Optimizing Procurement Processes through AI: An Analysis of Benefits and Challenges

Název práce: Optimizing Procurement Processes through AI: An Analysis of Benefits and Challenges
Autor(ka) práce: Abilova, Laman
Typ práce: Diploma thesis
Vedoucí práce: Vinš, Marek
Oponenti práce: Jirsák, Petr
Jazyk práce: English
Abstrakt:
Despite the claims of artificial intelligence (AI) offering transformative benefits for procurement, only 6% of companies are automating their procurement processes. This study investigates the implementation of GEP SMART, an AI-powered procurement platform, across three different industries- electronics, manufacturing, and pharmaceuticals- to evaluate its effects on cost savings, efficiency, and explore the extent to which it brings challenges to organizations. Based on semi-structured interviews with 12 procurement experts that were analyzed with MAXQDA, the study reveals that the implementation of GEP SMART, an AI platform, increases real-time efficiency with reduced manual errors, automates reports, increases stakeholder management strategies, and captures all procurement steps within one centralized platform. However, the study brings to light that organizations face some struggles during the implementation, such as resistance from employees, new platform complications, training challenges, and stakeholder management. The research validates three hypotheses: (1) AI integration is associated with demonstrable efficiencies; (2) Inadequate digital infrastructure complicates the automation process; (3) success depends on change management and tailored training programs. By bridging the gap in cross-sector evidence, this study provides actionable guidance for procurement leaders in their adoption of AI, arguing that phased implementation roadmaps and cultural adaptation are key to maximizing return on their investment (ROI).
Klíčová slova: AI; Procurement Process; Automation; GEP SMART
Název práce: Optimizing Procurement Processes through AI: An Analysis of Benefits and Challenges
Autor(ka) práce: Abilova, Laman
Typ práce: Diplomová práce
Vedoucí práce: Vinš, Marek
Oponenti práce: Jirsák, Petr
Jazyk práce: English
Abstrakt:
Despite the claims of artificial intelligence (AI) offering transformative benefits for procurement, only 6% of companies are automating their procurement processes. This study investigates the implementation of GEP SMART, an AI-powered procurement platform, across three different industries- electronics, manufacturing, and pharmaceuticals- to evaluate its effects on cost savings, efficiency, and explore the extent to which it brings challenges to organizations. Based on semi-structured interviews with 12 procurement experts that were analyzed with MAXQDA, the study reveals that the implementation of GEP SMART, an AI platform, increases real-time efficiency with reduced manual errors, automates reports, increases stakeholder management strategies, and captures all procurement steps within one centralized platform. However, the study brings to light that organizations face some struggles during the implementation, such as resistance from employees, new platform complications, training challenges, and stakeholder management. The research validates three hypotheses: (1) AI integration is associated with demonstrable efficiencies; (2) Inadequate digital infrastructure complicates the automation process; (3) success depends on change management and tailored training programs. By bridging the gap in cross-sector evidence, this study provides actionable guidance for procurement leaders in their adoption of AI, arguing that phased implementation roadmaps and cultural adaptation are key to maximizing return on their investment (ROI).
Klíčová slova: AI; GEP SMART; Automation; Procurement Process

Informace o studiu

Studijní program / obor: Management
Typ studijního programu: Magisterský studijní program
Přidělovaná hodnost: Ing.
Instituce přidělující hodnost: Vysoká škola ekonomická v Praze
Fakulta: Fakulta podnikohospodářská
Katedra: Katedra logistiky

Informace o odevzdání a obhajobě

Datum zadání práce: 25. 11. 2024
Datum podání práce: 14. 5. 2025
Datum obhajoby: 18. 6. 2025
Identifikátor v systému InSIS: https://insis.vse.cz/zp/90506/podrobnosti

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