Vpliv umetne inteligence na poslovne procese prodaje in nabave

Petrovič, Domen

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Title:	Vpliv umetne inteligence na poslovne procese prodaje in nabave
Authors:	ID Petrovič, Domen (Author) ID Smogavc Cestar, Andrej (Mentor) More about this mentor...
Files:	VS_Petrovic_Domen_2025.pdf (1009,54 KB) MD5: CE99C359CA49FBADA9153676E18DC503
Language:	Slovenian
Work type:	Bachelor thesis/paper
Typology:	2.11 - Undergraduate Thesis
Organization:	EPF - Faculty of Business and Economics
Abstract:	Diplomska naloga raziskuje vpliv umetne inteligence na optimizacijo poslovnih postopkov, zlasti na področju prodaje in nabave. Umetna inteligenca podjetjem omogoča večjo učinkovitost, prilagodljivost in zmanjšanje stroškov, hkrati pa izboljšuje uporabniško izkušnjo ter povečuje prihodke. Naloga temelji na preučevanju primerov iz prakse, ki dokazujejo vpliv UI na poslovne rezultate v različnih podjetjih. Teoretični del naloge obravnava ključne koncepte umetne inteligence, vključno s strojnim učenjem in analizo velikih podatkov, ter raziskuje njihove aplikacije v poslovnih procesih. Osredotoča se na uporabo umetne inteligence za avtomatizacijo procesov, napovedovanje povpraševanja in personalizacijo storitev v prodaji in nabavi, kar podjetjem omogoča hitrejše prilagajanje tržnim spremembam. Empirični del naloge vključuje več študij primerov. Amazon uporablja umetno inteligenco za personalizacijo priporočil izdelkov, kar je povzročilo 13% povečanje prihodkov, saj natančnejša priporočila spodbujajo večjo zvestobo strank. Walmart pa je z avtomatiziranimi pogajanji in uporabo e-avkcij v nabavnih procesih izboljšal učinkovitost pogajanj z dobavitelji, kar je privedlo do bolj transparentnih in konkurenčnih dobavnih pogojev ter večje zadovoljstvo končnih strank. Netflix uporablja umetno inteligenco za priporočanje personaliziranih vsebin, kar povečuje angažiranost gledalcev in podaljšuje njihovo uporabo platforme. Prilagajanje vsebin z uporabo UI je prispevalo k večji zvestobi uporabnikov in pomembnim finančnim prihrankom. HubSpot uporablja umetno inteligenco za avtomatizacijo marketinških procesov, kar je povzročilo kar 20% povečanje stopnje konverzij strank, kar dokazuje neposreden vpliv umetne inteligence na izboljšanje marketinških aktivnosti. Kljub številnim prednostim uporabe umetne inteligence naloga obravnava tudi izzive, kot so začetni stroški implementacije, etični pomisleki in odpornost zaposlenih na spremembe. Vendar raziskava kaže, da lahko podjetja, ki uspešno implementirajo umetno inteligenco, dolgoročno pričakujejo nižje stroške, višje prihodke in izboljšano uporabniško izkušnjo. Na podlagi raziskave lahko zaključimo, da ima umetna inteligenca ključno vlogo pri izboljševanju poslovnih postopkov v prodaji in nabavi, saj omogoča večjo učinkovitost, personalizacijo in boljše prilagajanje tržnim spremembam, kar podjetjem omogoča dolgoročno konkurenčno prednost.
Keywords:	Umetna inteligenca, podjetje, podatki, procesi, prodaja, nabava.
Place of publishing:	Maribor
Publisher:	D. Petrovič
Year of publishing:	2024
PID:	20.500.12556/DKUM-90849
UDC:	004.8
COBISS.SI-ID:	226284803
Publication date in DKUM:	17.02.2025
Views:	253
Downloads:	132
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:	16.12.2024

Secondary language

Language:	English
Title:	The impact of artificial intelligence on sales and procurement of business processes
Abstract:	The thesis explores the impact of artificial intelligence on the optimization of business processes, particularly in the areas of sales and procurement. AI enables companies to achieve greater efficiency, flexibility, and cost reduction while improving the user experience and increasing revenues. The thesis is based on case studies that demonstrate the impact of AI on business results in various companies. The theoretical part of the thesis examines key concepts of AI, including machine learning and big data analysis, and explores their applications in business processes. It focuses on the use of AI for automating processes, demand forecasting, and service personalization in sales and procurement, allowing companies to adapt quickly to market changes. The empirical part includes several case studies. Amazon uses AI for product recommendation personalization, resulting in a 13 % increase in revenue due to more accurate recommendations and greater customer loyalty. Walmart has improved the efficiency of supplier negotiations through automated negotiations and e-auctions, leading to more transparent and competitive procurement conditions, as well as higher customer satisfaction. Netflix utilizes AI for personalized content recommendations, increasing viewer engagement and extending platform usage. Personalizing content through AI has contributed to greater user loyalty and significant financial savings. HubSpot leverages AI to automate marketing processes, resulting in an 20% increase in customer conversion rates, demonstrating the direct impact of AI on improving marketing performance. Despite numerous advantages, the thesis also addresses challenges such as the initial implementation costs, ethical concerns, and employee resistance to change. However, the research shows that companies successfully implementing AI can expect lower costs, higher revenues, and an improved user experience in the long term. In conclusion, the research highlights that AI plays a crucial role in enhancing business processes in sales and procurement by enabling greater efficiency, personalization, and better adaptation to market changes, providing companies with a long-term competitive advantage.
Keywords:	Artificial intelligence, company, data, processes, sales, procurement.

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