Generative AI is revolutionising the shopping experience by creating hyper-personalised, intuitive customer interactions while enabling retailers to offer seamless, data-driven services. From AI-powered search to dynamic product customisation, GenAI is shaping the future of retail by merging online and offline experiences into one cohesive journey.
Integrating Generative AI (GenAI) into the retail sector transforms how consumers interact with brands and make purchasing decisions. The technology is shifting the internet from a mere information source to an intelligent platform, changing online shopping from a transactional experience to a deeply personal interaction. Brands now have the potential to use GenAI to understand their customers better than ever before and deliver tailored experiences that foster loyalty.
The Shift from transactional to personal shopping experiences
Generative AI is upgrading how consumers navigate online retail, creating a more personalised and seamless shopping experience. As Gopi Polavarapu, Chief Solutions Officer at Kore.ai, explained to Silicon UK, “Generative AI is transforming the online shopping experience by creating highly personalised customer interactions.”
Polavarapu continued: “GenAI’s ability to analyse vast amounts of customer data, including past shopping choices, browsing behaviour, and purchasing history, generates tailored product recommendations and marketing strategies. This level of personalisation mimics the experience of having a personal shopper who knows your style, keeping customers engaged and encouraging repeat visits.”
In fact, this personalisation extends beyond just recommending products. As Polavarapu explained: “Offering personalised touches, like predicting the best size or product for a customer, can help in achieving great cost savings for both the business and consumer by reducing the number of returns.” With retailers like H&M already charging customers for returning items, such innovations can significantly impact customer satisfaction and operational efficiency.
While GenAI is revolutionising the digital shopping sphere, customers still value a seamless connection between online and offline shopping. Shopify’s State of Commerce Report revealed that over two-thirds of European consumers (67%) and 65% of UK consumers believe that brands need to offer an integrated experience. As Polavarapu explained to Silicon UK, “By having a GenAI-powered chatbot in place that can prevent returns where possible, consumers can not only save time and money by cutting down returns, but also be guided towards products that are better-suited to their preferences.”
This integration isn’t just about maintaining a consistent experience; it’s about enabling a hyper-relevant, seamless journey across all touchpoints, allowing customers to switch from digital to physical retail effortlessly.
The Rise of AI-Powered Search
As Dom Couldwell, Head of Field Engineering, EMEA at DataStax, explained to Silicon UK, GenAI is fundamentally transforming how customers search for products. Traditional search engines rely on exact keyword matches, often delivering unsatisfactory results for customers unsure of what they are seeking. Couldwell noted, “Using semantic-based search and generative AI together, you can provide results that respond to what a customer means, not just what they type in.” This means that customers are no longer restricted by the limitations of conventional search functions. Instead, they can engage with a more intuitive system that understands their context and intent.
Additionally, visual search capabilities, powered by AI, are becoming more common. This allows customers to search using images, which Couldwell suggested is “often more convenient.” Visual search, when combined with GenAI, can revolutionise the way customers interact with online platforms, making the process faster, more intuitive, and ultimately leading to higher conversion rates.
Personalisation versus privacy: Striking a balance
One of the key challenges facing retailers as they implement GenAI solutions is maintaining a balance between personalisation and customer privacy. Couldwell stressed the importance of using methods like RAG (Retrieval-Augmented Generation) to ensure customer data is handled securely. He explained to Silicon UK that RAG, “delivers better context to the LLM [large language model], so it can be used during an interaction to provide more relevant results.” Crucially, however, the customer’s shopping history remains private, with none of the data being trained into the AI model.
This balance is essential for maintaining consumer trust in an era where data breaches and privacy concerns are front and centre. As Couldwell pointed out, “If the experience is better, and customers like it, I don’t see this being an issue.” However, brands must ensure that privacy and security remain a top priority as they roll out more advanced AI-driven shopping experiences.
The future of GenAI in shopping
Looking to the future, both Couldwell and Polavarapu shared insights into how retailers should prepare for the continued evolution of GenAI. Couldwell suggested that autonomous AI agents could become more prevalent, noting that, “we will see more agentic AI or autonomous agents coming through.” These agents would have greater flexibility than current GenAI models, capable of handling more open-ended queries and delivering a more proactive customer service experience. For example, an autonomous agent could design an entire holiday itinerary based on a customer’s preferences, going far beyond a simple product recommendation.
Polavarapu, on the other hand, emphasised the growing importance of social commerce. As more consumers share their shopping experiences on platforms like Instagram and TikTok, GenAI will play a critical role in real-time content generation. “Retailers should capitalise on this trend,” Polavarapu explained, “by reaching more customers through user-generated content.” This shift towards social-driven retail could become a key competitive advantage for brands willing to embrace the opportunities presented by GenAI.
