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AI shopping tools saving retailers time and money
Retailers are using AI shopping tools to streamline operations, improve customer journeys and find new revenue opportunities across ecommerce.
Retailers are using AI shopping tools to streamline operations, improve customer journeys and find new revenue opportunities across ecommerce.
The retail sector continues to be affected by the ongoing cost-of-living crisis.
As inflation remains stubbornly high, prices continue to rise, and hard-up Brits no longer have the disposable income they enjoyed before the pandemic.
The Commons Library reports that 60% of UK adults who experienced a rise in the cost of living cut back on non-essentials, a figure that climbs to 76% among disabled people.
For retailers, the picture is stark. Declining sales, squeezed margins, and closures continue to affect the high street.
As businesses search for ways to improve efficiency and cut costs, AI in ecommerce is emerging as a lifeline rather than a luxury.
There is still huge scepticism over the growing influence of artificial intelligence. Perhaps Hollywood is to blame for visions of robots taking over the world.
Today’s AI tools are not here to replace people, they’re here to give retail teams back time and resources.
Integrating AI into ecommerce strategies is about redefining how you work. It’s about understanding how automation can speed up routine tasks, so your people can focus on creating better customer experiences.
And with the UK AI in retail market forecast to grow from $310.7 million in 2023 to $3.55 billion by 2032 (an annual growth rate of 31%), adoption is no longer optional. Retailers who fail to invest risk being left behind.
But adopting AI isn’t about keeping up with the market. It’s about knowing how to use these tools effectively to deliver both efficiency and value.
More reading on AI in retail:
Using AI effectively is about supporting the customer journey at every stage of the funnel. Not just cost cutting.
A clumsy chatbot or irrelevant recommendation can drive shoppers away just as quickly as poor in-store service.
Every technical integration needs to be designed from the customer’s perspective:
When deployed thoughtfully, AI boosts conversion rates and delivers ROI. Retailers using AI-driven pricing achieved around 10% higher sales during peak trading seasons.
Those questions highlight a core challenge. Retailers need to decide whether AI should serve internal goals or customer-facing ones.
The truth is, it can and should do both.
It shouldn’t be an either/or choice. The most successful AI investments are those that simultaneously enhance customer experience while streamlining internal processes.
Thanks to the explosion of plugins for Shopify, Salesforce, and other platforms, AI shopping tools are now accessible even for smaller retailers with limited budgets.
This shift is part of a broader move toward plug-and-play retail tech stacks (known as composable commerce) that let retailers build flexible, efficient systems.
With that balance in mind, let’s look at how retailers are applying AI directly to the customer journey.
One of the first areas where AI is proving its value is content creation, especially when it comes to managing product catalogues at scale.
Manually writing product descriptions is time-consuming, particularly at scale.
Generative AI tools such as Shopify Magic can create product copy and add AI image editing to the platform.
Zalando are already testing AI-driven tools to improve product discovery, using large language models and generative AI to explore new ways of guiding customers to the right styles and products.
These experiments suggest that AI-enhanced search could evolve into even more personalised digital shopping assistants soon.
Customers aren’t averse to CGI if it serves a purpose.
AI-driven 3D imaging allows shoppers to interact with products virtually, understand dimensions and textures, and visualise big-ticket items in their homes.
This reduces uncertainty, cuts return rates and builds trust.
Virtual commerce assistants can answer common questions in real time, freeing human teams to focus on complex issues. The value lies not just in automation; it’s in the insights.
Retailers can identify recurring pain points and optimise their CRO strategies by reviewing interactions.
ASOS uses AI-powered personalisation and sizing engines (e.g. “Fit Assistant”) to recommend the best size, surface relevant products via “Your Edit” or “Style Match,” and test generative AI arms to improve customer discovery and make returns less likely.
Today’s customers expect search bars to understand them.
Natural language processing (NLP) helps systems interpret intent, informal phrasing, and even slang.
Pairing this with personalisation allows retailers to deliver exactly what the shopper is looking for.
Many shoppers browse online with the aim of later buying in-store – or research online, purchase offline (a trend known as ROPO).
