There are many battles in grocery but for many the biggest has always been for visibility and what a lot of marketers call ‘brand salience’, the likelihood that your brand comes to mind in a buying situation. For suppliers, their response is listings, shelf position, promotional slots, retailer relationships, ecommerce search, reviews and category performance. For retailers, it has meant helping shoppers find the right product quickly, while protecting trust around price, quality, availability and provenance.
AI search adds a new weapon in that battle and it is completely different to how shoppers might have done it before, with, say, Google. Shoppers already ask an AI assistant for “the best high protein yoghurt under £2”, “a nut-free lunchbox snack with less than 5g of sugar”, or “the most sustainable washing-up liquid available for delivery today”. A buyer might ask which challenger brands are gaining attention in a category, or which suppliers have the strongest sustainability credentials, writes James Crawford, Managing Director of PR Agency One and AMEC board director.
The answer may be built from retailer listings, product feeds, brand websites, reviews, nutrition data, news coverage, trade media, social media and company reports. PR (behind a lot of media, social and search) has suddenly become more important than ever. The user may never visit the brand website. They may not even begin with a retailer search bar. They may simply accept the AI-generated summary in front of them. OpenAI has already expanded shopping experiences in ChatGPT, including product discovery and merchant product feeds, while payment networks such as Visa and Mastercard are building infrastructure for agentic commerce, where AI agents help users discover, decide and transact with permission.
For grocery, that direction of travel is already setting board meetings on fire. Imagine a shopper asking an AI assistant to plan five weekday meals for a family of four, under a set budget, avoiding certain allergens, prioritising high protein, reducing waste and using products available for delivery tomorrow. In time, an agent may not just suggest the meal plan. It may compare products, check availability, weigh price against preference and populate a basket.
This could reshape one of grocery’s oldest contests: branded, own-label and challenger products fighting for attention. Historically, visibility has been shaped by distribution, shelf position, promotions, retail media and brand investment. AI assistants introduce another intermediary between shopper and shelf. If a customer asks for the best value olive oil, the highest-rated cereal, or a sustainable coffee brand, the answer may be shaped by the quality of the product information and evidence available online before the shopper reaches a retailer website. Strong own-label ranges may benefit from retailer authority, scale and rich ecommerce data, while challenger brands may gain ground if they have clear claims, strong reviews, credible media coverage and consistent product information. Larger brands may lose ground if their public information is fragmented, outdated or too dependent on paid visibility.
AI search can be gamed, at least in the short term. There is already evidence of spam, low-quality content and questionable optimisation tactics appearing in AI-generated results, in much the same way search was manipulated in the early days of Google. But that is a dangerous strategy for serious grocery brands. Businesses that rely on thin content, fake authority or synthetic noise are playing with fire. They may gain temporary visibility, but they are one model update, one source-quality change or one platform crackdown away from disappearing from results entirely.
For established grocery brands, the more durable route is to make public information work harder: product data, PR, social content, search content, reviews, certifications and sustainability evidence all need to tell a consistent story. That does not make AI visibility risk-free, but it builds the kind of evidence base that should survive changes in the way AI tools retrieve and summarise information.
For grocery, product data is now stepping out of the back-office, compliance or ecommerce teams into a top level marketing consideration. It is becoming part of the new shelf. Ingredients, allergens, nutrition, pack size, price, promotions, availability, certifications, sourcing, recycling information and sustainability evidence all help determine whether a product can be understood, compared and recommended.
Poor data creates poor answers. An old retailer listing may show an outdated formulation. A vague sustainability page may be judged against a competitor’s audited evidence. A product may be missed altogether because its attributes are not clearly structured. Worse, inaccurate AI-led shopping answers can direct consumers towards questionable sources.
Visibility is often the first thing we look for in marketing but the better questions to ask your teams are how is the brand being described? What sources are being used? Are the claims accurate? What impact can we see? Which competitors are being recommended instead? What is missing? Is the answer current? Is the model relying on earned media, reviews, product feeds, public records or low-quality pages?
AMEC’s recently published AMEC GEO Principles were created to bring rigour to this emerging field. They set out a practical framework covering three connected areas: upstream reputation signals, search and content readiness, and downstream AI outputs. They also warn against relying on any single score, platform or tool, and argue that AI outputs should be treated as directional evidence rather than absolute truth. A brand’s AI reputation is not created only by the comms team. It is shaped by category data, retailer pages, customer service responses, reviews, product reformulations, recall notices, sustainability reporting, packaging information, earned media, social media and the quality of the brand’s own website.
The practical starting point is an audit. Look upstream at the public information around the brand, its products and its category. Check whether product claims, retailer listings, reviews and earned media are accurate and current. Then look at content readiness: can search engines and AI systems understand the product pages, FAQs, claims and data?
Finally, test the questions shoppers, buyers, journalists and campaigners are likely to ask across different AI tools, recording the outputs, sources and gaps.
The next shelf is the AI generated answer that helps a shopper decide what to buy, a journalist decide what to write, or a buyer decide who deserves a conversation, it sits alongside your store or ecommerce website, or adjacent to marketplaces like Amazon.
Trust has always been grocery’s currency. AI is simply changing where that trust is judged.
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