The next customer on your website won’t be human

A profound shift is underway in how people shop online with retailers at the forefront of a new era in which AI agents will browse, compare and buy on behalf of consumers.

No longer will online shopping always begin with a person typing into a search bar, scrolling through product pages and opening multiple tabs to compare price, delivery and reviews.

Increasingly, a customer will simply tell an AI assistant what they need: a bedroom setup for a small apartment, a birthday gift that can arrive by Friday, or the best-value appliances for a renovation. The AI will then do the work a shopper would normally do themselves.

It will search, compare, ask questions, check stock, assess delivery windows, look at returns policies and, with the customer’s approval, complete the purchase.

While the 25-year-old web was built for human eyes, the next version will also need to be built for machines that can read, understand and act.

For retailers, this means the website can no longer be treated as merely a digital shopfront. To remain competitive, retail websites will need to become operating systems that AI agents can interrogate in real time.

If an AI agent cannot understand a retailer’s website, cannot trust its stock position, cannot work out whether a product can be delivered by Friday, or cannot complete a transaction easily, it will simply move on.

That is the key commercial risk facing Australian retailers today. Being invisible to AI agents will become as damaging as being invisible on Google search once was.

From being found to being understood

For years, retailers have focused on making their websites easy to find. The next challenge is whether an AI agent can understand what a retailer sells, what is genuinely available, how quickly it can be delivered, what it will cost, and whether the business can keep that promise.

A human shopper may tolerate vague delivery windows or inconsistent stock information. An AI agent will not. It will compare retailers quickly and favour those that provide clear, structured and reliable answers.

It means the most important aspects of a retail website will no longer be the visible front-end - it will be the systems and protocols that sit underneath: catalogue data, inventory, pricing, warehouse capacity, delivery logic, returns rules and payment pathways.

In the agentic AI era, operational truth becomes a customer experience issue.

This is not a plug-in problem

Many retailers will be tempted to treat this as another technology integration: add an AI tool, connect a new channel, build a chatbot, or put an AI layer over the existing website. But this profoundly misunderstands the scale of the change.

AI agents do not need a cleaner product page. They need to know whether the information reflects reality. Is this exact product available in this size and colour? Can it be delivered to Hobart by Friday? What happens if the customer wants to return it? Can the transaction be completed without the process breaking?

If catalogue, inventory, warehouse, freight and checkout systems do not speak to each other, the AI agent will receive incomplete or unreliable information. That creates risk for the retailer and frustration for the customer.

Retailers cannot bolt agent-readiness onto a legacy system and expect it to work. They will need to re-engineer their digital operations so AI agents can interact with them accurately, safely and in real time.

This is where Australian e-commerce has a structural advantage. Operating at scale across this geography (long lanes, dispersed population, high freight cost, demanding service expectations) has forced a greater level of supply chain discipline.

The companies that have survived and grown here have done so by being exceptionally good at inventory, demand planning, and fulfilment fundamentals. That muscle, it turns out, is exactly what the agentic era rewards.

What New Aim has been building

At New Aim, we have spent more than 20 years building technology to support complex ecommerce operations in Australia. Our investment in our proprietary tech stack makes the current shift an opportunity rather than threat.

We have built our own forecasting and demand planning stack with AI integration as the actual decision substrate, rather than the marketing layer. Sales and budget forecasting that ties to live cash flow. Warehouse capacity and S&OP planning that thinks in CBM, not just units, across multiple sites.

A model tuning workbench that lets buyers and marketing specialists inject qualitative signals - this supplier is going to miss; this category is heating up; this NPD will cannibalise - into quantitative forecast adjustments, with a human-in-the-loop confirmation step before anything writes to plan. A natural-language data agent that lets a planner ask, in plain English, why a sub-category’s Days Of Stock slipped and get a sourced answer back in seconds.

This capability was built to meet the demands of running a serious supply chain in Australia at scale. Our AimCore platform is the AI-native operating layer that runs forecasting, planning, sourcing and fulfilment across our business, streamlining information for external agents through a single layer rather than multiple legacy systems.

We have now begun productising that layer for the broader retail ecosystem under the brand AirOxy. The operational depth that took us years to build inside New Aim is exactly the kind of substrate that an agent-readable storefront needs underneath it: fast, honest, structured answers about what we actually have, what we can ship, and what we will have next month. It is the infrastructure other operators, channels, and AI surfaces will need access to as agentic commerce scales. AirOxy is how that substrate becomes available beyond our own four walls.

AimCore and AirOxy are not competitors to the marketplaces and channels we work with. They are the inventory and intelligence backbone that lets a marketplace, a search surface, or a third-party agent rely on our data and our promises. 

For Australian retailers, the impact of agentic AI is not to be underestimated. Showing up accurately and reliably on the new system of commerce is critical for future success, and ensuring back-end infrastructure can be read and relied upon by AI agents is a far more challenging engineering problem than most retailers realise.