What is agentic AI, and how is it changing how we shop?

Sharon Gee, senior vice-president product, AI, at Commerce

As more consumers turn to conversational chatbots such as ChatGPT for answers to everyday questions, a revolution is taking place that is changing how people shop, and in turn, how retail businesses operate. These platforms are pushing consumers away from traditional search engines towards answer engines, welcoming the era of conversational commerce.

Sharon Gee, senior vice-president product, AI, at Commerce, shares her insights on how impactful this will be for fashion, and her advice on how brands and retailers can keep up.

What is agentic AI?

Agentic AI refers to intelligent systems that can act autonomously on behalf of users – not just answering queries but making decisions, performing tasks and completing transactions. Unlike search engines, which return a list of links, answer engines are powered by large language models (LLMs) which interpret intent and provide responses in the context of the conversation, and adapt as more information is provided.

This is profoundly disruptive – and exciting.

Consumers are already shifting from keyword searches to asking natural, conversational questions. For example, “What’s the best vegan-friendly leather handbag under £300 for an autumn wedding?” That question will not take a user to a website – it will search the internet and find the best products that fit those requirements to surface in the chat.

Brands that rely on paid search or SEO (search engine optimisation) visibility must now also optimise for AI agents.

This marks a fundamental shift from search-based discovery to AI-assisted buying journeys.

This is not coming – it is already here.

Why is agentic AI going to be so impactful to fashion?

Fashion is a highly visual, trend-driven and personalised vertical, which makes it ideal for AI assistance.

Agents can pull from structured and unstructured data sources, meaning that they not only draw from product information, but also from reviews and fit guides to be able to make recommendations that align with the shopper. Agents can filter thousands of SKUs instantly and only show what is relevant to each shopper’s intent.

Will most consumers shift to this way of shopping?

Yes, and it is already happening. Almost 60% of consumers are already shifting their search behaviour to these new platforms. Gen Z and millennial shoppers are comfortable with conversational commerce, and are increasingly using tools such as ChatGPT, Perplexity, Google AI mode, Gemini or Microsoft Copilot to explore what to buy. It is not a matter of “if” – it’s a matter of readiness.

How can brands make sure AI agents are finding and recommending their products?

The recommendations from AI agents are powered by data. Sometimes this data is scraped, but the more real time, enriched and machine-readable product data is, the better – they can consume structured data such as title, description, size, price and colour, as well as unstructured data like images, videos, reviews, fit guides and video transcripts. Agents don’t just search. They interpret context, cross-check specs and anticipate purchase decisions.

Brands must ensure their data is discoverable and optimised across all the channels their shoppers are searching. If your product data is incomplete, inconsistent or siloed, your products become invisible to AI.

This is where Commerce plays an important role with the Feedonomics and BigCommerce platforms: we help brands optimise, enrich and syndicate data across marketplaces, search engines, and now answer engines.

Agentic AI has the power to impact the shopping journey beyond just product discovery. Tell us about agentic checkout.

Agentic checkout is whenever a shopper is able to purchase without leaving the chat experience.

This will be enormous for certain categories. Instead of the shopper starting product discovery in a chat and then being prompted to click to a website where they then need to add to cart and checkout, it can streamline the journey, removing the risk for drop off.

This kind of shopping flow works really well for certain categories, such as for fashion discovery or for products consumers already know they want. For products that require more consideration or deeper context, it’s likely shoppers may prefer a brand owned experience.

Are there trust issues that need to be overcome for more consumers to shop with AI agents?

Trust is always earned – and AI is no different. Consumers need transparency: what data is being used? How are recommendations made? Who is liable if something goes wrong?

But we have seen this before. Consumers once hesitated to put their credit card into a browser. Now one-click ordering is standard. Similarly, as AI agents become more accurate, helpful and accountable, trust will grow.

Brands can help by offering opt-in experiences, clear data policies and aligning with trusted platforms. Long term, AI trust will become a competitive advantage.

You believe data is the new store front. What does this mean?

In the agentic era, the store front isn’t just your website – it’s every instance where your data can be interpreted and acted on by an AI agent. “Data is the new store front” means your product data is your store. It’s how you show up in discovery, how you get recommended and how purchases are made.

Brands need to structure and enrich their product data, and then syndicate it across all relevant endpoints, such as search, social, marketplaces and LLMs. They must also maintain accuracy in real time across stock, price and delivery.

Does this mean brands’ own digital store fronts will become irrelevant?

Websites aren’t going away, but their purpose is evolving. They may no longer be the first touchpoint. Discovery could happen via an AI assistant and checkout could happen outside the store front. But your site is still critical for brand, trust, storytelling and validation. It must serve both humans and AI agents with structured content, clear brand identity and seamless back-end integration.

Where should brands start on the agentic journey?

Brands should invest now on data readiness: clean, enrich and structure your product catalogue. Optimise your data for experiences across both owned and third-party channels, based on shopper intent and channels’ specific schema requirements.

Also focus on distribution: syndicate your data to the platforms, marketplaces, answer engines and social channels that deliver quality search and shopping experiences to your customer.

Checkout agility is also important: adopt composable checkout flows, and engage partners that can unlock transactions and orders across a variety of channels. Brands should also experiment with AI agents: don’t wait. Test discovery and agent-commerce interfaces now.

My recommendation: future-proof now. If you delay, your competitors will own the shelf in the agentic world.

Finally, what advice do you have for brands in this era of digital commerce?

Rethink everything you know about traffic. In the agentic era, the customer may never visit your store. You have to be able to support search, discovery, considerations, purchase and fulfilment – all through data and with the right partners.

So, one: optimise for visibility to AI agents. Two: build agility into your tech stack and choose partners that give you leverage. And three: invest in long-term data syndication and orchestration. This is not a channel shift – it’s a commerce paradigm shift. And the brands that lead it will gain an advantage.