AI can enhance the ROPO journey by improving product search, personalisation, and localised inventory syncing. This makes it easier for customers to research online and then conveniently purchase in-store.
While front-end tools often grab the headlines, retailers see some of the most powerful results when AI reshapes what happens behind the scenes.
Behind the scenes, some of the most powerful gains are happening in logistics and operations, starting with supply chain optimisation.
AI predicts demand patterns, manages inventory levels, and flags potential disruptions before they happen. This minimises stockouts and overstock, protecting margins while supporting sustainability goals.
Tesco has already rolled out AI-powered supply chain visibility tools to improve stock accuracy and reduce dwell time in distribution centres.
From fulfilment to finance, AI can map workflows, spot bottlenecks, and suggest adjustments.
Over time, these small efficiencies add up to significant time and cost savings.
By analysing customer behaviour and market trends, AI helps teams design and launch products faster.
Importantly, human oversight remains crucial to ensure data-led decisions align with real-world trends.
Unilever recently revealed that its ice-cream supply chain uses AI and weather data to improve forecast accuracy by 10%, cutting waste while maintaining stock availability.
AI is already widely used in marketing automation, powering tailored recommendations, discounts, and promotions.
As these tools become more sophisticated, they allow retailers to deliver hyper-relevant campaigns that feel one-to-one rather than mass-produced.
So, which AI shopping tools are available to retailers, and how do they fit into different budgets and business sizes?
Here are some of the leading AI shopping tools that retailers are using today.
Adoption trends:
SMEs: 46% of small UK retailers experimented with AI shopping tools in 2024 (up from 28% in 2022).
Enterprises: Over 80% of large UK retailers now use AI in some form, with fraud prevention and personalisation leading adoption.
Beyond today’s established tools, new applications of AI are emerging that will shape the future of retail.
Let’s look at three areas where AI is shaping the next phase of ecommerce innovation.
88% of UK marketers say they now use AI to speed up content production or analytics. Companies using AI attribution to analyse which campaigns work best are seeing between 15% to 30% improvements in marketing ROI.
In Q1 2025, 35% of UK businesses reported being targeted by AI-related fraud, up from 23% the year before. AI tools are being deployed to detect synthetic identities, spot deepfake scams, and flag suspicious transaction patterns. They are helping retailers protect revenue without compromising checkout experience.
AI is driving both profit and purpose. A recent study found that among top retailers, AI adoption boosted profits by 39% and revenue by 31% while cutting carbon intensity by 21%. AI optimises delivery routes, reduces overstocking, and helps meet ESG pledges.
Investing in AI isn’t about choosing between customer experience or internal efficiency.
With the right tools, retailers can achieve both.
Far from replacing people, AI empowers them. It allows teams to serve customers better, make faster decisions, and run leaner operations.
With the AI ecommerce market already valued at $9.65 billion and growing nearly 19% year on year, it’s clear this isn’t hype, it’s the direction of travel.
Retailers who adopt now will not only survive but thrive, setting the pace in an increasingly competitive market.
Here are some of the most common questions retailers ask about AI in ecommerce and AI shopping tools.
AI in ecommerce uses machine learning and automation to improve retail. Common tools include product recommendations, chatbots, fraud detection, predictive pricing, and personalised marketing.
For SMEs, Shopify AI (Shopify Magic + Sidekick) offers product content generation and demand forecasting. Larger retailers often use Salesforce Einstein GPT and predictive analytics platforms like Dynamic Yield and Adobe Sensei.
AI tools monitor transactions in real time, flag suspicious activity, and reduce false declines. In Q1 2025, 35% of UK businesses were targeted by AI-driven fraud, highlighting the need for AI fraud prevention systems.
Tesco uses AI to improve supply chain visibility and reduce dwell time in distribution centres. Unilever applies AI forecasting in its ice-cream business, improving accuracy by 10% and cutting waste. ASOS has implemented AI fit finders and style recommendations to reduce costly returns. Zalando launched a generative AI fashion advice tool to enhance customer engagement.
Yes. AI pricing tools lifted peak season sales by ~10%, while the AI ecommerce market is growing nearly 19% year on year. The tools deliver ROI through higher conversions, reduced returns, and operational efficiency.
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