20.500.12556/DKUM-99689 Vpliv umetne inteligence in kadrovske analitike na dobrobit zaposlenih: priložnosti in izzivi The impact of artificial intelligence and people analytics on employee well-being: opportunities and challenges 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. 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. kadrovska analitika umetna inteligenca dobrobit zaposlenih management človeških virov JD-R model Human resource analytics Artificial intelligence Employee well-being Human resource management JD-R model true true false S. Kaučič] Slovenski jezik Angleški jezik Magistrsko delo/naloga 2026-08-24 09:40:50 2026-09-25 13:23:02 2026-09-26 03:10:41 0000-00-00 00:00:00 2026 0 Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 005.95:004.8 292542467 MAG_Kaucic_Sasa_2026.pdf MAG_Kaucic_Sasa_2026.pdf 1 1FB71528A959B8ADDE69649BA8ADFDAF 56820dd39258f97138e0aa8f00e8602bf3e3403e11fa5b58b9fb8fb0a0293912 eedb40d4-ad0d-11f1-b668-00155d0001be https://dk.um.si/Dokument.php?lang=slv&id=212086 Ekonomsko-poslovna fakulteta 0 0 0