This thesis explores the transformative impact of Artificial Intelligence on Business-to-Business manufacturing firms. As global competition intensifies, manufacturing companies are increasingly turning to AI to optimize operations, enhance supply chain efficiency, and improve product innovation. The study examines the adoption and integration of AI technologies within these firms, focusing on how AI-driven analytics, predictive maintenance, and automation contribute to increased productivity and cost reduction. Through case studies and empirical analysis, the research highlights the strategic advantages AI offers to BtoB manufacturers, while also addressing the challenges and implications of AI implementation in traditional manufacturing environments.
The Use of AI in BtoB Manufacturing Firms
ASGARZADE, FIDAN
2024/2025
Abstract
This thesis explores the transformative impact of Artificial Intelligence on Business-to-Business manufacturing firms. As global competition intensifies, manufacturing companies are increasingly turning to AI to optimize operations, enhance supply chain efficiency, and improve product innovation. The study examines the adoption and integration of AI technologies within these firms, focusing on how AI-driven analytics, predictive maintenance, and automation contribute to increased productivity and cost reduction. Through case studies and empirical analysis, the research highlights the strategic advantages AI offers to BtoB manufacturers, while also addressing the challenges and implications of AI implementation in traditional manufacturing environments.| File | Dimensione | Formato | |
|---|---|---|---|
|
Asgarzade_Fidan.pdf
accesso aperto
Dimensione
453.19 kB
Formato
Adobe PDF
|
453.19 kB | Adobe PDF | Visualizza/Apri |
The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License
https://hdl.handle.net/20.500.12608/101236