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Title:Umetna inteligenca in orodja menedžerjev
Authors:ID Kreslin, Damijan (Author)
ID Pušavec, Franci (Author)
ID Markič, Mirko (Author)
Files:URL https://ojs.fos-unm.si/index.php/ruo/sl/article/view/205/480
 
.pdf RAZ_Kreslin_Damijan_2026.pdf (402,19 KB)
MD5: E5C5FE37D5A8D0EFED71B3044E7C04D2
 
Language:Slovenian
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FM - Faculty of Management
Abstract:Raziskovalno vprašanje (RV): Kakšno je razmerje med umetno inteligenco in orodji menedžerjev ter ali umetna inteligenca deluje predvsem kot njihov substitut ali komplement? Namen: Namen raziskave je bil proučiti vpliv umetne inteligence na orodja menedžerjev in razviti konceptualni model povezav med presojo menedžerjev, dinamičnimi zmožnostmi in poslovno uspešnostjo podjetja. Metoda: Raziskava temelji na sistematičnem pregledu sodobne znanstvene in strokovne literature s področja menedžmenta, orodij menedžerjev, umetne inteligence in dinamičnih zmožnosti ter na ugotovitvah predhodne empirične raziskave o vplivu orodij menedžerjev na poslovno uspešnost podjetij. Na podlagi primerjalne analize literature je bil razvit konceptualni model razmerij med proučevanimi konstrukti. Rezultati: Razvit je koncept podatkovne intenzivnosti menedžerskih orodij kot dejavnika, ki pojasnjuje stopnjo njihove podpore oziroma substitucije z umetno inteligenco. Oblikovana je nova taksonomija menedžerskih orodij glede na podatkovno intenzivnost, potrebo po menedžerski presoji in vpliv umetne inteligence. Predlagan je izvirni konceptualni model, v katerem menedžerska orodja in umetna inteligenca vplivajo na poslovno uspešnost podjetja posredno preko menedžerske presoje in dinamičnih zmožnosti. Organizacija: Rezultati omogočajo menedžerjem boljše razumevanje področij, na katerih lahko umetna inteligenca učinkovito podpira menedžersko odločanje, ter področij, kjer ostaja menedžerska presoja ključni dejavnik uspešnega vodenja organizacij. Družba: Prispevek prispeva k boljšemu razumevanju odgovorne, pregledne in človeku osredotočene uporabe umetne inteligence v organizacijah ter poudarja pomen ohranjanja človeške presoje pri strateškem odločanju. Originalnost: Izvirni prispevek raziskave predstavlja razvoj koncepta podatkovne intenzivnosti menedžerskih orodij, oblikovanje nove taksonomije menedžerskih orodij ter razvoj konceptualnega modela, ki pojasnjuje posredni vpliv umetne inteligence in menedžerskih orodij na poslovno uspešnost preko menedžerske presoje in dinamičnih zmožnosti. Raziskava hkrati povezuje teorijo omejene racionalnosti, teorijo na virih temelječe konkurenčne prednosti in teorijo dinamičnih zmožnosti v enoten konceptualni okvir za proučevanje vpliva umetne inteligence na sodobni menedžment. Omejitve/nadaljnje raziskovanje: Raziskava je konceptualne narave in ne vključuje empiričnega preverjanja predlaganega modela. Prihodnje raziskave naj empirično preverijo predlagane povezave med umetno inteligenco, menedžersko presojo, dinamičnimi zmožnostmi in poslovno uspešnostjo podjetij.
Keywords:umetna inteligenca, menedžerska orodja, menedžerska presoja, dinamične zmožnosti, poslovna uspešnost, podatkovna intenzivnost, digitalna transformacija, menedžment
Publication version:Version of Record
Publication date:18.08.2026
Year of publishing:2026
Number of pages:Str. 185-204
Numbering:Letn. 15, št. 3
PID:20.500.12556/RUP-23742 This link opens in a new window
UDC:005.9:004.8
ISSN on article:2232-5204
DOI:10.37886/ruo.2026.011 This link opens in a new window
COBISS.SI-ID:293427203 This link opens in a new window
Publication date in RUP:02.10.2026
Views:93
Downloads:5
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Record is a part of a journal

Title:Revija za univerzalno odličnost : RUO
Publisher:Fakulteta za organizacijske študije
ISSN:2232-5204
COBISS.SI-ID:260228096 This link opens in a new window

Licences

License:CC BY-SA 4.0, Creative Commons Attribution-ShareAlike 4.0 International
Link:http://creativecommons.org/licenses/by-sa/4.0/
Description:This Creative Commons license is very similar to the regular Attribution license, but requires the release of all derivative works under this same license.

Secondary language

Language:English
Title:Artificial intelligence and management tools
Abstract:Research Question (RQ): What is the relationship between artificial intelligence and management tools, and does artificial intelligence primarily function as a substitute for or a complement to management tools and managerial judgment? Purpose: This study examines the relationship between artificial intelligence and management tools and develops a conceptual framework explaining how artificial intelligence affects firm performance through managerial judgment and dynamic capabilities. Method: The research is based on a systematic literature review covering management, management tools, artificial intelligence, and dynamic capabilities. Scientific articles, monographs, institutional reports, and previous empirical findings on management tools and business performance were analyzed. A conceptual model was developed through comparative analysis and theoretical synthesis. Results: The study introduces the concept of management tool data intensity, proposes a taxonomy of management tools according to their susceptibility to AI support, and develops a conceptual framework explaining that AI contributes to firm performance indirectly through managerial judgment and dynamic capabilities rather than through direct substitution of managers. Organization: The findings help managers identify areas where artificial intelligence can effectively support decision-making and areas where managerial judgment remains essential for organizational success. Society: The study contributes to a better understanding of responsible, transparent, and human- centered artificial intelligence adoption in organizations while emphasizing the continued importance of human judgment in strategic decision-making. Originality: The originality of the study lies in introducing the concept of management tool data intensity, proposing a novel taxonomy of management tools, and integrating bounded rationality theory, the resource-based view, and dynamic capabilities into a unified conceptual framework for explaining AI-enabled managerial decision-making. Limitations/Future Research: The study is conceptual in nature and does not include empirical validation of the proposed model. Future research should empirically test the proposed relationships among artificial intelligence, managerial judgment, dynamic capabilities, and firm performance using SEM or PLS-SEM methodologies.
Keywords:artificial intelligence, management tools, managerial judgment, dynamic capabilities, firm performance, data intensity, digital transformation, management


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