Generative AI has dominated the retail tech hype cycle in the past year. But does it have staying power as a strategy to drive sales in a slowdown?
Aggressive investment in AI has trickled all the way up to the executive branch. President Trump signed an executive order in late January removing barriers to American AI innovation, allowing companies to develop and deploy AI without regulatory restrictions. A hands-off approach has set up the playing field for an intense race among retailers to integrate AI rapidly and maintain a competitive edge.
Benjamin Fels, CEO and co-founder of AI supply chain firm Pendulum, notes that Trump’s $500 billion AI infrastructure investment could help US retailers compete with foreign e-commerce giants by enabling faster supply chains and predictive analytics. US retailers struggle to match Shein’s 30-day inventory turnover and 6,000 daily product launches, as well as mitigate the $1.5 trillion in global annual losses from supply-demand disconnects. Fels describes this as a global “algorithmic warfare”, where brands are racing to implement more AI-powered algorithms and personalised merchandising strategies to compete with Chinese retailers.
The same week as that executive order, China released DeepSeek-R1, a high-performance generative AI model built for roughly $5.5 million — far less than the tens of billions spent by Microsoft, Meta and Google on similar models, or the $500 billion invested by OpenAI and SoftBank. Rather than relying on expensive high-end chips, DeepSeek was developed using young engineering talent, making it a cost-effective alternative. Unlike TikTok, DeepSeek is open-source, making it nearly impossible for the US government to ban it, as users can freely download and distribute its data.
DeepSeek’s early success suggests that Chinese AI development could accelerate even faster than anticipated with technology on par with US AI. This presents an opportunity for global retailers from luxury to fast fashion to embrace open-source AI to enhance trend prediction, personalisation and customer experiences — potentially widening their competitive edge.
In 2024, 70 per cent of retail executives planned to implement generative AI, Carrie Tharp, VP of industries at Google Cloud, previously told Vogue Business. However, most brands were still in the ideation phase, exploring possibilities without major investments. Although many retailers have stated that they plan to implement AI, the investment to build in-house AI tools or purchase from partners is a costly multi-year endeavour. It’s yet to be seen if retailers commit to these investments long enough to see lasting results for customer engagement and sales.
“2024 was a year of AI exploration in retail, but 2025 is when we’re seeing innovations deliver measurable results,” says Ali Furman, consumer markets industry leader at PwC US. “Retailers are increasingly using AI to turn customer behaviour, preferences and purchase history into actionable insights that enhance operations, personalise marketing and optimise inventory decisions.” Furman noted that AI-driven personalised experiences are particularly crucial for targeting Gen Z shoppers, who adopt new fashion trends faster than older consumers.
Redefining personalisation
Victoria’s Secret has transformed its email marketing strategy using AI personalisation. Previously, the brand sent the same daily emails to all customers based on product and brand priorities rather than individual preferences, according to Lindsay Massey, vice president of marketing. Now, marketing emails are customised to each customer type, leading to double-digit increases in revenue per email, click-through rates and conversion rates. For example, Gen Z customers might receive promotions for logo bralettes, while millennials who previously purchased shapewear see recommendations for smoothing strapless bras.
Swarovski has established an AI Center of Excellence consisting of eight senior executives tasked with integrating AI across their full customer journey. A key focus has been enhancing search functionality with “searchandise”, a system that merges search and merchandising to personalise experiences. Swarovski collects customer data across e-commerce, mobile, and in-store interactions to tailor recommendations. AI now powers features like “recently browsed” and “complete your collection”.
“Integrating AI into our customer experience required meticulous planning to maintain a sense of luxury. Simultaneously, we aimed to leverage data and technology to enhance the customer journey,” says Lea Sonderegger, chief digital officer and CIO at Swarovski. “One of our primary challenges was ensuring that AI added genuine value rather than being implemented for its own sake.” AI-driven recommendations now account for 10 per cent of Swarovski’s website sales, the brand says.
Powering search and improving customer experience
Swarovski has also implemented AI-powered customer service tools that the company says reduced response times for customer service agents by 48 per cent year-over-year. The AI provides self-service options for customers and suggests responses for human agents, allowing for faster resolution. “Our AI-based customer service solutions finder streamlines our operations by improving response accuracy and reducing resolution times. AI-powered automation in ticket routing, solution recommendations, and translations has contributed to a measurable improvement in customer satisfaction,” said Sonderegger.
Mike Hite, chief technology officer at Saks Global, also credits AI for improving customer satisfaction. Saks’s chatbot, powered by Salesforce’s Agentforce, analyses customer interactions in real time to determine the best next action, helping service teams prioritise more meaningful interactions.
“As we work to reinvent luxury shopping, we are using advanced technology, including AI, to deliver luxury fashion and experiences that are perfectly curated to each individual customer, said Hite. “In autumn 2024, we launched Agentforce for Saks Fifth Avenue to bolster our approach to delivering elevated customer service. Since then, Agentforce has increasingly augmented our teams’ capacity to deliver individualised and efficient customer support.”
If the customer has a frequently asked question, such as a password reset, Agentforce will recommend a response. This frees up the human customer service agents to dedicate time to speaking to customers with more urgent requests, such as a bridesmaid dress that requires overnight shipping.
Global footwear retailer Caleres — home to brands like Sam Edelman, Vince and Veronica Beard — relaunched 13 branded e-commerce sites featuring AI-powered product search and discovery. With over 600,000 product SKUs and 900+ brick-and-mortar stores, the company has seen a 23 per cent increase in conversion rates and a 5.5 per cent increase in revenue per visitor since implementing AI search enhancements.
“We had a desire to deliver a more personalised, immersive shopping experience sitewide. We wanted to do more ‘storytelling’ with our site, in line with what other leading websites were doing,” states Dan Cornwell, director of e-commerce and digital experience at Caleres. “We are big believers in the power of machine learning [a subfield within AI], especially with the volume of orders and visits on our websites.”
“The most popular AI applications in retail focus on personalisation,” said Peter Curran, GM of commerce at Coveo, an AI firm that powers Caleres. “According to Forrester Research, AI-driven personalisation can help brands increase sales by up to 15 per cent.”
Generative AI has taken centre stage in retail technology, but its long-term impact on sales remains uncertain, especially amid economic slowdowns. The US government has fuelled AI development by removing regulatory barriers and investing in AI infrastructure, intensifying competition between American and Chinese retailers. As brands shift from AI exploration to implementation, the real test in 2025 will be whether these investments deliver sustained growth or merely serve as short-term competitive advantages.
At stake is the future of AI’s role in retail — whether it becomes an indispensable driver of efficiency and personalisation or just another passing trend in the industry’s innovation cycle.
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