Artificial Intelligence in Logistics: Optimizing Efficiency and Sustainability
Artificial intelligence streamlines logistics with route optimization, demand forecasting, and automated warehousing, reducing costs and environmental impact for sustainable operations. See latest price on Amazon.
Quick facts
Topic: Transportation
Tags: Transportation, Artificial Intelligence, AI Trends
Length: 339 pages
Best for: Readers who want practical, plain-English AI insights with real-world examples.
Because AI in transportation affects safety, reliability, efficiency, and emissions. Getting the basics right matters long before anyone wheels in the hype machine.
What you’ll learn
Where AI is already being used in transportation today — and where the claims are running ahead of reality.
The workflows, systems, and trade-offs behind practical transportation use cases, explained in plain English.
Key themes including routing, prediction, safety, operations.
The limits, risks, and awkward questions worth asking before you sign off on the sales pitch.
Who this book is for
Supply chain managers, logistics directors, and operations teams who need clear analysis of AI's impact on routing, forecasting, and warehouse automation.
What this book covers
Artificial intelligence streamlines logistics with route optimization, demand forecasting, and automated warehousing, reducing costs.
What makes this book distinct
Route optimisation is only the most visible AI application in logistics. This book goes deeper — into demand forecasting accuracy improvements that have cut warehouse overstock by double-digit percentages, autonomous vehicle deployment in controlled environments, and the AI layer underpinning same-day and next-day delivery economics.
Not your book? Not a supply chain management textbook. If you're in operations and want process frameworks, you'll find this more conceptual. If you want to understand what AI is doing to the competitive dynamics of logistics, it's the right level.
Jonathan HarrisArtificial Intelligence Author & Host of Turing's Torch AI Weekly
Longer-form context from the retired overview page, now folded into the canonical book route.
Problem framing: where this topic gets messy
In transport and mobility, the hard part is not hearing that AI exists. It is deciding where it genuinely improves safety, timing, reliability, and cost without creating fresh operational risk. Artificial intelligence streamlines logistics with route optimization, demand forecasting, and automated warehousing, reducing costs. Pages: 339. Because AI in transportation affects safety, reliability, efficiency, and emissions. Getting the basics right matters long before anyone wheels in the hype machine.
Practical outcomes
In practical terms, the aim is simple: you should leave with a clearer feel for where prediction, routing, control, and decision-support are genuinely useful — and where the sales pitch outruns the engineering. That means clearer judgement, fewer lazy assumptions, and a much better sense of where to press further or walk away.
Identify where ai is already being used in transportation today — and where the claims are running ahead of reality.
Work through the workflows, systems, and trade-offs behind practical transportation use cases, explained in plain english.
Work through key themes including routing, prediction, safety, operations.
Work through the limits, risks, and awkward questions worth asking before you sign off on the sales pitch.
Chapter-level signals
Not a chapter list carved in stone, but the sort of material readers can reasonably expect to work through.
Where AI is already being used
Where AI is already being used in transportation today — and where the claims are running ahead of reality.
The workflows, systems, and trade-offs behind
The workflows, systems, and trade-offs behind practical transportation use cases, explained in plain English.
Key themes including routing, prediction, safety,
Key themes including routing, prediction, safety, operations.
The limits, risks, and awkward questions
The limits, risks, and awkward questions worth asking before you sign off on the sales pitch.
What makes this title distinct
Route optimisation is only the most visible AI application in logistics. This book goes deeper — into demand forecasting accuracy improvements that have cut warehouse overstock by double-digit percentages, autonomous vehicle deployment in controlled environments, and the AI layer underpinning same-day and next-day delivery economics. Not your book? Not a supply chain management textbook. If you're in operations and want process frameworks, you'll find this more conceptual. If you want to understand what AI is doing to the competitive dynamics of logistics, it's the right level.
Artificial intelligence streamlines logistics with route optimization, demand forecasting, and automated warehousing, reducing costs.
Who is this book for?
Supply chain managers, logistics directors, and operations teams who need clear analysis of AI's impact on routing, forecasting, and warehouse automation.
How long is it?
It’s 339 pages (varies by edition).
What format is it available in?
Available as an eBook via Amazon (use the buy link on this page).
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