Each year the buzz of the festive period comes around, and so does the pressure to find the perfect gift. Hours spent scrolling, second-guessing, and cross-referencing budgets are all too familiar experiences. This year — and those to follow — could be very different with AI emerging as the key to stress-free gifting.
A third of Gen Z and a quarter of Millennials now use AI for shopping consultancy, with nearly 50% using it daily to research brands, compare prices, and generate gift ideas. This marks a dramatic shift in shopping behaviour, and the arrival of agentic commerce, where AI-powered platforms don’t just assist the journey; they orchestrate it. In this new era, AI agents act autonomously on behalf of shoppers, searching, comparing, and even completing the sale across multiple channels, often without ever visiting a merchant’s website.
Such experiences are seamless, contextual, and increasingly the default for how consumers opt to interact with commerce online. With AI taking on the role of consumers’ personal shopper, brands must ensure they aren’t overlooked. By optimising their product data across the channels where discovery and checkout occurs, they can ensure it’s accessible to both search engines and AI agents.
Removing the friction from gift giving with agentic commerce
For decades, ecommerce visibility has been driven by SEO and paid adverts that direct shoppers to a brand’s own website. AI has disrupted this format and retailers are noting the shift, with around 20-30% of web traffic from search engines already evaporating.
AI agents are now active participants in the buying process rather than passive recommendation tools, with ChatGPT agent requests increasing by a staggering 200% between July and August alone. Whether it’s curating a list based on someone’s interests or tailoring product suggestions, they can streamline the process, converting what was once a time-consuming decision, into a moment of confidence for shoppers.
Younger consumers, in particular, rely on these tools as trusted shopping advisors, with more than a quarter stating they trust AI recommendations over those of friends, family, or influencers.This means if a brand’s data is not discoverable within AI ecosystems, it risks being overlooked by an entire generation of consumers. Brands that will thrive are those that design for prompts, not pages, and prepare their product data accordingly. For example, Brompton cycles are already leaning into prompt-style recommendations based on terrain and route type.
Personalisation underscoring shopping experiences
One of AI’s key attributes is its ability to power personalised and tailored online commerce experiences. This is invaluable during the holiday season, when gifts are intended to be relevant to the recipient. In fact, 42% of shoppers want to see offers that align with their interests, and 35% are looking for recommendations informed by their search history.
Rather than everyone navigating the same storefront, AI agents are trained to a brands specific data set and can provide in-depth product recommendations and consultation for customers, suggesting items that are uniquely suited to a customer’s past purchases and browsing habits. Great examples of this are On Running, which uses AI agents that instantly match customer queries about fit and terrain to the most suitable running shoes and Estee Lauder leverages shade matching, regimen pairing, and ingredient-based personalisation, to create a tailored shopping experience. Agents can also offer recommendations to adapt based on location or upcoming events, all leading to a more targeted shopping experience.
When data becomes the new wrapping paper
Brands must follow the lead set by consumers and embrace AI. To ensure visibility in these AI-driven marketplaces, brands must optimise for AI discovery, from structured data to transparent product details and authentic reviews. Data becomes the key to visibility and driving sales conversions and these retailers who adapt will find themselves on an array of digital gift lists this holiday season.
Brands need to view their product catalogues as flexible, AI-ready datasets instead of fixed listings. Agents rely on more than product names and prices; they require context such as FAQs, imagery, inventory levels, and brand narratives to generate trusted responses to the more specific questions that shoppers may have. Many retailers already have these assets, but they’re seldom structured or connected in a way that LLMs can digest. The brands that do organise this information see immediate benefits. Mizuno, for instance, improves conversation by surfacing products matched precisely to a shopper’s sport, skill level, and playing surface, dramatically shortening the decision-making journey. Success now hinges on tagging, structuring, and integrating them into machine-readable feeds so agents can generate accurate, trusted answers.
A smarter future for gift giving
It is increasingly evident that AI is driving the future of gift shopping, reshaping how people discover, compare, and how they buy.
Shoppers are no longer typing, filtering, and scrolling the way they used to. They’re asking questions, looking for recommendations, and putting their trust in AI to find the most relevant answers and products for them. In response, the way brands achieve visibility must change.
The brands who will thrive in this new era of ecommerce are those who make it easy for AI to choose them. They’re preparing their product data to ensure it’s accurate, complete, and consistent. At the same time, they are ensuring that both their own websites and the data provided to AI platforms tell the full story of each product, supported by rich context, detail and brand-backed content.
Al Williams
Al Williams is General Manager of B2C at Commerce, with extensive experience helping brands and SaaS platforms grow through effective ecommerce strategy, technology, and customer-focused digital experiences.
