Meet the adaptive AI adopters: how 10 UK retailers are turning AI into growth

Adaptive AI is no longer confined to labs and pilot projects. Across the UK, leading retailers are quietly combining adaptive, traditional and generative AI to rethink everything from warehouse safety and search relevance to stock forecasting and customer acquisition. This question-led guide introduces 10 “adaptive AI adopters” and shows how they are using machine intelligence to deliver real commercial impact.

Who are the adaptive AI adopters in UK retail?

Adaptive AI adopters are retailers that use AI systems which learn continuously from new data and adjust decisions in real time. Rather than relying on static rules, these brands let algorithms optimise for changing conditions across channels, products and customer journeys.

In the UK, standout adaptive AI adopters include Boots, B&Q, Charles Tyrwhitt, John Lewis, Marks & Spencer, Next, THG, The Very Group, Specsavers and Ocado. Each is blending AI with human expertise to improve efficiency, reduce waste and create more relevant customer experiences.

How is Boots using adaptive AI to transform warehouses and customer journeys?

Boots is using AI as part of a major warehouse transformation and across multiple digital touchpoints. In its Burton-on-Trent site, around 150 small “co-bot” robots move stock around the warehouse, avoiding colleagues and reducing the need for manual carrying. This has cut accidents and created a safer, more efficient environment.

The retailer is also trialling an AI-powered robotic arm from Knapp to pick products quickly and carefully, learning from experience as it goes. Online, Boots’ search now uses adaptive AI to personalise results based on live data such as stock levels, trending shades and customer preferences. Forecasting models feed in external signals like weather to predict sales more accurately.

On the customer-facing side, Boots is testing a ChatGPT-based chatbot to answer conversational questions such as “How do I develop a skincare routine?”, recommending relevant products while also trialling similar tools for internal HR and procedural queries. AI is also being used to optimise advertising placements and even to create elements of its 2023 Christmas campaign imagery.

How is B&Q applying AI to personalisation, pricing and retail media?

B&Q’s AI strategy is centred on making its vast assortment easier to navigate and its marketing more precise. With around 1.2 million products available through its marketplace, adaptive AI helps connect data across multi-channel touchpoints to understand behaviour and respond with personalised communications in real time, from direct marketing and emails to coupons at the till.

AI-powered pricing is a key focus at group level for Kingfisher. Models help manage markdown and clearance pricing, forecast demand and inform supply decisions, freeing staff to interpret and act on the insights rather than spend time on manual administration.

B&Q has also built Athena, an in-house orchestration framework for AI, to integrate multiple technologies and adopt new tools quickly. This includes a Kingfisher-built recommendation engine that has delivered higher click-through rates, better add-to-basket performance and faster response times. The retailer is also part of Microsoft’s Early Access Programme, trialling generative AI to understand where it can best enhance productivity.

How is Charles Tyrwhitt using adaptive AI to optimise acquisition and inventory?

Charles Tyrwhitt, which generates over 80% of its sales online, uses adaptive AI to improve search targeting and make better use of its large product range. By analysing market and performance data in real time and cross-referencing it with inventory, adaptive AI ensures the right products are promoted to the right customers at the right moment.

Working with Upp.ai’s retail inventory and intelligence solution, the brand has reduced the cost of acquiring new customers in the UK and US, increased daily Google Shopping spend per customer and surfaced product lines that were previously underexposed. By focusing on questions such as the probability of a sale, the cost of each action and likely efficiency, adaptive AI has helped uncover overlooked inventory and customers.

This has translated into significant gains, including a reported 60% sales uplift in the US, 40% in the UK and a 74% reduction in customer acquisition cost. A live dashboard lets teams track performance, while the AI continues to learn and optimise against targets and thresholds set by the business.

How is John Lewis investing in AI across customer experience and logistics?

John Lewis is placing AI at the heart of its turnaround and modernisation plans. It is investing heavily in its technology stack, including a multi-year programme focused on improving online navigation, personalisation and overall customer experience.

A notable example is its partnership with AI-powered imaging company Zyler, which allows customers to virtually try on rental outfits by uploading a photo and clothing size. Within three months of launch, the rental arm saw a 30% uplift in sales, with customers engaging enthusiastically with the virtual try-on service.

John Lewis has also committed £100m to a Google Cloud partnership to enhance its AI capabilities and has signed a deal with Locus Robotics to deploy AI-driven autonomous mobile robots in its Milton Keynes warehouse. These robots work alongside human colleagues to move products more efficiently and remove the need for workers to push heavy trolleys or lift boxes.

How is Marks & Spencer using AI in stores and the supply chain?

Marks & Spencer is applying AI to both front-of-house operations and its wider supply chain. Through a partnership with SymphonyAI, M&S uses AI to compare real shelves with digital planograms, helping colleagues place inventory where it will perform best and flagging items that need replenishment. This shelf-edge technology combines camera data, sales performance and warehouse stock information to guide store teams.

In the supply chain, M&S has partnered with Relex to improve food forecasting. The system blends internal sales data with external signals such as weather patterns to predict demand, reduce waste and improve availability. New forecasting, ordering and stock allocation systems have already been rolled out across a majority of food categories.

