Generative Artificial Intelligence in Logistics
Use Cases and Application Potential
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Beschreibung
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.
Autor*in
Ludwig Häberle
Themen in »Generative Artificial Intelligence in Logistics«
Generative AI, Artifical Intelligence, Logistics, Supply Chain Automation, Digitalisierung, Use Cases, Knowledge Enablement Decision Drafting, Operational Intelligence, Tender Management Procurement, Negotiation, Customs, Contract Check, Invoice Check Data Quality, Document Management, Shipment Tracking Forecasting, Planning, Training, Onboarding, Knowledge Twin Damage Detection, Anomaly Detection, Real-time Alerts, Offer Creation Proposal Drafts, Project Rollout, Risk Management Deployment, Monitoring, Framework, Efficiency, Productivity Transparency, Collaboration, Innovation, Sustainability