AI Integration in RISE with SAP: Enhancing Operational Efficiency and Decision-Making in Manufacturing through Cloud Migration to SAP S/4HANA

Název práce: AI Integration in RISE with SAP: Enhancing Operational Efficiency and Decision- Making in Manufacturing through Cloud Migration to SAP S/4HANA
Autor(ka) práce: Luong, Huu Loc
Typ práce: Diploma thesis
Vedoucí práce: Hönig, Vladimír
Oponenti práce: Procházka, Petr
Jazyk práce: English
Abstrakt:
This master’s thesis examines how integrating AI within the RISE with SAP framework affects operational efficiency and decision-making in manufacturing companies. The study uses a mixed-methods approach, combining quantitative multiple regression analysis of survey data with qualitative thematic analysis of open-ended responses. The quantitative analysis outcomes validate that the use of AI for analytics and automation boosts how well manufacturing works and improves decision-making quality. Meanwhile, the thematic analysis depicts crucial user concerns about the need for AI capabilities tailored to manufacturing, transparency, customization, and alignment with strategic goals. The findings show the potential and challenges of using AI in manufacturing, providing practical recommendations for SAP and industry professionals. Even though there are some limitations with the sample size and the way the study was designed, this thesis offers essential insights on improving AI tools to enhance innovation and competitiveness in manufacturing companies.
Klíčová slova: Cloud Migration; ERP; SAP; AI; Digital Transformation; AI-driven; Cloud ERP; RISE with SAP; S/4HANA Cloud
Název práce: AI Integration in RISE with SAP: Enhancing Operational Efficiency and Decision-Making in Manufacturing through Cloud Migration to SAP S/4HANA
Autor(ka) práce: Luong, Huu Loc
Typ práce: Diplomová práce
Vedoucí práce: Hönig, Vladimír
Oponenti práce: Procházka, Petr
Jazyk práce: English
Abstrakt:
This master’s thesis examines how integrating AI within the RISE with SAP framework affects operational efficiency and decision-making in manufacturing companies. The study uses a mixed-methods approach, combining quantitative multiple regression analysis of survey data with qualitative thematic analysis of open-ended responses. The quantitative analysis outcomes validate that the use of AI for analytics and automation boosts how well manufacturing works and improves decision-making quality. Meanwhile, the thematic analysis depicts crucial user concerns about the need for AI capabilities tailored to manufacturing, transparency, customization, and alignment with strategic goals. The findings show the potential and challenges of using AI in manufacturing, providing practical recommendations for SAP and industry professionals. Even though there are some limitations with the sample size and the way the study was designed, this thesis offers essential insights on improving AI tools to enhance innovation and competitiveness in manufacturing companies.
Klíčová slova: Cloud Migration; ERP; Digital Transformation; AI-driven; Cloud ERP; RISE with SAP; SAP; AI; S/4HANA Cloud

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 strategie

Informace o odevzdání a obhajobě

Datum zadání práce: 1. 6. 2024
Datum podání práce: 14. 5. 2025
Datum obhajoby: 18. 6. 2025
Identifikátor v systému InSIS: https://insis.vse.cz/zp/90556/podrobnosti

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