Artificial Intelligence Integration in Business: Study of Employee Competences in Relation to the Organisational Needs Cover Image

Artificial Intelligence Integration in Business: Study of Employee Competences in Relation to the Organisational Needs
Artificial Intelligence Integration in Business: Study of Employee Competences in Relation to the Organisational Needs

Author(s): Paul-Vasile Vezeteu, Dumitru-Iulian NĂSTAC
Subject(s): ICT Information and Communications Technologies
Published by: EDITURA ASE
Keywords: artificial intelligence in business; competence management; level of knowledge and competences of the employees; AI-driven organisational needs; generative AI

Summary/Abstract: Artificial intelligence is a computational technology that has proved its ability to contribute to a wide range of industries such as healthcare, manufacturing, and finance. If properly integrated, it can increase the competitive advantage of a business and enhance the ways it conducts operations. In this regard, competences play an important role in safeguarding the efficient coexistence of employees with intelligent systems. The scientific literature made important contributions to determine what the key competencies when working with AI and how companies plan to adapt to the new technologies. While the papers provide a good overview of what the market requires, we consider that the view is very general, and it is not correlated with what AI integration means for a business. Understanding why strategic decisions are made requires a detailed analysis of the implications of AI in a working environment. The present study aims to communicate a wider perspective on why different levels of knowledge are required with respect to AI, what are the derived competencies and how they relate to various levels of authority in an organisation. Additionally, in this article, the authors make a leap from technical research, focused on AI applications in various fields, to a more general approach with interest in AI integration in business.

  • Issue Year: 26/2024
  • Issue No: 67
  • Page Range: 832-847
  • Page Count: 16
  • Language: English
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