A significant barrier to AI adoption in the business world is the scarcity of clear, accessible information on how to leverage AI to enhance organisational productivity. Understanding the practical applications of AI is a prerequisite for companies to identify relevant opportunities and develop a strategy to operationalise them. To address this need, the AI Governance and Regulatory Innovation team at The Alan Turing Institute is pursuing a research project to illuminate how businesses in the four BridgeAI priority sectors of agriculture, forestry and fishing, construction, creative industries, and transportation and storage can leverage AI to be more productive. The first milestone of this project is the publication of a framework for categorising and analysing business applications of AI and a brief analysis of sector-specific AI use cases. Our findings are published as a series of five documents: four sector-specific briefings complemented by a paper presenting a framework to categorise and analyse AI use cases. This paper is the sector-specific briefing which aims to contribute towards demystifying how businesses in the transportation and storage sector can use AI to be more competitive, sustainable, and productive. The first part of the briefing offers an overview of the key economic features of the UK’s transportation and storage sector, including a brief discussion of sector-specific challenges to AI adoption. In the second part, we leverage the AI use case classification framework to discuss five sectoral AI applications. Each AI use case is accompanied by a use case card, which provides a visual summary of the key information related to that application. These examples illustrate the wide-ranging and diverse potential applications of AI in the transportation and storage sector.