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The Role of Artificial Intelligence in Last Mile Delivery
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The emergence of artificial intelligence (AI) offers possibilities to transform last mile delivery operations. It offers various solutions to long-standing challenges in logistics while meeting the increasing demands of consumers. The paper presents a review of the role directly played by AI in the optimisation of last-mile delivery, analysed from the studies available, major applications, benefits, challenges, and futuristic trends. This paper further describes how AI enables predictive analytics through demand forecasting, algorithms for route optimisation, modes of last mile delivery involving autonomous vehicles and drones, customer communication systems, and inventory management. Case studies of the industry leaders like Amazon, FedEx, and DHL, have indicated some salient benefits namely cost reduction, enhanced customer satisfaction, and improved efficiency. However, challenges persist, such as data security, high costs of implementation, and difficulties in having the same rules and regulations met by individual companies. The paper points to the possibility of various developing technologies, including federated learning and edge AI, that can be looked at as possible solutions. There are also suggestions in relation to policy formulation and strategies which companies in last-mile logistics can update to foster the adoption of AI. Noteworthy points are also contained for industry players and policy makers, related to leveraging AI and the attendant challenges, to drive effective transformation of last mile delivery.
Title: The Role of Artificial Intelligence in Last Mile Delivery
Description:
The emergence of artificial intelligence (AI) offers possibilities to transform last mile delivery operations.
It offers various solutions to long-standing challenges in logistics while meeting the increasing demands of consumers.
The paper presents a review of the role directly played by AI in the optimisation of last-mile delivery, analysed from the studies available, major applications, benefits, challenges, and futuristic trends.
This paper further describes how AI enables predictive analytics through demand forecasting, algorithms for route optimisation, modes of last mile delivery involving autonomous vehicles and drones, customer communication systems, and inventory management.
Case studies of the industry leaders like Amazon, FedEx, and DHL, have indicated some salient benefits namely cost reduction, enhanced customer satisfaction, and improved efficiency.
However, challenges persist, such as data security, high costs of implementation, and difficulties in having the same rules and regulations met by individual companies.
The paper points to the possibility of various developing technologies, including federated learning and edge AI, that can be looked at as possible solutions.
There are also suggestions in relation to policy formulation and strategies which companies in last-mile logistics can update to foster the adoption of AI.
Noteworthy points are also contained for industry players and policy makers, related to leveraging AI and the attendant challenges, to drive effective transformation of last mile delivery.
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