How AI Is Unlocking Hidden Capacity In Delivery Fleets

Highlights of Talking Logistics episode with Cyndi Brandt (Descartes) on how AI and machine learning are unlocking hidden capacity in delivery fleets, improving route density, and reducing costs.

Mar 31, 2026

If you operate a delivery fleet, the question is always the same: how do you deliver orders on time, undamaged, and at the lowest possible cost — with the fewest vehicles, miles driven, and drivers?

It’s a complex optimization problem with a lot of moving parts, which is why most leading fleet operators rely on route planning and optimization solutions. But as the operating environment continues to get more challenging, technology is also getting smarter. Advances in AI and machine learning are enabling companies to better understand the gap between what was planned and what actually happens in the field — unlocking hidden capacity and savings in the process.

So what does that look like in practice? I explored that question and its implications with Cyndi Brandt, VP, Fleet Solutions at Descartes, on a recent episode of Talking Logistics.

Rising Diesel Prices: How Are Shippers Responding?

Diesel prices are rising again — and quickly. As reported in the Wall Street Journal: “Diesel prices for U.S. truckers rose a record 96 cents a gallon this past week [25% increase], an ominous sign for retailers and manufacturers juggling tariffs and bracing for higher shipping costs following the U.S.-Israeli attacks on Iran.”

If elevated prices persist through the rest of 2026, how will shippers respond?

This survey explored the expected impact on transportation spend, the actions companies are most likely to take, how fuel surcharge programs are structured, and the biggest challenges in managing fuel price volatility.

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