Diebold Nixdorf redefines the role of AI in modern retail

Faced with labour shortages and rising customer expectations, retailers are turning to AI as a strategy for growth.

In Asia-Pacific, retailers are allocating investments in artificial intelligence (AI) to respond to labour shortages, rising customer expectations, and increasingly complex omnichannel operations. But as the technology matures, the conversation is shifting. Success is no longer measured by how much AI a retailer adopts but by whether that AI solves real business problems.

For Kristie Longhurst, General Manager Retail ANZ at Diebold Nixdorf, that distinction is what separates retailers seeing meaningful returns from those still experimenting.

“The AI earning its place in stores isn't the headline-grabbing kind; it's quietly solving practical everyday problems at the checkout, on the shopfloor and in the back office,” she said in a Retail Asia interview. 

Retailers are no longer pursuing large-scale transformation projects from the outset. Instead, they address specific operational challenges first, whether it is reducing checkout friction, improving loss prevention, streamlining payments, or helping employees manage growing workloads.

From AI ambition to business outcomes

One of the clearest signs of this shift is the way retailers now measure success. IDC research commissioned by Diebold Nixdorf found that 97% of Australian retailers link self-service technology directly to revenue growth, whilst 69% of Australian consumers prefer self-service as a leading checkout option. These findings suggest that retailers now view automation as a driver of business growth.

As Longhurst explained, “That’s significant because self-service was originally introduced as a way to manage labour costs. Today, leading retailers see it as a growth enabler.” 

This changes how technology investments are evaluated. Retailers are now looking at whether AI improves customer experience, increases revenue, and boosts basket completion, rather than how much labour it can save. The same thinking also reshapes the role of store associates.

Much of the conversation around AI has centred on automation replacing people. In practice, however, retailers are seeing greater value when AI supports employees instead of replacing them. Diebold Nixdorf refers to this approach as the “augmented associate.”

“In practice, it means AI takes on the repetitive, routine work, allowing the associate to focus on the work that requires human judgement, empathy and customer interaction,” Longhurst said.

As a result, customers benefit from faster and more seamless shopping journeys. Employees, on the other hand, spend less time monitoring routine processes and more time delivering meaningful service. Rather than choosing between operational efficiency and customer experience, retailers are increasingly using AI to improve both at the same time.

In global retail markets, the embedding of AI into operations has also translated into measurable results.  

At EDEKA Jäger in Germany, for instance, AI-powered age verification is used to automatically approve more than 80% of age-restricted self-checkout transactions within seconds, without storing customers' personal data. Meanwhile, at Intermarché in France, intelligent loss prevention technology reduced transaction anomalies from around 3% to under 1%, whilst staff interventions fell by almost 15% as shoppers self-corrected following the prompts.

Although the applications differ, they demonstrate the same principle that retailers achieve the greatest impact when AI is deployed to solve clearly defined operational problems. 

Building connected stores for long-term success

Longhurst underscored that solving individual operational challenges is only the first step. The next opportunity is in connecting those capabilities so they work together as part of a broader retail ecosystem. When checkout, payments, loss prevention, and customer experience systems share intelligence, retailers gain a real-time understanding of what is happening across the store. 

“The value of AI compounds when it is connected. A single AI tool solving one problem is useful, but its intelligence is limited to what it can see,” she said.

Longhurst added, “A standalone tool solves a point problem. A connected ecosystem gives you an operating model that continuously improves customer experience, operational performance and business outcomes.”

She also emphasised that trust must evolve alongside innovation. The AI-powered age verification at EDEKA Jäger embodies this principle because the technology completes transactions in seconds without storing personal data. 

For retailers looking to scale AI successfully, Longhurst advises beginning with the business challenge first before turning to the technology. Identify a clearly defined operational problem, measure the commercial outcome, then gradually connect successful initiatives into a broader ecosystem.

“Start with the problem, not the technology. The retailers who get the most from AI begin with a specific, well-defined operational challenge, such as a friction point at the checkout, a shrink issue or a queue problem, rather than with an ambition to ‘do AI.’”

For Diebold Nixdorf, the future of retail AI is about applying technology with purpose. Retailers that focus on solving real operational challenges, connect intelligence across the store, and keep customers and employees at the centre of every innovation will be best positioned to create lasting business value. 

AI has increasingly become part of everyday retail operations. In this landscape, success will belong not to those who experiment the most but to those who are able to turn technology into measurable outcomes.

To further explore the full findings, download Diebold Nixdorf’s IDC whitepaper, “The Evolution of Self-Checkout in Australia” here.