Around one in 11 Australian retailers had adopted artificial intelligence in 2024-25, lagging behind other industries.
This is revealed in new figures from the Australian Bureau of Statistics (AI), which show retail trade recorded a nine per cent AI adoption rate in 2024-25, placing it in the bottom third of all industries surveyed and below sectors including mining, health care and arts and recreation.
This sits oddly alongside the fact that retail is the most innovation-active industry in Australia, with 59 per cent of retail businesses reporting so to the ABS.
Across all industries, one in ten (12 per cent) of all businesses reported use of Artificial Intelligence (AI) in 2024-25, compared to just 1 per cent in 2022–23.
The subdued results in AI usage across retail come to light despite the sector generating continuous streams of transactional, behavioural and inventory data.
Kelly Slessor, founder of Tribe Gen AI and author of AI for Ecommerce, says the gap was less a reflection of reluctance than readiness.
"This is not a sector that needs to be convinced to change," she says. "It is a sector that needs to be equipped to use AI in practical, commercial ways."
Slessor adds that skills, not cost, is the primary blocker, further noting that the two are difficult to separate. Retailers that lacked the literacy to scope an AI use case could not build a credible business case, making every investment feel uncertain.
"Cost-benefit uncertainty is usually a symptom of the skills gap," she said. “If you do not understand what the tools can do, you cannot scope the opportunity. If you cannot scope the opportunity, every business case feels unclear.
“Once retailers build AI literacy, the cost-benefit conversation becomes much easier.”
As for the gap – with retail’s usage of AI of 9 per cent sitting far down from Information Media and Telecommunications (38 per cent), financial and insurance services (24 per cent) and mining (18 per cent) – Slessor offers two key factors.
The first is that retail has quite a long tail of small and micro businesses. Other data in the ABS dataset show that larger businesses are more likely to be using AI than medium and small businesses.
In recent years, many major retailers have onboarded key AI technology. The Iconic, for instance, uses the technology for a range of areas – inventory management, customer service, delivery, as well as how it ranks listings. One key push is multi-modal search, which allows customers to search for items without worrying about keywords. They can type in “beach-themed party outfits”, and the search engine knows how to respond.
Meanwhile, Kmart is accelerating its apparel product development cycle through AI, with managing director Aleksandra Spaseska flagging faster design-to-shelf lead times as a key driver of recent category growth. Youth apparel is the stand-out performer at Kmart thanks to this.
"Our youth apparel ranges continue to perform well, representing an increasing proportion of womenswear and menswear sales,” Spaseska says.
AI is now being embedded across the product design and quality lifecycle, including trend analysis, insight generation, and supplier collaboration, with Spaseska flagging that the business expects to move toward "even more agentic AI applications" over time.
Slessor says that the big chains and pure-play e-commerce brands are moving faster, but pointed out that they do not represent the average retailer. For thousands of small operators, she says, AI still feels abstract, expensive or like something that is only allowed for bigger businesses.
The other factor driving the AI usage gap in retail compared to other industries, according to Slessor, is that the number is “almost certainly” under-reporting what is really happening. She says that many retailers are using AI to generate product content, brief campaigns, personalise customer journeys, triage service tickets, forecast demand, recommend products, build audiences, or run a customer service agent. But many may not see this as “adoption”.
“Retail has the appetite to change. What it lacks is the infrastructure and skills to turn that appetite into AI capability,” Slessor says.
“Retailers are innovators by nature (new product launches, developing campaigns etc). They are able to spot customer shifts and respond quickly, but most of them didn't sign up to be technologists. They are less confident when the innovation requires data integration, automation, system architecture or AI literacy.”
Slessor says the big challenge here is that many retailers are spread so thinly in terms of resources. AI is a whole other job on top of business-as-usual, and the learning takes time.
The good news, Slessor says, is that AI usage does not require huge capital investment. She says the job is not always to buy something new, but rather to use the AI capability already inside the stack properly.
“The retailers making progress are not starting with giant AI transformation projects. They are starting narrow,” Slessor says.
“One workflow. One pain point. One measurable outcome.
“Actionable data insights. Product descriptions. Email segmentation. Campaign testing. Customer-service triage.
“Prove the value quickly. Build confidence. Then expand.”
Three years ago, Slessor says some of this work needed a data team and a six-figure budget. Today, she says, a lot of it can be done with the right tools, the right training and a clear use case.
“The capital barrier has come down. The capability barrier is what is left. And that is where retail needs to focus next.”