As artificial intelligence-powered web browsers and agentic search tools such as ChatGPT, Perplexity and Gemini-enhanced Chrome become the default entry point for online discovery, grocery retailers are entering a new era of digital visibility.
For produce departments in particular, the shift is both an opportunity and a wake-up call: These AI agents will increasingly determine which retailers get recommended, which products surface first and which stores are seamlessly added to a customer's cart.
Nate Barad, vice president of product marketing for Algolia, says this new landscape requires grocers to treat AI systems as a new type of customer, one that interprets product data, evaluates who has the best answer and then makes recommendations on behalf of human shoppers.
“Your fastest-growing user is the agent,” Barad says. “We have to prepare for an agentic customer the same way as a human customer. It's not either-or.”
To stay visible in AI-driven search results — and to make sure fresh produce is recommended accurately — retailers must begin rethinking the way they structure, enrich and distribute their product data.
Barad recommends these six steps to help grocers prepare for AI-powered browsing:
1. Make Product Data Machine-Readable and Machine-Lovable
The first priority is product data quality, Barad says. AI systems need structured, consistent and complete data in order to understand and recommend products.
Barad breaks this into two categories:
- Machine-readable: inventory data, nutritional information, naming consistency and the basic hygiene that allows AI tools to understand what the product “is.”
- Machine-lovable: the kind of additional context that helps an AI agent “choose” your product over others, such as FAQs, conversational descriptions, storage tips, ripeness guidance and culinary applications.
This machine-lovable content is especially critical for fresh produce.
“Nutrition is going to be first,” Barad says. “But what the agent really wants is the information that isn't normally in your index, like whether a chicken breast is used in chicken tikka masala. For produce, that could be what apples are best for a pie or which are better for keto.”
For grocers, this means enriching product catalogs with details they've never had to include before, such as:
- Best uses (e.g., fuji apples for snacking; granny smith for pies).
- Dietary attributes (low-sugar, keto-friendly produce items).
- Ripeness stages and storage instructions.
- Recipe compatibility.
- Frequently asked questions.
This new metadata helps AI answer not just “Where can I buy Honeycrisp apples?” but also “Which apples should I buy for apple pie on Thursday?” — and recommend your store in the process, Barad says.
2. Prioritize Data Enrichment to Win the AI Auction
AI agents don't simply crawl a website and show every retailer equally. They conduct what Barad calls a “mini auction,” analyzing multiple data sources before deciding which retailer gets recommended.
“Is it the type of information that gets you recommended, that gets you chosen as the answer by the agent?” he explains.
Conversational metadata, usage suggestions, recipe links and problem-solving content make a retailer more competitive in this silent AI bidding process.
For produce, Barad says this includes consumer-driven needs such as:
- “What can I make with half a head of cabbage and two onions?”
- “Which tomatoes are best for bruschetta?”
- “What produce items fit a low-FODMAP diet?”
AI agents surface the retailer whose data best answers these questions, not necessarily the lowest price or the closest store.
3. Prepare for Zero-Click Shopping
As AI-driven experiences like Walmart's GPT-powered shopping carts emerge, Barad expects browsing and purchasing to become more conversational, more personalized and less dependent on navigating retailer websites.
He warns retailers to prepare for zero-click environments, where a shopper may never visit their site at all.
“Your goals are going to be different,” he says. “You may not get a view or a click-through. Goals will be follow-up questions, voice add-to-carts and recurring personalized purchases: ‘Order me the same tomatoes I got last week; those were delicious. Never order me those tomatoes again.'”
This shift favors retailers whose product data is rich enough to support personalized guidance, especially for produce, which often relies on sensory qualities and contextual uses.
4. Be Ready for Problem-Solving Queries
AI-powered shopping is less task-driven (search apples, find results) and more solution-oriented (Which apple is best for my diabetic diet?). Barad expects grocers to see more problem-solving queries, particularly around:
- Meal planning
- Dietary restrictions
- Substitutions
- Nutrition comparisons
- Cooking advice
This is where produce departments can shine. Shoppers will increasingly ask agents:
- “What vegetables should I eat to boost fiber this week?”
- “Which greens last longest in the fridge?”
- “Suggest a produce-focused shopping list for a family of four.”
Retailers prepared with detailed, enriched data are more likely to appear in these high-intent recommendations.
5. Adopt the Model Context Protocol
One of Barad's strongest recommendations is for retailers to ask their technical teams about Model Context Protocol, or MCP — a new standard that allows grocers to securely make their catalogs available directly to AI systems like OpenAI, Amazon and others.
“That's the sanity check to the first question: Is my data even machine-readable? Can I transact in this new internet ecosystem?” he says.
For retailers, MCP is the difference between AI pulling unverified, scraped information from your website or AI using your official, structured product data, the version most likely to surface correctly in search.
6. Don't Assume Your Current Data Practices Are Enough
Barad's final caution to retailers: If you do nothing, AI engines will still pull your data, but in messy, incomplete ways that leave you at a disadvantage.
“If you're doing nothing, that's what's happening,” he says. “Your data is being scraped. You have to prioritize the data you're feeding these engines.”
Thus, retailers need intentional data pipelines, not passive ones, Barad says.
AI-powered browsers represent a foundational shift in how consumers discover and shop for groceries, even fresh produce. To stay visible, grocers must begin treating AI tools as customers who need clear, enriched and comprehensive information to make decisions.
With the steps Barad outlines, produce departments can do more than adapt, they can lead. In an era when shoppers increasingly ask AI “What's the best apple for my pie?” retailers who invest in rich, machine-lovable product stories will be the ones whose aisles appear at the top of the answer.
