Field Guide: Practical AI In Logistics

AI is everywhere in logistics conversations. But most professionals we talk to feel the same way: overwhelmed, skeptical, and unsure where to start.

That’s why we built our new field guide, Practical AI in Logistics, 2025. It’s not about buzzwords. It’s about showing logistics leaders what actually works today, what’s still experimental, and how to take the first step without adding stress to an already overworked team.

What We Learned in Building This Guide

1. Logistics leaders are tired of hype.

Many of the companies we spoke with have been burned by “game-changing” technology promises before. They don’t want more jargon. They want clear answers to simple questions: Where does AI really help? What’s ready to use now? What should I ignore?

2. Three lanes of AI adoption are emerging.

As we mapped out use cases, the noise sorted itself into three categories:

• Everyday Fixes: cutting down paperwork and manual tasks.
• Smarter Predictions: spotting risks before they become costly problems.
• Guided Decisions: copilots that help people move faster without taking control away.

By framing AI this way, we found it became far easier for leaders to connect the dots between problems they face every day and the tools they could realistically use.

3. Starting small is the safest path.

No one needs to “transform their supply chain” overnight. The most successful teams start with a single workflow — invoices, ETAs, or exception triage — and measure results. Once the team trusts the output, they expand. This step-by-step approach avoids failed projects and builds real confidence.

4. Integration is the make-or-break factor.

Every conversation circled back to one point: AI is only as good as the data it can see. If systems aren’t connected, AI becomes another failed pilot. That’s why integration isn’t a side note — it’s the foundation.

Why This Guide Matters

Our customers told us they don’t have the time or IT resources to decode what’s real in AI. They want to solve problems in the real world: fewer SLA penalties, cleaner data, faster exception handling.

This guide is designed to do exactly that:

• Show which AI use cases are ready for production today.
• Highlight which ones to watch — and which to ignore.
• Provide practical “how to start” steps that don’t overwhelm already stretched teams.

Ready to See What’s Real?

AI can be valuable for logistics — but only if it’s applied in ways that solve today’s problems. Download the guide and see how to separate real-world use cases from marketing hype.