The Necessary Skillset Based on the Use of Artificial Intelligence in Czech Top Organisations

Zdeněk Kronberger (1), Lucie Depoo (2), Gabriela Říhová (3)
(1) University of Economics and Business, Czechia,
(2) University of Economics and Business, Czechia,
(3) University of Economics and Business, Czechia

Abstract

Purpose: The rapid advancement of artificial intelligence (AI), is transforming the required skills in the workforce. This article presents research findings from large organisations that have adopted AI.


Methodology/Approach: The aim is to identify the skills driven by the utilisation of AI. The paper pinpoints the key skills for effective AI implementation and creates a model that delineates the specific groups related to AI utilisation. The data were obtained from the Top 100 organisations in Czechia, focusing on those actively leveraging AI.


Findings: The outputs show the orientation of the use of AI skills in marketing and human resources and basic administrative tasks. A significant gap was found in relation to emotional and interpersonal skills, which has not yet been emphasised in studied organisations.


Research Limitation/Implication: This paper formulates future-oriented, successful approaches to skill development with the wider use of AI. The limitation is first approach to technologically oriented Czech top organisations and limited sample due to a specific approach and early phase of AI use in operations.


Originality/Value of paper: The results yielded a new framework of AI-required skills, reflecting the changing competency requirements for effective AI utilisation. This research contributes to the academic domain by providing an integrated and fundamental framework for competency development that incorporates technological advancements.


 

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Authors

Zdeněk Kronberger
Lucie Depoo
lucie.depoo@vsem.cz (Primary Contact)
Gabriela Říhová
Kronberger, Z., Depoo, L., & Říhová, G. (2024). The Necessary Skillset Based on the Use of Artificial Intelligence in Czech Top Organisations. Quality Innovation Prosperity, 28(2). https://doi.org/10.12776/qip.v28i2.2030

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