Razvoj konceptualnega modela uvajanja umetne inteligence v projektni management

Horvat, Leon

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Title:	Razvoj konceptualnega modela uvajanja umetne inteligence v projektni management
Authors:	ID Horvat, Leon (Author) ID Kern, Tomaž (Mentor) More about this mentor...
Files:	MAG_Horvat_Leon_2026.pdf (1,08 MB) MD5: 26CB350C840B51F623489441F03EEBDD
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	FOV - Faculty of Organizational Sciences in Kranj
Abstract:	V magistrskem delu smo obravnavali uvajanje umetne inteligence (UI) v projektni management ter razvili konceptualni model, ki organizacijam omogoča strukturirano, premišljeno in varno integracijo UI v projektne procese. Izhodišče predstavlja naraščajočo kompleksnost sodobnih projektov, ki jo povzročajo razpršene ekipe, hitre spremembe zahtev in velike količine podatkov, zaradi česar se tradicionalni pristopi, ki temeljijo na izkušnjah projektnih vodij in ročnem spremljanju aktivnosti, pogosto izkažejo za nezadostne. UI pa omogoča hitrejše odločanje, natančnejše napovedi in učinkovitejše obvladovanje tveganj. Namen naloge je bil raziskati vlogo UI v projektnih procesih, opredeliti koristi, omejitve in tveganja ter prepoznati dejavnike, ki vplivajo na uspešno implementacijo UI v organizacijah. Na podlagi sistematičnega pregleda literature smo analizirali ključna teoretična izhodišča, med katerimi izstopajo okvir tehnologija-organizacija-okolje (ang. Technology-Organization-Environment – TOE), model sprejemanja tehnologije (ang. Technology Acceptance Model – TAM) ter modeli digitalne in UI zrelosti. V raziskavi smo potrdili, da UI pomembno vpliva na projektne procese ter prispeva k večji učinkovitosti in boljšemu obvladovanju tveganj, hkrati pa literatura opozarja na izzive, kot so kakovost podatkov, razložljivost modelov (ang. model explainability, tj. sposobnost UI, da pojasni svoje odločitve), pomanjkanje kompetenc, odpor do sprememb ter zahteve regulativnih okvirov, kot sta evropska uredba o varstvu osebnih podatkov (ang. General Data Protection Regulation – GDPR) in evropska uredba o UI (ang. Artificial Intelligence Act – AI Act). Na podlagi tematske analize identificiranih tehnoloških, organizacijskih, kompetenčnih, etičnih, regulativnih in okoljskih dejavnikov smo oblikovali šestdimenzionalni konceptualni okvir, ki predstavlja temelj za razvoj konceptualnega modela uvajanja UI. Ta je strukturiran v štiri faze: pripravo, pilotno implementacijo, integracijo in spremljanje učinkov. Model organizacijam ponuja jasno pot uvajanja UI ter podpira dvigovanje zrelosti, zmanjševanje tveganj in krepitev kompetenc projektnih ekip. Vse zastavljene cilje magistrske naloge smo dosegli, saj smo analizirali vlogo UI v projektnih procesih, opredelili koristi in tveganja, pregledali dejavnike uspešne implementacije ter razvili konceptualni model uvajanja UI. Zaključki potrjujejo, da uvajanje UI ni zgolj tehnološki izziv, temveč proces, ki zahteva strateško usklajenost, organizacijsko pripravljenost, ustrezne kompetence in kulturo učenja, zato priporočamo postopno uvajanje UI z jasnimi cilji, pilotnimi projekti, vlaganjem v kompetence ter vzpostavitvijo mehanizmov za etično in regulativno skladno uporabo UI.
Keywords:	Umetna inteligenca (UI), projektni management, konceptualni model, digitalna transformacija, implementacija UI
Place of publishing:	Kranj
Year of publishing:	2026
PID:	20.500.12556/DKUM-98364
COBISS.SI-ID:	287243523
Publication date in DKUM:	07.08.2026
Views:	142
Downloads:	19
Metadata:
Categories:	FOV
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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:	08.06.2026

Secondary language

Language:	English
Title:	Development of a conceptual model for implementing artificial intelligence in project management
Abstract:	This master’s thesis examines the introduction of artificial intelligence (AI) into project management and develops a conceptual model that enables organizations to integrate AI into project processes in a structured, deliberate, and safe manner. The starting point is the increasing complexity of contemporary projects, driven by distributed teams, rapidly changing requirements, and growing volumes of data, which often render traditional approaches based on the experience of project managers and manual monitoring insufficient. AI, on the other hand, enables faster decision making, more accurate predictions, and more effective risk management. The aim of the thesis was to explore the role of AI in project processes, identify its benefits, limitations, and risks, and determine the key factors influencing successful AI implementation in organizations. Based on a systematic literature review, we analyzed key theoretical foundations, including the Technology–Organization–Environment (TOE) framework, the Technology Acceptance Model (TAM), and digital and AI maturity models. The study confirmed that AI significantly affects project processes and contributes to greater efficiency and improved risk management, while the literature also highlights challenges such as data quality, model explainability, lack of competencies, resistance to change, and regulatory requirements, including the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (AI Act). Through thematic analysis of identified technological, organizational, competence related, ethical, regulatory, and environmental factors, we developed a six dimensional conceptual framework forming the basis for a conceptual model of AI implementation. The model is structured into four phases: preparation, pilot implementation, integration, and impact monitoring. It provides organizations with a clear pathway for adopting AI and supports maturity development, risk reduction, and competence strengthening within project teams. All objectives of the thesis were fully achieved, as we analyzed the role of AI in project processes, identified benefits and risks, examined key implementation factors, and developed a conceptual model for AI adoption. The findings confirm that introducing AI is not merely a technological challenge but a process requiring strategic alignment, organizational readiness, appropriate competencies, and a culture of learning. Accordingly, we recommend a gradual approach to AI implementation, supported by clear objectives, pilot projects, investment in competencies, and mechanisms ensuring ethical and regulatory compliance.
Keywords:	Artificial intelligence (AI), project management, conceptual model, digital transformation, AI implementation

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