Vpliv umetne inteligence in kadrovske analitike na dobrobit zaposlenih: priložnosti in izzivi

Kaučič, Saša

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Title:	Vpliv umetne inteligence in kadrovske analitike na dobrobit zaposlenih: priložnosti in izzivi
Authors:	ID Kaučič, Saša (Author) ID Treven, Sonja (Mentor) More about this mentor...
Files:	MAG_Kaucic_Sasa_2026.pdf (1,58 MB) MD5: 1FB71528A959B8ADDE69649BA8ADFDAF
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	EPF - Faculty of Business and Economics
Abstract:	V magistrskem delu smo na podlagi pregleda in analize obstoječe strokovne ter znanstvene literature preučevali, kako uvajanje umetne inteligence in kadrovske analitike vpliva na dobrobit zaposlenih ter s kakšnimi priložnostmi in tveganji se pri tem srečujejo organizacije. V delu so bile analizirane ugotovitve različnih avtorjev s področja avtomatizacije kadrovskih procesov, digitalnega nadzora ter algoritmičnega upravljanja. Pregled literature poudarja, da napredna digitalna orodja opazno pohitrijo in poenostavijo delo kadrovske službe, zlasti pri pregledovanju prijav, obdelavi velikih količin podatkov ter načrtovanju kadrovskih potreb. Vendar pa preučevani viri opozarjajo, da preveliko zanašanje na avtomatsko odločanje in ocenjevanje ljudi skozi gola številska merila prinaša resne stranske učinke. Pri zaposlenih sproža dodaten stres, zmanjšuje občutek samostojnosti pri delu ter ustvarja pritiske zaradi stalnega nadzora. Iz obravnavane literature izhaja, da sta za ohranitev zaupanja in občutka pravičnosti ključni predvsem dve stvari: transparentnost glede delovanja algoritmov ter ohranitev končne presoje v rokah človeka. Obravnavane raziskave kažejo, da je usposabljanje zaposlenih povezano z večjim zaznavanjem koristi uporabe umetne inteligence, ne potrjujejo pa, da samo po sebi nujno zmanjšuje odpor, negotovost ali zaskrbljenost zaposlenih. Ugotovitve znotraj naloge potrjujejo, da tehnologija sama po sebi ni dobra ali slaba za počutje delavcev, ampak je vse odvisno od načina njene implementacije v delovno okolje.
Keywords:	kadrovska analitika, umetna inteligenca, dobrobit zaposlenih, management človeških virov, JD-R model
Place of publishing:	Maribor
Publisher:	S. Kaučič]
Year of publishing:	2026
PID:	20.500.12556/DKUM-99689
UDC:	005.95:004.8
COBISS.SI-ID:	292542467
Publication date in DKUM:	25.09.2026
Views:	82
Downloads:	2
Metadata:
Categories:	EPF
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Licences

License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	24.08.2026

Secondary language

Language:	English
Title:	The impact of artificial intelligence and people analytics on employee well-being: opportunities and challenges
Abstract:	This master's thesis examines how the adoption of artificial intelligence and HR analytics impacts employee well-being, highlighting both benefits and risks for modern organizations based on a comprehensive literature review. Through the analysis and synthesis of existing academic research, the study evaluates automated recruitment, workplace monitoring, and algorithmic management practices. The literature indicates that AI-driven tools significantly improve HR efficiency by simplifying candidate screening, streamlining data processing, and assisting in strategic workforce planning. However, empirical studies warn that over-reliance on automated decision-making and evaluating staff performance strictly through quantitative metrics creates notable drawbacks. It increases employee stress, reduces day-to-day work autonomy, and creates uncomfortable pressure from continuous digital oversight. The reviewed research reveals that maintaining employee trust and procedural fairness depends heavily on two key factors: algorithmic transparency and keeping human judgment at the center of final decisions. Furthermore, the reviewed evidence associates employee training and digital skill development with more positive perceptions of the benefits of artificial intelligence, but does not establish that training alone necessarily reduces employee resistance, uncertainty, or job-related concerns. Ultimately, the thesis concludes that the impact of AI on workplace well-being is not defined by the technology itself, but rather by how thoughtfully leadership integrates it into organizational culture.
Keywords:	Human resource analytics, Artificial intelligence, Employee well-being, Human resource management, JD-R model

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