Shaping the Future of Freight Logistics: Use Cases of Artificial Intelligence

The human–machine interface is increasingly attracting attention. This paper investigates the potential value and impact of using Artificial Intelligence (AI) in the freight logistics industry by defining various use cases. It explores how the logistics industry can use data and AI to improve its economic, social, and environmental sustainability through better decision making. The research methodology involved a systematic literature review, interviews with subject matter experts, facility visits, and generative AI. The SLR showed that none of the peer-reviewed literature offers an extensive exposition of AI use cases in freight logistics. The key findings highlight AI’s untapped potential in the logistics industry, with 77 unique use cases identified across three spheres: holistic supply chain opportunities, transport vehicles, and logistical facilities. The research is expected to contribute to the growing body of knowledge of AI in logistics, inform future research, guide industry practices, and inspire further innovation in logistics technology.

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Publication Details

Journal
Sustainability
Published
2025-02-07
DOI
https://doi.org/10.3390/su17041355
Citations
10
Primary Topic
Urban and Freight Transport Logistics
Type
article
Field-Weighted Citation Impact
10.06
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article

Shaping the Future of Freight Logistics: Use Cases of Artificial Intelligence

Martin Johannes du Plessis, Joubert van Eeden, Leila L. Goedhals-Gerber, Retief Gerber
10 citations
Sustainability
Urban and Freight Transport Logistics
10.06
article

Shaping the Future of Freight Logistics: Use Cases of Artificial Intelligence

Martin Johannes du Plessis, Joubert van Eeden, Leila L. Goedhals-Gerber, Retief Gerber
article en
10 citations

Abstract

The human–machine interface is increasingly attracting attention. This paper investigates the potential value and impact of using Artificial Intelligence (AI) in the freight logistics industry by defining various use cases. It explores how the logistics industry can use data and AI to improve its economic, social, and environmental sustainability through better decision making. The research methodology involved a systematic literature review, interviews with subject matter experts, facility visits, and generative AI. The SLR showed that none of the peer-reviewed literature offers an extensive exposition of AI use cases in freight logistics. The key findings highlight AI’s untapped potential in the logistics industry, with 77 unique use cases identified across three spheres: holistic supply chain opportunities, transport vehicles, and logistical facilities. The research is expected to contribute to the growing body of knowledge of AI in logistics, inform future research, guide industry practices, and inspire further innovation in logistics technology.

SustainabilityVol. 17(4)
Stellenbosch University (ZA)
Openalex Percentile: Top 2%
Urban and Freight Transport Logistics
10.06
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