AI Shopping Assistants Are Coming for Bland Brands
Jessica Kent
Head of Agency
A customer who used to browse your website, compare a few products and make their own judgement is now asking an AI assistant to do the sorting for them. They might ask for the best garden furniture for a small patio, the most reliable appliance for a rental property or the safest skincare option for sensitive skin. The assistant pulls together the options, checks reviews, compares features, summarises the trade-offs and gives an answer that feels good enough to act on.
Definitely handy for the customer, but uncomfortable for a lot of brands, because in that moment, your website may not get the chance to do the selling. Instead, your business could be reduced to a short paragraph in a comparison against three competitors who look annoyingly similar. That’s the bit many eCommerce teams are not taking seriously enough.
AI shopping assistants will not only change how people search, but they’ll also change how much of your brand reaches the customer before a buying decision is made. For brands with a clear point of view, strong customer proof and useful content, that could be a new route into consideration. For brands relying on generic promises about quality, service and value, it could be brutal.
At Brave, we’re not looking at AI shopping as a shiny new channel to bolt onto the side of a marketing plan. We’re looking at it as a stress test. It’ll show which brands have built something customers can recognise and which ones have been coasting on product, price and performance media. The honest truth is that AI won’t make weak brands stronger; it’ll make them easier to compare.
This isn’t one of those vague “future of retail” predictions that sound impressive and mean very little. Google has already added AI shopping features into Search and AI Mode, including conversational product discovery, price tracking and virtual try-on tools. OpenAI has introduced shopping research in ChatGPT, where users can describe what they need and receive a researched buying guide rather than working through tons of tabs themselves. OpenAI also gives merchants the option to share product feeds with ChatGPT so products can be represented in shopping experiences.
The behaviour is moving quickly, too. NielsenIQ reported in 2026 that 42% of consumers now use AI tools to shop, with AI influencing discovery, comparison and selection. That doesn’t mean every customer is ready to let an assistant buy on their behalf, but it does show that AI is already becoming part of the normal shopping process.
A recent study of an AI shopping assistant inside Ctrip, China’s largest travel platform, found that people often used the assistant alongside traditional search, especially for exploratory queries that are difficult to phrase as standard keywords. Customers don’t always know the product name, category term or technical phrase. They know the situation they are in, the problem they want solved, the budget they have and the thing they are worried about getting wrong. That’s where AI assistants become useful.
For marketers, this should ring alarm bells. Not panic bells, but proper commercial ones. If a customer reaches your website after an assistant has already framed the decision, your brand has less room to shape the conversation from scratch. You’re entering a buying journey that has already started without you.
Some brands will respond by churning out more content, because that’s often the first reaction when search behaviour changes. In our experience, that’s usually how brands create a bigger mess. Publishing more bland content doesn’t protect your brand. It gives AI more bland material to summarise.
AI shopping assistants are designed to reduce effort. They take a crowded market and make it feel manageable, cut through options, compare the obvious factors and help the customer move closer to a decision. That’s great when you are buying, but less great when you’re the brand being compressed into a few lines.
If your identity is weak, this is where things get ugly. You become a row in a table. You become “similar to X but slightly cheaper” or “well-reviewed but more expensive” or “good option if delivery speed matters”. That might still win you some sales, but it’s not a strong place to build from. The thinner your brand, the more the assistant has to rely on functional comparison.
This is why we are fairly blunt about brand work. It’s not decoration. It’s not the soft bit you do after the “real” marketing is sorted. Brand is one of the things that stops your paid media from turning into a discount tap. It stops your SEO from becoming a pile of forgettable advice pages. It gives your email marketing a role beyond sending another “sale ends tonight” campaign. Most brands say they care about differentiation, but fewer are willing to do the work that makes them genuinely different in the eyes of a customer.
A stronger brand gives both people and AI systems something clearer to work with. It might be known for honest buying advice, specialist category knowledge, a loyal customer base or a brilliant aftercare, the angle depends on the business. The important part is that it shows up everywhere, not only on the about page.
If the only place your brand feels distinctive is in a workshop document, it’s not distinctive enough.
A lot of teams still treat product feeds, structured data and product descriptions as housekeeping. Necessary, yes, but hardly brand-defining. That mindset is outdated.
If AI shopping tools are using product feeds, merchant data, third-party sources, reviews and onsite content to understand your products, then every one of those inputs affects how your brand may be represented. OpenAI’s merchant guidance talks about sharing catalogues, product feeds and promotions so products can be properly represented inside ChatGPT shopping experiences. That’s a technical requirement, but it has a brand consequence.
Messy product information makes your brand look messy. Thin descriptions make your offer look thin. Inconsistent naming creates confusion. Weak attributes force comparison on whatever data is available. Poor imagery leaves questions unanswered. Generic copy makes you sound generic, because frankly, you’re giving the system nothing better to use.
This isn’t about stuffing your feed with fluffy brand claims. Nobody needs a product title that reads like it has swallowed a manifesto. It’s about being clear, complete and commercially useful.
A product page should explain who the item suits, what problem it solves, where it performs well, what trade-offs exist and why a customer might choose it over another option. A product feed should be accurate and consistent. A review strategy should encourage customers to talk about real usage, not only leave a star rating and disappear. Your images should answer buying questions, not simply show the product from five sterile angles on a white background.
There’s going to be an explosion of mediocre AI-shopping content. You can see it coming a mile off. “Best X for Y” guides written with no real opinion. Comparison pages that sit on the fence because the brand is too nervous to say anything useful. FAQs that answer obvious questions while ignoring the objections customers actually have. Blog posts that technically cover a topic but feel like nobody involved has ever spoken to a buyer. This kind of content is easy to produce and easy to forget.
