Artificial Intelligence in Logistics: Transforming Supply Chains for Efficiency and Sustainability

Who this book is for

• Curious readers who want a grounded view of Artificial Intelligence in Logistics without the applause soundtrack.
• Operators, managers, and curious readers who want to know whether AI in transportation improves the workflow or just adds another dashboard to ignore.
• Anyone who wants clear context on where AI is already being used in transportation today — and where routing models hit warehouse floors before they trust the louder claims.
• Readers looking for sharper judgement on the useful detail sits here: routing logic, stock flow, and timing rather than recycled buzzwords.

Key themes

• Transportation
• Artificial Intelligence
• AI Trends

What you’ll learn

• Where AI is already being used in transportation today — and where routing models hit warehouse floors.
• The useful detail sits here: routing logic, stock flow, and timing.
• Key themes including routing, prediction, safety, operations.
• The limits, risks, and awkward questions worth asking before you sign off on the sales pitch.

Audience fit

Best for people weighing real adoption choices in Logistics. It is written for operators, planners, analysts, product teams, and readers tracking mobility systems who want practical context rather than brochure copy.

Deeper overview

Artificial intelligence streamlines logistics with route optimization, demand forecasting, and automated warehousing, reducing costs. This one stays close to the hard realities inside Logistics, especially where routing models hit warehouse floors.

Why this title is useful in practice

In practice, Artificial Intelligence in Logistics: Transforming Supply Chains for Efficiency and Sustainability is most useful when the real issue is the point where promised efficiency in transportation meets maintenance logs, handovers, and failure modes. It is written for readers who want a grounded, non-technical view of AI in Logistics, including operators, planners, analysts, product teams, and readers tracking mobility systems, and it tackles questions such as where AI is already being used in transportation today — and where routing models hit warehouse floors., which makes it more useful than a generic explainer when someone has to decide what happens next in an actual workflow, classroom, policy setting, or team.

Practical outcomes

You should finish it with a clearer feel for where AI in transportation improves the workflow, where it adds fragility, and what to pilot before anyone starts chest-thumping.

• Understand why transportation matters now and what the evidence actually says.
• Assess whether transportation is applicable to your context before committing resources.
• Ask the right governance and implementation questions before adoption decisions become expensive.

Chapter-level signals

What makes this title distinct

Artificial Intelligence in Logistics: Transforming Supply Chains for Efficiency and Sustainability keeps its boots on the ground, looking at workflow, failure modes, and whether the gains survive contact with real operations in transportation.

Because decisions in Logistics affect safety, throughput, reliability, and emissions. Once AI enters the loop, sloppy assumptions get expensive very quickly.