Artificial Intelligence (AI) Integration in HRM function of selected companies/Organizations in the Czech Republic.

Kinjal Jeeva Sengunthar

Master's thesis

Abstract:

This thesis derives into the integration of Artificial Intelligence in Human Resource Management Functions across two enterprises of varying scales in the Czech Republic: the large-scale Amazon s.r.o and medium-scale Novartis s.r.o. Initiated by a theoretical explanation of a detailed review of ongoing practices, supported by examples of implementations of AI in HRM functions in global companies. This investigation into theoretical precedents helps in the preparation of a survey questionnaire qualitative analysis of practical data derived from surveys conducted within the selected companies. The practical segment of the study, through comparative analysis, uncovers how AI’s application differs between a large-scale and a medium-scale industry setting, reflecting on its impact on HRM practices. This juxtaposition reveals the complexities and variegated nature of AI integration, providing insights into the operational and strategic adjustments necessary for effective AI adoption in HRM processes. This thesis results conclude that AI offers substantial benefits for organizational efficiency and workforce management, its successful integration necessitates overcoming challenges through tailored strategies based on the company's scaling. This balanced approach ensures not only the realization of AI’s potential in streamlining HRM practices but also the sustainable growth and empowerment of the workforce, contributing valuable insights to both academic discourse and practical implementation in the field of HRM and AI integration.

Keywords

AI, HRM, Integration, Amazon s.r.o, Novartis s.r.o, Large-scale industry, Comparative analysis, medium-scale industry, HRM functions, AI advantages/Disadvantages, Challenges, Benefits, Sustainable organizational growth.

Language used: English

Date on which the thesis was submitted / produced: 31. 3. 2024

Thesis defence

• Supervisor: Ing. Richard Selby, Ph.D.
• Reader: Dagmar Charvátová, externi

Czech University of Life Sciences Prague

Faculty of Economics and Management

Master programme:
Business Administration