A lot of things happened on 30 November 2022.

It was the day that the House of Representatives voted to censure former Prime Minister Scott Morrison over a portfolio of secret appointments.

It was the day Australia beat Denmark 1-0 in the World Cup Group Stages. 

And it was the day ChatGPT was launched.

The world hasn’t been the same since, and it wasn’t because of Matthew Leckie’s goal in the Socceroos’ plucky victory.

Over the last three-and-a-half years, “AI-powered” has become to logistics leaders what “artisanal" is to bakers. It gets attached to everything. Your WMS vendor just shipped it. Your ERP has it. And. Every. Cold. Email. In. Your. Inbox. Has. It. Too. (We know that, because we receive a lot of those emails too).

The hard part isn't deciding whether to invest in AI, it’s knowing where to invest, and why.

In this week’s Delivered, we look at four questions to help you do exactly that.

TL;DR

• 62% of retailers say AI is the biggest trend in 2026. The opportunity is real, but so too is the fear of backing the wrong horse.
• The retailers pulling ahead aren't using more AI tools; they're using fewer but better-integrated tools, tied to clear answers to strategic questions.
• Four questions to ask before your next AI investment: What do our customers actually want? Where does our team lose the most time? Do we have the right data? Will it get smarter the longer we use it?

The AI arms race

Two in three retailers (62%) say AI is the biggest trend they're watching. AI and automation is also the second biggest investment focus for retailers in FY26. The investment intent and the opportunity is real, but so too is decision paralysis and the pressure to invest smartly. 

There was once a day where your CFO only got involved in the biggest deals. Today, they’re more hands on, scrutinising every decision and every investment. Even those that they would’ve let Jake in accounts sign-off on before. 

That scrutiny cuts both ways. Move fast without direction and things become expensive quickly. But move too slowly, and the opportunity might pass or the margin pressure becomes too great.

The retailers who will look back on 2026 as the year they pulled ahead aren't necessarily the ones who bought the most AI tools. They're the ones who were disciplined about 1) why they bought them and 2) where they applied them.

The difference between an AI investment that transforms your operation and one that misses the mark is the questions you ask before signing a contract.

1. What do your customers actually want?

If you’ve been in any vendor demo recently, you know that they (and you) typically get starry-eyed about the most technically impressive capability in the technology stack.

You know the one; the ‘full bells and whistles’ feature that apparently solves everything, but neither you nor the vendor can properly explain what it actually does.

Many of these features are genuinely exciting, but does it do what your customers want? So start there, with the customer outcome. 

Think about what’s driving cart abandonment, for example.

According to Shippit research, 68% of shoppers say that seeing an accurate delivery date before they buy is essential or very important, and 38% say it makes them more likely to complete the purchase. 

Yet only 7% of retailers currently offer it at checkout. That’s not just a big gap, it’s cavernous. 

A customer who doesn't know when their order will arrive is a customer who might not order at all. AI-powered estimated delivery dates calculated on real carrier performance data - not a vague ‘3-7 business day’ window - close that gap directly. 

So the first question to ask isn't just ‘what's the most advanced AI investment available?’. It's ‘what's the AI investment that most directly helps my customers today?’.

2. Where does our team lose the most time?

The second most powerful question is an internal one: What parts of your logistics operation are smart, capable people spending time on that shouldn't require smart, capable people?

Carrier selection that runs on intuition and historical averages. Manual exception handling when a delivery goes off-script. WISMO tickets that land in the support queue because a customer couldn't find a real-time update.

For most mid-to-large retailers, these are the daily rituals within a fulfilment operation. And they represent the clearest ROI case for AI investment.

AI investments should shift what teams spend their attention on: decisions that need human judgment, carrier relationships, and work that is revenue-generating, strategic, and fulfilling at the same time. 

Before your next demo, write a short list of where your team spends time unnecessarily, then treat that as your starting point.

3. Do we have the data and structure in place?

According to Shippit research, two in three retailers rarely or never use their delivery data to optimise operations, reduce costs, or improve delivery experiences. 

Every AI investment runs on the quality of the data beneath it. The better data you feed it, the better the results. 

But data quality is only half the equation. The other half is whether your systems are actually connected. 

An AI tool that can’t talk to your OMS, your carrier platforms, or your warehouse management system because there isn’t an API isn’t augmenting your operation, it’s running in isolation.

An AI investment built on incomplete, inconsistent, or siloed data produces incomplete, inconsistent results.

So before you invest, ask honestly: is our data clean, accessible, and connected to the workflows and processes that actually matter?

If the answer is yes, you're ready. If it's not, don't spend money on the fixtures and fittings before you've poured the concrete.

4. Will it get smarter the longer we use it?

Not all AI is created equal. The distinction that matters most for long-term ROI is whether the system learns from your data over time, or whether it runs the same off-the-shelf logic it landed with. 

A static forecast built on last year's sales history has value. A model that continuously weighs current signals - order volumes, promotional calendars, seasonal anomalies, macroeconomic trends - and updates its forecasts on a week-by-week basis has far more tangible value. 

When you're evaluating an AI investment, ask what it will know about your operation in twelve months that it doesn't know today. Ask whether its performance data is available to you. Ask if it scales and adapts as your business does. 

The best AI investments in logistics aren't set-and-forget. They're built to learn, iterate, and improve. That's what makes them worth the line item, and justifies your CFO’s involvement in the procurement process.

Before you book your next demo

Four questions are a starting point, not a finish line. 

A few things worth working through before you commit to the demo:

1. Map your customer's purchase journey to determine where delivery uncertainty creates churn. What other needs are you failing to deliver on?
2. List the top three tasks your ops team does repeatedly that feel like they shouldn't require human input.
3. Ask how the platform performs on your specific carrier mix and route profile, not just aggregate benchmarks.
4. Request performance data over time, not just at point of sale. Does the product improve with use?
5. And ask yourself, are we investing in a tool that our data will do justice?

The retailers who will look back on the AI arms race as transformative aren't the ones who moved fastest. They're the ones who moved strategically; with the most clarity about what their customers needed, where their operations were leaking, whether they had the right foundations, and which tools were actually built to get better over time.

The better your questions today, the stronger your results tomorrow. 

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