How Food and Drink Brands Can Win AI’s Trust

Featured in The AI Journal

Sam Barker, Head of Omnichannel Search & Insights

Written bySam BarkerEMEA | Head of Omnichannel Search & Insights

Sam brings over a decade of search experience, specialising in search strategy innovation to help brands stay relevant and visible as consumer search behaviour evolves. His career spans various sectors including B2C e-commerce and B2B finance, with notable clients such as ASDA, Uniqlo, JP Morgan and Santander. Before joining Greenpark, Sam previously helped lead the SEO proposition at Dentsu.

Can you believe that 58.5% of Google searches now end in zero clicks?

Consumers are increasingly turning to large language model (LLM) tools, like ChatGPT, Gemini and Google’s AI overviews, to discover, evaluate and compare the way they eat and drink.

And honestly, who can blame them? LLM search collapses the entire shopping funnel into one place: inspiration, product info, suitability, ratings and reviews. What used to be a journey across multiple tabs is now compressed into a single interaction. For consumers it’s a one stop shop while for brands, it’s a whole new frontier to conquer.

Interestingly, within the food and drink space, it’s novice cooks and culinary enthusiasts leading the charge. According to Greenpark’s latest data, among AI users searching for recipes, 74% turn to ChatGPT, while 52% use Gemini. Dedicated cooking tools are also gaining traction: ChefGPT grabs 36% of searches, followed by Mr Cook and SuperCook at 28% each.

In addition to pure convenience, these tools help people learn, experiment and fall in love with cooking, meaning the brands that show up here are connecting with people who really care about food.

That growing reliance on AI-driven answers introduces a competition centred less on ranking positions and more about how your brand is interpreted by LLMs that inform the customer how they should feel about you.

The rise of algorithmic sentiment

Which brings us to the tricky bit of getting in front of these customers to begin with: influencing algorithmic sentiment.

Before you start panicking, no AI doesn’t have feelings, and we aren’t all trapped inside a Matrix style simulation.

“Sentiment” is how an LLM interprets and communicates trust, reputation and tone signals across your digital footprint. Product reviews, forums, social posts, your website, all of it counts.

And the story AI tells off the back of all this becomes the default answers for queries like “which chocolate brand is best for baking?” The model is making a judgement call based on the consistency and depth of information it has available. Which means that if your presence across the web is patchy or contradictory, you’re far less likely to feature.

This is where food and drink brands can end up working against themselves without realising it. Inconsistent product descriptions across retailers, outdated ingredient information, missing nutritional data or poorly managed reviews all create friction for an LLM trying to understand who you are and what you offer. Over time, that weakens the confidence it has in presenting your brand as an answer.

Once you see it through that lens, the next step becomes less about quick wins and more about operational alignment.

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