Generative Artificial Intelligence in Logistics – Use Cases and Application Potential
ISBN
9783689523251
Type
book
Date Issued
2025-08-26
Author(s)
Abstract
The use of Generative AI (Gen AI) in logistics is gaining significant attention, with expectations of cost reduction and improved efficiency. However, there has been a lack of structured evaluation and practical guidance for its application in the field.
A practitioner-focused study by the Institute for Production and Supply Chain Management (PSCM-HSG) at the University of St. Gallen addresses this gap. It offers a theoretical foundation of Gen AI, explores current and future use cases in logistics, and provides actionable frameworks and recommendations for businesses.
The study identifies 16 potential use cases, categorized into:
• Knowledge Enablement (e.g., digital knowledge twins, training support),
• Decision Drafting (e.g., offer creation, contract and invoice checks), and
• Operational Intelligence (e.g., data management, customs clearance).
A four-phase framework is proposed to help companies:
1. Identify relevant use cases,
2. Assess their potential,
3. Implement them using an eight-step method, and
4. Deploy & control solutions effectively.
Developed through collaboration with various companies, the study offers both practical and academic insights, aiming to support the successful integration of Gen AI in logistics.
A practitioner-focused study by the Institute for Production and Supply Chain Management (PSCM-HSG) at the University of St. Gallen addresses this gap. It offers a theoretical foundation of Gen AI, explores current and future use cases in logistics, and provides actionable frameworks and recommendations for businesses.
The study identifies 16 potential use cases, categorized into:
• Knowledge Enablement (e.g., digital knowledge twins, training support),
• Decision Drafting (e.g., offer creation, contract and invoice checks), and
• Operational Intelligence (e.g., data management, customs clearance).
A four-phase framework is proposed to help companies:
1. Identify relevant use cases,
2. Assess their potential,
3. Implement them using an eight-step method, and
4. Deploy & control solutions effectively.
Developed through collaboration with various companies, the study offers both practical and academic insights, aiming to support the successful integration of Gen AI in logistics.
Funding(s)
Promotional Association of the Institute for Production and Supply Chain Management at the University of St.Gallen
Language
English
HSG Classification
contribution to practical use / society
Refereed
No
Publisher
Cuvillier Verlag
Publisher place
Göttingen
Pages
72
Subject(s)
Division(s)
File(s)![Thumbnail Image]()
Name
WaibelHaberle_Generative Artificial Intelligence in Logistics_Table of Contents.pdf
Size
1.46 MB
Format
Adobe PDF
Checksum (MD5)
a58870a0e79f5d061804e4990c45ad68