The retailer is also investing in people. It has launched what it describes as the first data science and AI academy in retail, training colleagues in machine learning and related skills as part of a wider push to make M&S a leading destination for retail and technology careers.

What is Next doing with AI and its Total Platform?

Next has more than doubled its technology spend over five years and almost doubled the size of its tech team, now employing more developers than product staff. While not all of this investment is AI-specific, the retailer is using AI across forecasting, sales data analysis and stock planning to decide what to re-stock, when and where.

Chief executive Simon Wolfson has highlighted both adaptive and generative AI as priorities. Generative AI is being used to draft customer communications, helping teams write thousands of clearer, more helpful emails to address queries and direct customers towards the right solutions.

Next’s broader technology strategy includes its Total Platform, which powers the ecommerce and logistics operations for brands such as Cath Kidston, JoJo Maman Bébé and Reiss. As Total Platform grows and is forecast to add tens of millions of pounds to group profits, AI is expected to play an increasing role in spotting patterns, managing complexity and scaling service for partner brands.

How is THG combining adaptive and generative AI across its business?

THG has been using AI since 2016 and now treats it as its top investment priority. It blends generative AI with machine learning and adaptive models to support revenue growth and operational efficiency across its portfolio.

On customer-facing sites such as Coggles, AI-powered recommendations and an Outfit Builder tool suggest curated looks, boosting engagement and sales. Natural language processing improves search so that conversational queries like “sunburn” surface relevant products such as sun creams.

Adaptive AI helps THG build richer customer profiles, incorporating journeys, add-to-basket behaviour and purchases, and predicting lifetime value. Behind the scenes, AI supports machine translation of product copy, fraud and anomaly detection, and profanity filtering in more than 78 languages.

One standout use case is influencer revenue forecasting. AI models predict the revenue that potential influencers might generate, enabling more objective selection and improving return on marketing investment. Throughout, THG emphasises the need for human refinement to maintain quality, authenticity and brand voice.

How is The Very Group using adaptive AI for forecasting and search?

The Very Group is focusing its AI efforts on stock forecasting and customer search. In partnership with Amazon Web Services, it uses AI for time series modelling and seasonality profiling, improving stock level forecasts and product availability, especially around peak trading periods like Black Friday and Christmas.

For on-site search and recommendations, The Very Group uses an AI system from Constructor that learns intent and promotes the most relevant products to the top of search and browse results. Applied across search, browse and recommendation areas, this adaptive approach effectively re-merchandises the range in real time as customer behaviour changes.

AI and machine learning are central to the group’s strategy for understanding who is shopping, how they shop and how best to serve them, from inventory management to marketing and payment options. Alongside technology investment, The Very Group is actively upskilling employees with new learning and tools to help them work alongside AI effectively.

How is Specsavers using AI to drive appointments and marketing effectiveness?

Specsavers has been experimenting with AI since at least 2018, when it launched Frame Styler, an iPad-based virtual try-on tool that helps customers see how glasses will look on them. The retailer has also invested in data-driven marketing effectiveness, partnering with Ekimetrics to centralise and continuously update marketing data across channels.

This centralised data allows marketing teams to plan spend, forecast returns and refresh models more frequently, supporting a more rigorous effectiveness culture. AI is also used in paid search campaigns to target ads geographically based on store appointment availability across more than 900 branches.

By allocating keyword bids in Google Ads according to where capacity is highest, Specsavers increased store appointments and reduced cost per acquisition. The AI-driven approach has delivered a double benefit: more efficient advertising and better use of in-store capacity, and the retailer continues to run an evolved version of this system.

Why is Ocado seen as a flagship adaptive AI adopter?

Ocado is widely regarded as one of the most advanced AI adopters in UK retail. Following its 2019 joint venture with M&S, Ocado Solutions was set up to focus on technology innovation for both the group and international partners, supported by substantial capital raising for global expansion.

The business has invested heavily in robotics and autonomous systems, acquiring robotics firms and partnering with Oxbotica on autonomous vehicle software. Its Re:Imagined platform uses Series 600 robots in “hive” warehouses, where AI-driven bots pick products from grids with high speed and accuracy, using machine vision and deep reinforcement learning to handle thousands of SKUs.

Ocado continues to develop its Swift Router technology, which uses AI to let customers shop until the last minute while orders are picked and loaded just before dispatch. “AI copilots” are being developed to balance demand forecasts with shift planning and warehouse operations. With technology solutions revenue growing strongly and partners across Europe, the Americas and Asia Pacific, Ocado’s AI systems are designed for global scalability.

What can other retailers learn from these adaptive AI adopters?

Across these ten retailers, common themes emerge. They mix different types of AI – adaptive, traditional and generative – to solve concrete problems rather than chasing technology for its own sake. They connect AI closely to commercial outcomes such as sales growth, cost reduction, waste minimisation and customer lifetime value.

They also invest in people and partnerships: building internal frameworks, academies and orchestration platforms while working with specialist providers where it makes sense. Above all, they treat AI as an ongoing capability that keeps learning, not a one-off project. Other retailers can follow their lead by starting with clear use cases, securing strong data foundations and involving colleagues at every stage of the AI journey.

If you are ready to explore how adaptive AI can help you unlock similar results in retail media and ecommerce, visit upp.ai to learn more about Upp.ai’s solutions and speak with the team about your goals.