Good eCommerce content has judgment. It helps people make a decision, says when the cheaper option is perfectly fine and when it is a false economy, and explains who a product suits and who should look elsewhere. It answers the question the customer is slightly embarrassed to ask and makes the reader feel like somebody knowledgeable is helping them, rather than a content calendar being filled. That’s the standard brands need to aim for if they want to stay visible and memorable in AI-assisted journeys.
Your content should come from the places where real customer friction shows up. These are full of language your customers actually use, and they often reveal the concerns your marketing team has stopped noticing because you are too close to the product. It’s not complicated, but it does require teams to listen. Plenty of brands would rather publish ten new blog posts than improve the one page, causing confusion.
A strong customer community doesn’t have to mean a loud Facebook group, a founder podcast or a branded hashtag that nobody uses unless they are being paid. Some brands force community in ways that feel painfully artificial, and customers can tell.
The better version is quieter and more useful. It’s the customer base that gives your brand a life outside your own marketing, reviews that describe genuine use, or customers sharing photos that look like real life, not a campaign shoot. AI can summarise social proof, but it can’t invent the trust behind it.
That trust matters because it creates brand memory. If someone discovers you through an AI assistant, buys once and then forgets your name, you’ve rented a sale. If they remember the experience, come back directly, sign up for email, leave a useful review or recommend you to someone else, you’ve started to build protection.
This is why retention should not sit at the bottom of the priority list. Email has a major role here, too. A proper email marketing strategy gives you a direct line to customers without relying entirely on search results, social algorithms or AI assistants. Too many brands only send emails when they have a sale to push, which is why their lists go cold, and their customers only respond to discounts. Email should help people choose better, use the product properly, come back at the right time and feel part of the brand’s world.
The commercial point is simple: owned audiences become more valuable when borrowed discovery gets less predictable.
Paid media will still matter. Anyone claiming AI shopping kills paid media is probably trying to get attention. Customers still need to be reached, demand still needs to be captured, and products still need to be sold.
The problem is that paid media gets blamed for brand weaknesses it didn’t create.
If every ad screams discount, customers remember the discount. If every Shopping campaign relies on the same basic product information as everyone else, the platform has very little to work with. If Meta creative shows nice product shots but no real reason to care, performance will eventually get harder.
The best media strategy in the world can’t make a forgettable brand memorable on its own. It can amplify what is there, test angles, and help you learn what customers respond to. It can’t magic up differentiation if the business has never done the thinking.
This matters even more in an AI-assisted shopping journey. If an assistant has already framed the customer’s options, your paid activity needs to reinforce a clear reason to choose you. That could be expertise, aftercare, product quality, range depth, speed, fit, sustainability, or community. The important part is that it appears consistently across the feed, the ad, the landing page, the reviews and the follow-up journey. Consistency should feel like the same person turning up in different rooms, not the same sentence being copied across every channel.
A lot of brands misunderstand what “human” means. They think it means being casual, chatty or throwing in a few playful lines. Sometimes that works, but often, it feels like a brand trying to be everyone’s mate while still sending automated support replies.
A human-feel brand is specific. A product page that says which option is best for daily use rather than pretending they are all equally perfect. A returns page written in normal language. A post-purchase email that helps rather than immediately chasing the next order. A help article that gives the answer without making someone scroll through a lecture.
These details build trust because they feel considered. They also give AI systems richer material to understand and repeat. If your site contains specific, useful, customer-led information, the assistant has more to work with. If your site contains vague claims and thin content, don’t be surprised when the summary feels flat.
This is where AI can be useful internally, as long as it is kept in its lane. It can help organise information, draft structures, analyse themes and speed up production. It shouldn’t be left to decide what your brand believes, what your customers care about or what good judgment sounds like. Those things need people.
The sensible response to AI shopping is not panic. It’s also not pretending that nothing is changing. The sensible response is to strengthen the parts of your brand that should have been stronger anyway.
Start with your best-selling products and highest-value categories. Look at them as if you were an AI assistant trying to summarise the options for a busy customer. Is the information complete? Are the differences between products clear? Do the reviews add useful context? Does the page explain who the product suits? Can a customer understand why your brand is a better choice without digging around for clues?
Then look at your content. Be honest about what is useful and what is there because someone thought the blog needed feeding. Weak content doesnt’ become valuable because AI exists. Improve the pages that influence decisions. Write guides with a point of view. Build comparison content that helps people choose. Use customer questions as source material rather than guessing what people want to know.
Next, tighten your customer signals. Ask for better reviews. Use post-purchase emails to learn what customers valued. Bring customer service insight into product page improvements. Turn repeat objections into content. Use paid media data to understand the language and angles that create interest. Treat retention as part of brand-building, not a separate revenue channel that only wakes up during promotions.
Finally, make sure the business is saying the same thing in all the places that matter. SEO, paid media, email, CRO, product, customer service and brand can’t all run on different versions of the truth. AI shopping assistants will make inconsistencies easier to expose, and customers will feel it too.
The brands that win won’t be the loudest; they will be the clearest. They will have better information, stronger customer proof, sharper content and a more recognisable reason to exist. They will use automation where it helps, but they won’t let it sand away the parts of the brand that people actually remember.
AI shopping assistants are coming for bland brands because bland brands are easy to compare. The work now is to make your brand harder to flatten.
