Over the past year or so, AI has gone from hype to mainstream. While previously emerging solutions gained column inches as a select few giants ploughed investment into them, numerous retailers are now edging forward in their AI strategy.
This shift – albeit a slow one – was borne out by our research this year. We asked the retailers we interviewed to rate their AI capabilities from one to 10, with one meaning AI is not used at all and 10 meaning the retailer uses it across multiple business areas.
Compared with last year, retailers feel further ahead. In this year’s research, 66% rate their business from one to five in AI capabilities, while 34% give it a rating from six to 10.
By contrast, the 2024 figures showed 75% between one and five and 24% between six and 10, indicating increasing AI adoption among retailers.
For those ranking themselves lowest on AI capability, the main challenges highlighted include high costs of adoption, limited training resources to effectively use tools and difficulty rolling out initiatives at scale.
The biggest areas of investment highlighted by the retail leaders we interviewed include: AI to improve ecommerce customer experience (including investment in personalised home pages, search functionality and chatbots); AI to support with data (through automation, efficiencies and surfacing key insights); and AI to enhance marketing across the board (from forecasting customer behaviour through to enhancing email campaigns and more).
In this chapter, we spotlight eight of the retailers we interviewed that are heavily investing in AI.
B&Q
Operational efficiency gains
Utilising AI across:
- Business efficiencies and cost savings
- Supply chain and sourcing
- Front-end customer experience website features
Chief executive Graham Bell says AI has become central to B&Q’s strategy. The technology supports a whole spectrum of functions from front-end features such as chatbots and visual search to back-end logistics such as Far East sourcing, freight load optimisation and property data analysis.
“AI is involved in a lot of less exciting stuff,” Bell explains, referencing how the company uses it for supply chain forecasting and shipload calculations. While customer-facing AI tools help shoppers find the right product or get help via chat, the major efficiency gains are found in operations.
B&Q has even established a dedicated team to identify emerging AI opportunities across the organisation. Bell adds: “It’s not the fancy selling stuff, but it’s practical stuff that helps you save money.”
With extensive AI use in HR, inventory, marketing and demand planning, B&Q exemplifies how traditional retailers can modernise from within.
“We’re very proactive implementing it,” says Bell, affirming that, while the tech may often be invisible to customers, its value is deeply felt across the business.
BrandAlley is using AI across multiple areas including chatbots and product recommendations (BrandAlley)
BrandAlley is using AI across multiple areas including chatbots and product recommendations (BrandAlley)
BrandAlley
A test-and-learn approach
Utilising AI across:
- Agile, adaptable innovation strategies
- Customer service (chatbots and call centres)
- Product recommendation and marketing
BrandAlley has taken a flexible, forward-looking approach to AI. According to chief executive Rob Feldmann, the company is consciously avoiding long-term investments in favour of agile, short-term integrations.
“You have to be quite careful… it may have to change again because it’s improving so quickly,” he says. In a rapidly evolving tech environment, 12 months can feel like a lifetime.
This philosophy has shaped BrandAlley’s AI deployment across multiple areas, including customer experience via chatbots and product recommendations, back-office functions such as warehouse automation and cybersecurity, and call-centre operations.
AI helps the retailer stay responsive to customer needs while avoiding the rigidity of legacy systems. Feldmann notes the importance of this adaptability as “we’re trying to do a lot of short-term deals in all the areas”.
This includes paid search optimisation, automated fraud prevention and AI-enhanced customer service. The result is a nimble business model ready to pivot with each wave of innovation.
Holland & Barrett
Cultural and technical change
Utilising AI across:
- Staff productivity tools
- Footfall analytics across its store estate
- Digital wellness app H&B&Me
Holland & Barrett is on a strategic AI journey. “We’re on the higher end of the scale, but we’re not at a 10,” says chief executive for wellness solutions Tamara Rajah. The retailer is trialling AI across numerous areas – customer service, product design, marketing and internal productivity tools – with a measured approach to full deployment.
“Where there are results, we are going further and deeper,” Rajah notes. This data-led mindset ensures that AI investments are outcome-focused rather than hype-driven.
The company is also exploring enterprise-level generative AI (such as GPT) to improve productivity and employee access to tech-driven tools. From automated hiring processes to warehouse robotics, the brand is embedding AI gradually but intentionally.
“It’s all so new. So it’s a combination of driving business results and getting colleagues to adopt it,” Rajah says, pointing to the importance of cultural change alongside technical change.
With AI playing a role in cybersecurity, personalised marketing and even product development, Holland & Barrett’s multi-pronged approach positions it for long-term gains. The company’s investment in training and adoption support reflects its belief in AI not just as a tool, but a future capability embedded in day-to-day work.
Collaborating with Kin + Carta, Matalan became the UK’s first retailer to launch a generative AI tool for large-scale website content (Matalan)
Collaborating with Kin + Carta, Matalan became the UK’s first retailer to launch a generative AI tool for large-scale website content (Matalan)
Matalan
Pushing the boundaries
Utilising AI across:
- Website navigation and product descriptions
- Forecasting models
- Automating replenishment
Matalan is pushing the boundaries of AI implementation, with a focus on both innovation and efficiency.
“We’re using it to write product descriptions and ‘walk our website’,” says chief operating officer Phil Hackney, likening the process to how a store manager might assess their floor. AI supports productivity on the back end too, by organising complex data, writing code and enhancing cybersecurity.
A standout achievement was Matalan’s collaboration with Kin + Carta, becoming the UK’s first retailer to launch a generative AI tool for large-scale website content. AI is also enhancing forecasting via models that account for weather patterns and store footfall.
