCID
University of Szczecin

Petr Hlaváček
University of Jan Evangelista in Usti nad Labem

Rafał Czyżycki ORCID
University of Szczecin
Słowa kluczowe: artificial intelligence regional development high-tech enterprises employment EU regions
Data publikacji całości:2025-10-02
Liczba stron:9 (87-95)
Klasyfikacja JEL: J01 E02
Cited-by (Crossref) ?:

Abstrakt

Purpose: This article aims to consider the cognitive, theoretical-methodological, and empirical issues surrounding the development of the percentage of people employed by high-tech companies and to establish the extent of the impact on the GDP of the countries studied, while also pointing to the significant potential for the positive impact of artificial intelligence. Need for the study: High-tech companies and their development lead to wisdom and create intellectual excellence in the regions where they develop. Artificial intelligence, which enriches the development of these actors with new tools not previously used and allows the acquisition of new digital competencies not previously used, has and will continue to significantly impact these development processes in the near future. Methodology: The empirical part presents the results of a survey conducted on a sample of 242 NUTS 2 regions of the EU. The study uses Pearson's correlation coefficient and presents the evolution of the coefficient value examining the impact of high tech on the development of GDP per capita (t=0) in individual EU regions. Findings: Furthermore, based on the analyses conducted, it can be clearly stated that the percentage of people employed in high-tech areas has a significant statistical impact on the shape of a region's GDP regardless of the time lag. However, detailed analysis shows that the strongest impact of the high-tech indicator on GDP occurs when a two-year lag is taken into account. Practical Implications: The resulting conclusions of the study provide knowledge to regional managers that their development and the development of high-tech companies are interrelated.
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