Practical considerations for retailers
For retailers looking to harness the power of GenAI, there are several important considerations to bear in mind: One of the most significant is how to integrate AI into existing retail infrastructures effectively. As Couldwell highlighted, “GenAI is not a one-size-fits-all technology—it depends on your data.” Retailers must assess their current technology stack, data quality, and infrastructure to ensure that GenAI implementations deliver maximum value.
Polavarapu recommended that retailers invest in AI Platform as a Service (AIPaaS) solutions to manage the complexity of deploying and maintaining advanced AI systems. This allows businesses to leverage AI’s benefits without needing to build every aspect from scratch. Retailers that adopt a more comprehensive approach to GenAI—thinking of it as a platform to drive value across the entire organisation, rather than just a series of point solutions—will be better positioned to capitalise on this transformative technology.
GenAI is undeniably set to reshape the retail landscape. From personalising customer experiences to improving operational efficiency, the technology promises benefits for both consumers and brands.
As retail continues to evolve, one thing is clear: GenAI will be at the forefront of the revolution, turning online shopping into an intelligent, hyper-personalised, and interactive experience.
Chris Connon, Senior Client Strategist and Retail Expert, Slalom.
How is Generative AI transforming the online shopping experience for consumers today?
“Retail is going through a transformative period, thanks to the wide deployment of AI to utilise the vast amounts of data that have been too complicated to access in the past but can revolutionise how retailers are using GenAI to tailor marketing content, product recommendations, and even shape entire shopping journeys to individual consumer preferences.
“Taking Pinterest as an example, the company’s visual search technology, like Pinterest Lens, harnesses deep learning models to analyse uploaded images, identify objects, and provide highly relevant recommendations. Users are offered a seamless experience where they can discover new ideas, products and content. Not only does this increase engagement but it can help to broaden commercial opportunities.
“Elsewhere, retailers are using GenAI to power advanced image recognition technology, which allows customers to search for products using photos or even virtually “try on” clothing or makeup using augmented reality. We’re likely to see this more widely adopted in the future among retailers as it facilitates an “in-store” experience for customers who want the convenience of at-home shopping, but prefer to have a preview of products they are purchasing.
“A customer-centric approach to AI reassures consumers that AI is not just a technological advancement, but a tool that can truly enhance their shopping and buying experiences.”
How do you see GenAI influencing consumer behaviour and purchasing decisions in the near future?
“Given GenAI’s capability to make hyper-personalised recommendations and enhance tailored marketing, it is likely to lead to more spontaneous purchasing by consumers. GenAI can present products that closely align with individual preferences and needs, so impulse purchases may feel more justified and relevant.
“‘Personalisation’ has been a buzzword in retail for a while now, but AI is the superpower that’s finally making it possible for retailers to streamline their processes, inventory and customer touchpoints to optimise and personalise the experience.
“On the other hand, consumers can use GenAI to their advantage to make more informed purchases. They can access more detailed product comparisons, reviews, and information, increasing the consideration phase. Ultimately, this still leads to a more positive outcome with higher post-purchase satisfaction and increased brand loyalty.
“Finally, AI-driven personalisation will start to set a new expectation standard among consumers. Customers will come to expect a tailor-made experience across all retail touchpoints. Retailers unable to meet this standard across the board will likely see decreased customer loyalty as a result.”
What are the key challenges retailers face when integrating GenAI into their shopping platforms?
“The technical hurdle of integrating GenAI into shopping platforms is multifaceted.
“First, retailers need vast amounts of high-quality data to train AI models, including product information, customer behaviour, transaction history, and external data like market trends or social media sentiment. Ensuring consistency across these datasets is key to avoiding mistakes in inventory management or customer service.
“Second, integrating data from different sources requires cross-collaboration among a business’ IT, data science and business units. Ensuring colleagues across these departments have a good understanding of AI and the importance of data quality is crucial to producing accurate results.
“Even if retailers get the data right, there’s still the hurdle of security and ethics when handling sensitive data like customer information, when training their AI models. The onus is on the retailer to ensure that data is protected from any breaches or unauthorised access.”
How can GenAI help retailers manage and optimise their inventory and supply chains?
“Used properly, GenAI allows retailers to move beyond traditional forecasting models to dynamically predict demand, optimise stock levels, and improve overall supply chain efficiency.
“GenAI’s ability to analyse vast datasets in real-time, whether that’s sales trends, customer behaviour or external factors like weather or economic conditions, means retailers can generate more accurate demand forecasts, reducing the risk of overstocking or being out of stock of certain products.
“It can also simulate various supply chain scenarios, helping retailers proactively address potential disruptions and identify the most efficient logistics strategies.
“Furthermore, GenAI can assist in optimising inventory management by automating reorder processes, suggesting optimal stock levels for different locations, and even predicting when specific items will need replenishment. This improves operational efficiency and reduces waste and costs associated with excess inventory.
“The benefits? Enhanced efficiency, reduced costs, and a surge in customer satisfaction. This value-unlock underscores the potential of AI in retail, making it one of the most exciting sectors to embrace this technology.”