“Each of these use cases is anchored in the same ambition: to improve productivity and pace,” says Hackney. In marketing, tools such as Salesforce Marketing Cloud use AI to automate customer communications, while advertising efforts leverage AI-powered audio content for real-time relevance.
On the logistics side, generative AI supports Matalan’s new replenishment system by speeding up development and improving automation. Systems like the Knapp OSR Shuttle use AI to make autonomous decisions, responding dynamically to their environments.
From bug scraping to product recommendations, AI has become integral to Matalan’s transformation.
Not On The High Street
Driving search and discovery
Utilising AI across:
- Product recommendation and search
- Shrinking developer workloads
- Back-end efficiencies
For marketplace retailer Not On The High Street, AI is a key lever for improving discovery and product matching. With more than 350,000 products on offer, surfacing the right item is both a critical challenge and an opportunity.
“Discovery is a key pillar for us,” says chief executive Jessica Nesbitt, who has led the brand’s investment in AI-powered search, browse and recommendation tooling. The business uses signals such as wishlists, cart additions and personalisation to track the impact of AI on customer intent.
Nesbitt describes the uplift as “huge optimisation gains,” helping to improve conversion deeper in the funnel.
On the tech side, AI tools assist developers in debugging code and speeding up releases, shrinking workloads that once took days into minutes. “It’s not marginal gains,” Nesbitt affirms.
However, the retailer is careful to protect its creative identity: “We’re not investing in AI to replace the creative elements. It doesn’t sit with our kind of ethos.” The company maintains a clear line, leveraging AI for scale and utility while preserving human artistry for branding and product visuals.
AI is also used to support HR and cybersecurity functions, but the company’s strategic focus remains on experience enhancement.
With AI powering both front-end personalisation and back-end efficiency, Not On The High Street is balancing technology with its values on this journey.
Not On The High Street is leveraging AI for scale and utility while preserving human artistry for branding and product visuals (NOTHS)
Not On The High Street is leveraging AI for scale and utility while preserving human artistry for branding and product visuals (NOTHS)
Pets at Home
A customer-focused future
Utilising AI across:
- Product development and design
- Customer experience and insights
- Saving time on administrative tasks
Pets at Home is determined not to fall behind. “Either you get on the bus or you miss the bus,” says chief operating officer Anja Madsen, who believes the retail industry is generally lagging in AI adoption.
The business has built a dedicated AI team within its tech function, focused on enhancing both productivity and customer experience. While early AI use centred on operational efficiency, the company is now shifting its attention to customer-facing innovation, including product development and personalisation.
“The future of AI is really more the customer-focused side,” says Madsen, emphasising opportunities in marketing, content and new product experiences. AI tools are already improving warehouse operations, scheduling, HR decision-making and forecasting, while also supporting call centres and in-store queries.
Madsen is optimistic about Pets at Home’s potential, thanks in part to its strong data foundation: “One of our USPs is our use of data. We’re actually in a great position to capitalise.”
With a commitment to proactive adoption and cross-functional implementation, the retailer is striving to go from follower to leader in the AI landscape. It’s not about adopting every trend, but ensuring every investment adds meaningful value – whether in store, online or behind the scenes.
The Very Group
Accelerating digital transformation
Utilising AI across:
- Personalisation engine – Sigma IQ
- Accelerating digital transformation
- Supporting decision-making
At The Very Group, AI is being used across both retail and financial services.
“Forecasting, credit decisioning and then our personalisation engine, Sigma IQ – that’s our bleeding edge,” chief executive Robbie Feather explains. Sigma IQ represents Very’s latest advancement, using AI to drive more refined personalisation and dynamic content delivery.
Beyond marketing, Feather sees significant potential for AI to “make tech projects easier,” especially in helping retailers migrate from outdated legacy systems. With AI accelerating digital transformation, Very is positioned to reduce the time and cost of system overhauls, an ongoing challenge for the industry.
The business also applies AI in merchandising, pricing optimisation and predictive inventory management. These applications enable more responsive operations and better alignment between product availability and demand.
Feather believes AI has the potential to deliver a “giant leap” forward in the retail sector, not just in customer experience but also in internal processes and infrastructure.
As a business with roots in both remote selling and credit, Very demonstrates how AI can serve multiple verticals, enhancing agility and improving decision-making across the board.
The Very Group demonstrates the potential of AI for both retail and financial services (Very)
The Very Group demonstrates the potential of AI for both retail and financial services (Very)
Wickes uses AI learning for its TradePro scheme, a tailored offering for professional customers (Wickes)
Wickes uses AI learning for its TradePro scheme, a tailored offering for professional customers (Wickes)
Wickes
Balancing ambition and pragmatism
Utilising AI across:
- Trade loyalty programme
- Automation and warehouse robotics
- Enhancing customer journeys
For Wickes, AI is an increasingly central part of operations and customer strategy. Chief executive David Wood says the retailer has strong uptake in customer-facing tools and operational systems.
“We have very advanced AI machine learning, particularly our TradePro scheme,” Wood notes, referring to Wickes’ tailored offering for professional customers.
The company uses AI to optimise everything from campaign targeting and merchandising to automated recruitment and warehouse robotics.
Wood summarises Wickes’ AI approach with three guiding questions: “How does it help me improve the customer experience? How does it help me run the business to be more operationally efficient? And how will customers continue to use AI to shop?” This triad has guided investments in advertising, personalisation and supply chain forecasting.
AI is also embedded in HR systems to support inclusive hiring and workforce management. Meanwhile, cybersecurity tools powered by AI provide early threat detection and help enforce best practices.
Wickes’ AI usage balances ambition with pragmatism, focused on enhancing customer journeys, reducing inefficiencies and anticipating how shoppers will interact with technology in the future. “It brings you full circle back to making sure you’re using it to enhance the customer experience,” Wood says.