Joe Hale, founder of Verde Digital, looks at how AI shopping could impact retailers. Really.
Until recently, AI shopping was treated as a future concept for UK retailers once the technology matured and consumer behavior caught up. But recent developments in the US shed a little more light on where AI shopping is heading.
JD Sports’ announcement that it will allow U.S. customers to search for products and buy with one click directly through AI platforms such as Microsoft Copilot, Google’s Gemini, and ChatGPT signals a clear shift. At the same time, Google and Shopify launched the Universal Commerce Protocol (UCP), designed to standardize how AI accesses product data, pricing, and availability.
The promise is to deliver frictionless discovery, conversational commerce, and personalization at scale. The challenge for UK retailers is how to approach AI search alongside SEO and e-commerce performance, which still underpins the majority of online revenue.
Having worked with retailers through multiple waves of “next big things” like mobile-first shopping, marketplaces, and social commerce, I’ve learned that winners aren’t always first movers. They are a brand that understands which parts of the stack must evolve and which parts must be protected. AI shopping is no exception.
JD’s approach is notable in that it treats AI as a transactional channel. With Stripe handling checkout and connecting LLM directly to its product information, pricing, and inventory systems, JD enables customers to move from discovery to purchase in a single conversation flow, without having to visit a website or app.
This model could be transferred to the UK market, but regulations, margins and consumer expectations are different. But it shows the direction of travel and how AI is moving from influencing to mediating shopping decisions.
SEO is not dead
Every time a new search method comes along, SEO and Google are declared dead. Absolutely not. In fact, some of our clients have achieved record book returns.
AI shopping won’t eliminate search behavior, but it will add new ways for users to shop. Using AI, shoppers ask questions instead of typing keywords. Instead of scanning the results page, you’ll see recommendations. However, beneath that conversational layer, search still relies on well-known signals such as structured data, authority, relevance, and trustworthiness.
In other words, the same basics filtered with additional layers.
The danger for brands is assuming that an AI shopping assistant simply “knows” their catalog, which is not the reality. AI relies heavily on how well-defined and connected products are through feed consistency, entity relationships, schema markup, real-time availability, and historical performance data.
From an SEO perspective, this puts a new emphasis on fundamentals that are often neglected. Product titles must be accurate and consistent across channels. Attributes such as size, color, and category should be clearly structured and not buried in free text descriptions. Internal links and taxonomies are still important because they help machines understand how products relate to each other.
Brands that weaken these foundations in pursuit of AI integration risk losing visibility within the AI shopping landscape. Companies that maintain technical hygiene, invest in content that reflects the true intent of their customers, and carefully manage product data will be far more resilient, regardless of which protocols or platforms prevail.
AI assistants still rely on structured data, clear product entities, authoritative content, and trust signals to make recommendations. What disappears is the visible ranking. Rather than appearing on page 1 of search engines, brands may or may not be mentioned within conversation responses.
For UK retailers, this poses a subtle but serious risk. You may not see a dramatic drop in traffic or rankings. You may simply stop participating in the conversation.
Therefore, securing your SEO fundamentals is a way to ensure continued visibility with AI-driven discovery even as interfaces change.
Brands that are already winning with AI search are those that approach it from a brand perspective, complemented by SEO fundamentals that support them from both a brand and non-brand perspective.
E-commerce performance still pays the bills
There is a danger that agency business may distract from more immediate priorities. Rushing to AI enablement to appease senior stakeholders can distract brands and marketers from focusing on what actually drives immediate revenue.
Many e-commerce sites in the UK still suffer from issues that directly suppress conversions, such as poor performance, inefficient internal search, weak filtering, and inconsistent pricing logic. AI won’t solve these problems, but it will illuminate them.
Trust can be quickly lost when an AI assistant reveals inaccurate stock levels or misleading prices, but that trust is hard to regain in the UK. JD’s AI initiative builds on significant investments in digital infrastructure, including a major replatforming of its U.S. e-commerce operations.
For most UK retailers, adapting to AI shopping is less about innovation and more about getting the basics right. Product data must be accurate and well-managed. Site performance must meet rising expectations. Analytics must clearly show the journey a user takes from discovery to conversion so that AI-induced actions can be understood rather than guessed. Without these foundations, AI becomes a layer of complexity rather than a source of value.
Expect fragmentation before consolidation
One of the assumptions underpinning much of the current discussion is that we are moving towards a single dominant standard for AI commerce, but I don’t think this is the case.
Google’s Universal Commerce Protocol isn’t the only framework retailers need to work with. In addition to platform-driven standards, we are already seeing more informal protocols emerge through direct integration between commerce engines, payment providers, retailers and AI models. JD Sports’ use of Commercetools and Stripe is an example of a retailer-controlled approach, while platforms such as Microsoft form their own terms through Copilot and Bing. For British brands, this signals an era of coexistence rather than integration, with visibility relying less on upholding a single standard and more on having data, SEO and e-commerce systems that can adapt to multiple standards.
Therefore, we are much more likely to see a fragmented period where platform-specific implementations, retailer-owned systems, and hybrid approaches compete over several years. Each optimizes different incentives, including ad revenue, conversion efficiency, data ownership, and loyalty.
This means that flexibility is more important to brands than loyalty. The goal is not to choose a winning protocol, but to build systems and teams that can adapt without having to rebuild the platform each time the situation changes.
It requires a modular data architecture, a strong first-party understanding of the customer, and a willingness to resist delegating strategic decision-making to vendors that provide certainty in uncertain territory.
hold on to what’s important
When new technology emerges, there is intense pressure to respond quickly. Boards want reassurance, investors want a clear narrative, and teams want direction.
My advice to e-commerce brands moving forward with AI shopping is to be strategic. Try ways to keep your foundation intact while protecting the foundations that drive your current revenue. Don’t get caught up in the next wave of SEO by forgetting the basics that we know continue to drive the majority of your total revenue.
AI will change the way people shop. While protocols such as UCP may well become part of your infrastructure, visibility and profitability will still depend on remembering that technology shapes demand, not creates it. If you still understand your customers better than anyone else, and your SEO and e-commerce foundations reflect that understanding, then you’re already more prepared for AI shopping than you think.
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