Artificial intelligence is no longer an experiment in retail. According to Amperity's data, almost half of retailers use AI every day or several times a week. 2025 Retail AI Status investigation.
From customer data platforms to forecasting models and chatbots, the technology is today embedded in everyday operations, reshaping the way brands engage customers and compete in busy markets.
“We have AI embedded in many parts of our business, so it feels seamless rather than experimental,” said Daniel Chasle, chief data director for fashion in the UK. Newsweek.
“For example, we deployed Microsoft Copilot to a subset of our employees, using customer profile algorithm stitching, Zendesk's AI chatbot, AI chatbots that support customer service deflection, and AI coding assistants for developers to help with daily tasks.
Newsweek Illustration/Canba
The normalization of AI reflects an industry turning point. 97% of retailers plan to maintain or increase AI spending this year, focusing on personalization, media spending and demand forecasting. Loyalty and customer service are also important goals as executives seek to reduce costs and strengthen relationships at the same time.
“What retailers really want is a demonstrable outcome,” said Tony Owens, CEO of Amperity. Newsweek. “They don't want AI for AI. They want evidence to drive growth. Every use case must be tied to revenue, efficiency, or loyalty in a way that you can measure.”
Changes in omnichannel strategies
One of the biggest changes in 2025 is Astrathea, which retailers think about omnichannel: to provide customers with a consistent shopping experience directly, online and mobile.
“Omnichannel 1.0 was about where our customers were, inventory, websites and apps,” Owens explained. “Omnichannel 2.0 is about the customer's journey itself, and AI allows them to personalize those journeys in real time. Customers decide on channels rather than retailers and vote in their wallets.”
Retailers believe it is possible. 63% believe that AI will help improve customer loyalty, while 65% expect it to increase customer lifetime value. However, currently, 43% are under 43%, and they are currently applying AI to customer-facing applications.
“Customers don't consider themselves a segment or a cohort. They travel with your brand,” Owens said. “AI helps retailers meet them on their journey by predicting their needs, adjusting offers and being consistent across all channels. People know that brands really “get them.”
Still, adoptions are uneven. Though enthusiasm is high, retailers are cautious about pushing AI directly into the customer's touchpoint, often suppressing it due to cost, skill gaps and infrastructure challenges.
Solving data puzzles
This study highlights one major obstacle. 58% of retailers say their customer data is fragmented or incomplete. That fragmentation results in cost, delayed decision making, and complicated personalization.
“The challenge is to acquire data from different systems and weaving it together to give the physical customer a consistent view of the data behind it,” Chasle said. “The opportunity is to have a uniform view of the customer, their shopping behaviors and preferences, and to understand all touchpoints and customer interactions. This makes for a very powerful dataset that can help you enhance your decision-making and customer engagement.”
The New Look brand addressed the issue by combining the enterprise data platform with Amperity's identity resolution. “Amperity makes data seamlessly available to your data platform, allowing you to access the data science team,” Chasle said.
That effort has already brought about results. New Look is about using real-time customer profiles to fine-tune your marketing campaigns and improve your personalization. According to Owens, unified data helped brands identify customers with nearly 26% higher value than they previously recognized.
Owens said it was “proof that putting the right data behind AI will bring better travel for customers and measurable benefits of business customer data.”
And the results are concrete. “The improved, newly created real-time customer profiles are already fueling paid media suppression activities, CRM optimization, and will soon start powering new waves of personalization experiences,” Chasle said.
Owens said the New Look example shows potential benefits. “By unifying customer profiles and power forecasting models using amperities, they revealed nearly 25% higher value customers than before. That insight has proven that better offers, stronger transformations, and putting the right data behind AI will bring better journeys for customers and measurable benefits of customer data for business.”
But not all retailers have made this leap. The survey currently uses AI in production to resolve customer identity and prepare data for marketing, highlighting how the data challenges are spreading.
From experiments to embedding
For many retailers, adoption of AI is beyond pilot projects. Almost half already use AI every week, with people with a customer data platform far ahead of their peers.
Organizations with a customer data platform (CDP) are twice as likely to use AI every day (60% vs. 29%) and fully recruited by multiple business units (22% vs. 10%).
“There's no budget luxury to experiment with, so we're approaching it on a value-based basis as part of our roadmap for change and as part of our prioritization of business value and alignment to comprehensive strategies,” Chasle said.
Owens said the distinction between experimenters and leaders has been clear. “Experiments usually see productivity gains, such as reducing costs, speeding workflows, and progressive improvements. It's valuable and all retailers need to experiment with AI right now. But leaders take that even further.
That gap could widen. As some retailers incorporate AI into their core operations, others risk being stuck in pilot mode without scaling their confidence or resources.
What's coming next
Owens and Chasle pointed out personalization as the next big opportunity.
“Yes, personalization of the web experience is on the roadmap for the time being. The vision of this leads to a personalized AI stylist feature that supports our customers both on digital and retail channels,” says Chasle.
Owens predicted that the next wave would be even more transformative. “By 2026, retailers will begin democratizing data across the enterprise and use it to coordinate customer journeys end-to-end, when AI will provide the full return of customer data.
“That's the moment of separation,” he continued. “Retailers who learn this will acquire a large portion of their customers in the category and set the standard for the next generation of brands. Brands that will not be delayed. This is the crucial moment in retail. There are winners, there are losers.”
The findings reflect a broader consumer survey, including Cognizant's recent survey, indicating that shoppers are increasingly expecting personalizations that drive AI on retail travel. To sum up, the two reports show both sides of the AI revolution. Consumers demand seamless experiences, and retailers provide them by racing and building the data foundation.
Whether these predictions come to fruition depends on how quickly retailers have overcome the same obstacles that have previously slowed down AI: siloed data, high costs, employee training.
The study highlights the tension between ambition and preparation. While 97% of retailers are increasing their AI investment, only 11% feel strongly that they are ready to deploy AI tools at scale. High costs, technical gaps, and fragmented data remain persistent hurdles.
Still, the direction is clear. “The biggest opportunity is to be able to tackle these business processes and reimagined them with AI. “It will require important business buy-in with senior stakeholder sponsorship, a clear end-state vision, and a roadmap of activities that will gradually tackle the necessary changes.”
