Uporaba umetne inteligence v notranji reviziji in njena povezanost z učinkovitostjo notranje revizijske dejavnosti v slovenskih organizacijah

Zemljič, Tamara

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Title:	Uporaba umetne inteligence v notranji reviziji in njena povezanost z učinkovitostjo notranje revizijske dejavnosti v slovenskih organizacijah
Authors:	ID Zemljič, Tamara (Author) ID Kolar, Iztok (Mentor) More about this mentor...
Files:	MAG_Zemljic_Tamara_2026.pdf (2,45 MB) MD5: 3B6F1C51F469E0C5418D6DED6BF28A4A
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	EPF - Faculty of Business and Economics
Abstract:	Umetna inteligenca postaja vse pomembnejši dejavnik digitalne transformacije organizacij in pomembno vpliva tudi na področje notranje revizije. Zaradi vse večje količine podatkov, kompleksnosti poslovnih procesov ter potrebe po hitrejšem in učinkovitejšem izvajanju revizijskih postopkov organizacije vse pogosteje uvajajo različna AI-orodja in napredne analitične tehnologije. Uporaba umetne inteligence notranji reviziji omogoča avtomatizacijo rutinskih nalog, hitrejšo obdelavo podatkov, učinkovitejše zaznavanje nepravilnosti ter izboljšanje kakovosti odločanja. Hkrati pa njena uporaba odpira tudi številna vprašanja glede varnosti podatkov, zanesljivosti rezultatov, regulative in etičnih vidikov uporabe. Magistrsko delo obravnava uporabo umetne inteligence v notranji reviziji slovenskih organizacij ter njeno povezanost z zaznano učinkovitostjo in kakovostjo notranjerevizijske dejavnosti. Posebna pozornost je namenjena organizacijskim, tehnološkim in kompetenčnim dejavnikom, ki vplivajo na uvedbo umetne inteligence, ter zaznanim oviram in tveganjem pri njeni uporabi. Rezultati raziskave kažejo, da organizacije umetno inteligenco v notranji reviziji večinoma uporabljajo v omejenem obsegu, predvsem pri pripravi poročil, analiziranju dokumentov in podpori načrtovanju revizijskih postopkov. Med najpomembnejšimi ovirami so respondenti izpostavili tveganja glede varnosti, zaupnosti in zasebnosti podatkov, visoke stroške uvedbe ter regulativno negotovost. Ugotovitve raziskave prav tako kažejo, da je višja stopnja uporabe umetne inteligence povezana z višjo zaznano učinkovitostjo in kakovostjo notranjerevizijske dejavnosti. Magistrsko delo prispeva k boljšemu razumevanju uporabe umetne inteligence v notranji reviziji slovenskih organizacij ter odpira možnosti za nadaljnje raziskovanje in razvoj sodobnih notranjerevizijskih praks v digitalnem okolju.
Keywords:	umetna inteligenca, notranje revizija, digitalna transformacija, TOE model, učinkovitost notranje revizije, SPSS analiza.
Place of publishing:	Maribor
Publisher:	T. Zemljič]
Year of publishing:	2026
PID:	20.500.12556/DKUM-98168
UDC:	657.6:004.8
COBISS.SI-ID:	287730947
Publication date in DKUM:	13.08.2026
Views:	259
Downloads:	12
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:	21.05.2026

Secondary language

Language:	English
Title:	The use of artificial intelligence in internal audit and its connection to the effectiveness of interal audit activities in slovenian organizations
Abstract:	Artificial intelligence is becoming an increasingly important factor in the digital transformation of organizations and is also having a significant impact on the field of internal audit. Due to the increasing amount of data, the complexity of business processes and the need for faster and more efficient implementation of audit procedures, organizations are increasingly introducing various AI tools and advanced analytical technologies. The use of artificial intelligence in internal audit enables automation of routine tasks, faster data processing, more efficient detection of irregularities and improvement of the quality of decision-making. At the same time, its use also raises numerous questions regarding data security, reliability of results, regulations and ethical aspects of use. The master's thesis deals with the use of artificial intelligence in internal audit of Slovenian organizations and its connection with the perceived efficiency and quality of internal audit activities. Special attention is paid to organizational, technological and competency factors that influence the introduction of artificial intelligence, as well as perceived obstacles and risks in its use. The results of the research show that organizations mostly use artificial intelligence in internal audit to a limited extent, mainly in preparing reports, analyzing documents and supporting the planning of audit procedures. Among the most important obstacles, respondents highlighted risks related to data security, confidentiality and privacy, high implementation costs and regulatory uncertainty. The findings of the survey also show that a higher level of use of artificial intelligence is associated with higher perceived efficiency and quality of internal audit activities. The master's thesis contributes to a better understanding of the use of artificial intelligence in internal audit of Slovenian organizations and opens up possibilities for further research and development of modern internal audit practices in the digital environment.
Keywords:	artificial intelligence, internal audit, digital transformation, TOE model, internal audit effectiveness, SPSS analysis.

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