Agentic commerce is set to reshape how shoppers interact with retailers. With AI agents and emerging standards such as the Universal Commerce Protocol, digital shopping is becoming more intuitive wherever customers begin or end their journey.
But what does this mean for shoppers, and how will this change the way we search online?
At its core, agentic shopping is designed to manage your entire shopping process. It can recommend what it thinks the shopper would like and complete the entire transaction without the shopper ever leaving the chat.
It sounds good, but it relies on more than just technical know-how and unified data. It relies on a significant change in how we choose to search for items and products.
Agentic AI creates more intuitive recommendations by understanding the context behind your search.
Until recently, we were used to finding items via search bars. We may have used short, snappy, keyword-driven phrases to find what we were looking for. But thanks to AI, people are becoming far more comfortable using conversational tools to find exactly what they need rather than browsing and hoping that they’ll stumble across something suitable.
There’s now been a shift in how we search for items. Shoppers aren’t just asking for an item; they are relying on their chosen search tool (whether an AI agent or a search bar) to understand the broader context and intent behind their need for those items.
For example, rather than searching for a ‘black dress’ or ‘office wear’, they might ask for a “knee-length black dress with sleeves that works for summer but can also be suitable to wear at work”. Or instead of asking for “holiday wear”, they might ask for “holiday wear for a week in August when attending a wedding in Rome.”
That shift in the conversational search means that shoppers won’t receive generic product recommendations. Instead, the search agent will incorporate the broader context, such as the time of year, weather implications, and societal expectations, as well as product-specific features such as fabric type or item style.
This conversational shift changes everything.
Unlike traditional search bars, which reset each search context to zero, agentic shopping tools incorporate previous conversation history every time you ask them to search for something new.
It’s natural for users to become more descriptive each time they chat with the tool, and over time, the agent will learn more about the user’s likes, dislikes or brand preferences.
But the biggest shift comes from how shoppers can respond to those recommendations.
Historically, AI-driven suggestions may have only enabled customers to select a thumbs-up or thumbs-down icon to show their preferences. More intuitive retailers may have encouraged users to choose from a limited set of predetermined checkboxes to explain their opinions, but that only ever enabled limited feedback.
Now, customers can look at the recommendations and have a detailed conversation to share their opinions. It’s easier to tell the chat “Yes, I like the style, but I don’t like the colour or pattern” or “I want something similar but with longer sleeves, or a different neckline”. Those insights become far more nuanced and personal. They result in entirely different shopping experiences because it’s no longer a straightforward search; it’s become an ongoing discussion.
Agentic shopping has turned the internet into a department store.
Agentic shopping has the potential to transform the retail sector because shoppers aren’t heading to a single retail website anymore. Instead, the agentic chat brings recommendations from multiple outlets to the customer.
The traditional shopping method required users to visit multiple sites, search for an item, browse the stock responses, and decide before moving on to the next outlet.
These tools have transformed that process. Shoppers now ask an AI agent a highly specific question about what they are looking for, then receive a wider range of recommendations from across the web that match the item’s intent.
From a shopping perspective, this sounds good for the customer because it gives far more choice.
But agentic shopping can only work if the recommendations are suitable and accurate.
While the internet may be the ultimate department store, shoppers may only want to receive item suggestions from local retail brands or those they already know and trust. If recommendations come from further afield, involve lengthy or expensive shipping times, or are unavailable, shoppers will quickly revert to their previous shopping behaviours.
For agentic shopping to work as intended, retailers must ensure their product inventory contains sufficient high-quality data for these systems to learn from. This is nothing new; it’s what brands have focused on as part of omnichannel shopping for years. But today’s intuitive shopping journey could start via a chat tool, on social media or in-store.
That’s why there must be no fragmented or incorrect data across different channels. Otherwise, this leads to discrepancies in stock availability, pricing, or even product quality, contributing to poor customer experiences.
At the moment, agentic shopping and traditional search are in a sweet spot.
There’s a perfect blend of conversational capabilities that allow customers to be very specific about what they are looking for, while also enabling detailed feedback on recommendations.
While third-party agents will continue to influence discovery, it’s the brand-owned environment that maintains the conversion.
Retailers are still in control of the final ordering, payment and shipping processes. This remains important because it allows brands to manage the experience, upsell or cross-sell, and reinforce loyalty through a familiar checkout process, offers, and rewards.
For customers who aren’t yet ready to transition to an agentic commerce experience, brand familiarity and trust remain the most important part of any shopping experience, whether browsing or buying, in-store or online.
