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.
2024
The Use of AI in BtoB Manufacturing Firms
BtoB
Manufacturing Firms
Use of AI
File in questo prodotto:
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

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/101236