AI in Supply Chain: Hype or Reality?

AI is everywhere—at least, that’s what vendors want you to think. From buzzword-filled sales decks to overhyped feature lists, “AI-powered” has become the label slapped on anything remotely data-driven. But is it truly artificial intelligence—or just good old data analytics in a shiny wrapper?

In last-mile logistics, for example, AI can’t predict when a driver will pull a no-show, blow a tyre, or run into unexpected delays—because at the end of the day, no amount of historical data can account for the unpredictable nature of real-world events.

In this article, we will dive into the difference between AI and data analytics, the future of AI in last-mile delivery, and the importance of people.

What’s the Difference Between AI and Data Analytics?

In the logistics world, data analytics and AI often get thrown into the same basket, but they’re fundamentally different tools with distinct capabilities.

The difference!
Data analytics looks at historical and real-time data to identify trends, inefficiencies, and opportunities. It’s about understanding what has happened and what is happening right now.

For example, a logistics provider might use analytics to spot recurring delivery bottlenecks, identify high-risk routes, or forecast peak demand periods based on past performance.

AI, on the other hand, goes beyond analysis. It uses machine learning algorithms to make autonomous decisions and continuously improve based on new data. In theory, AI should be able to predict future disruptions and dynamically adjust operations without human intervention.

Example: Take route optimisation as an example. A solid data analytics engine can assess historical delivery times, traffic patterns, and operational constraints to suggest the most efficient delivery routes. A system labelled as “AI-powered” might claim it can predict future disruptions, but can it really? No algorithm can foresee a driver calling in sick at the last minute, an accident that stops traffic or road closures caused by weather events throwing everything into chaos.

Take navigation services as an example.

Google Maps provides a route and eta based on historical data, whereas Waze will provide real-time traffic updates. Does that mean Waze is AI? It may be mistaken as AI, but no, Waze utilises crowd-source data to update their navigation with information provided by users.

The importance of people

The bottom line – AI has a place but don’t fall for all the hype or the misused terminology..

When it comes to real-time, last-mile execution, the real magic still lies in smart, data-driven decision-making—and often that comes from digitising your supply and empowering your people with data analytics, not AI.

At the end of the day, your workforce—warehouse managers, dispatchers, logistics managers and drivers are the real differentiators. They’re the ones adapting to last-minute disruptions, making judgment calls in high-pressure situations, and ensuring deliveries reach the right place at the right time.

So, if there is anything you take from this article, it’s this:

• AI is often just data analytics with a pretty label.

• The real magic is in digitisation and empowering your people

Want to see how real-time insights and data—not buzzwords—can transform your last-mile operations? Contact Radaro here or via email at support@radaro.com.au.