Unilever is reshaping how consumers discover food brands and how new products move from concept to shelf, using artificial intelligence to accelerate development, sharpen digital visibility and deliver hyper‑personalised support to foodservice operators.

Its €12.9 billion Foods division now treats AI as a strategic engine powering innovation, relevance and growth — and the implications for the wider food and drink trade are significant.

Across retail, recipe search and foodservice, algorithms increasingly influence what people cook, crave and buy. Unilever recognises that brands must now win the attention of both consumers and AI systems.

As Olivia Kirby, director of integrated demand generation, foods, puts it, AI is fuelling the innovation, visibility and personalisation needed to keep Power Brands such as Hellmann’s and Knorr “unmissable, on‑trend and irresistible.”

AI reshapes product discovery in a world ruled by search

Unilever sees a fundamental shift in how consumers find food inspiration. Product discovery no longer happens only on shelves or traditional search engines. It now happens through AI‑driven search and conversational tools, where large language models (LLMs) increasingly determine which brands appear in recipe suggestions, shopping prompts and meal‑planning queries.

Research cited by Unilever shows that nearly 50% of AI search users rely on agentic tools to inform food and beverage purchase decisions. With 29,000 questions asked per second on ChatGPT, the company argues that cutting through the noise has become business‑critical.

To respond, Unilever uses AI search visibility platforms to analyse how its brands perform across LLMs, identify gaps and refine content strategies. The approach mirrors SEO — but for AI‑generated answers rather than search‑engine results pages.

A clear example emerged ahead of the 2026 Big Game in the US. Hellmann’s discovered that it ranked poorly for the prompt “Game Day sandwich recipes.” The brand traced the issue to a lack of listicle‑style content, a format LLMs favour when generating recommendations. Hellmann’s moved quickly: it created a dedicated Game Day sandwich listicle, updated descriptions with relevant keywords, reframed existing recipes into AI‑friendly formats and expanded its recipe section.

The results were immediate. Hellmann’s achieved a 10‑position boost in visibility rankings and almost doubled its overall visibility score — a leap that significantly increased its likelihood of being recommended to consumers searching for relevant recipes.

For the food and drink trade, the message is clear: AI‑optimised content is becoming as important as packaging, merchandising and traditional digital marketing. Brands that fail to adapt risk disappearing from the digital pathways that increasingly shape consumer choice.

AI accelerates product development as food trends speed up

Unilever also uses AI to transform how its R&D teams develop new products. The company argues that food trends now move “at the pace of cultural conversation,” driven by viral recipes, social media and real‑time digital behaviour. To stay relevant, brands must innovate faster than ever.

AI allows Unilever’s scientists to explore thousands of recipe variations in seconds, identifying the strongest directions before physical testing begins. Heike Steiling, chief R&D officer of Foods, says AI is not a replacement for human creativity but a tool that gives developers more time to explore it. By recognising patterns in taste, product data and customer feedback, AI helps teams predict which variants consumers are most likely to love.

Knorr’s Fast & Flavourful Paste demonstrates the impact. R&D teams used AI to digitally test a wide range of recipes before any live trials. By identifying the best flavour and texture combinations upfront, they cut development time in half, reducing the need for extensive physical testing and accelerating the path from concept to cart.

For producers, this signals a shift in how innovation pipelines may evolve across the industry. AI‑assisted development could reduce costs, shorten timelines and increase the success rate of new launches — especially in categories where flavour, texture and convenience trends change rapidly.

Hyper‑personalisation becomes a competitive advantage in foodservice

R&D in the lab.

Unilever Food Solutions (UFS) is applying AI to deliver hyper‑personalised recommendations to chefs and operators. With research showing that 71% of consumers expect tailored interactions, UFS sees personalisation as a critical differentiator for foodservice businesses.

Unlike generic AI systems that scrape the internet, UFS builds its digital experience on proprietary data:

• 35,000 chef‑authored recipes
• extensive industry and trends research
• culinary and product resources
• the expertise of 250 UFS chefs across 75 markets

By combining this data with real business details — menus, customer reviews, website information and publicly available social content — UFS generates real‑time analysis tailored to each operator’s needs.

UFS CEO Nuria Hernández‑Crespo describes this as AI applied with purpose, turning data into practical insights that help operators solve genuine challenges and seize opportunities. For foodservice customers, this means more relevant menu ideas, operational guidance and product recommendations — all personalised to their business.

For the wider trade, UFS’s approach signals how AI could reshape B2B relationships. Suppliers may increasingly use proprietary data and AI‑driven insights to support customers, strengthen loyalty and differentiate their service models.

A new competitive landscape shaped by algorithms

Across product discovery, innovation and foodservice support, Unilever is using AI to strengthen its Power Brands and stay ahead of shifting consumer expectations. The company argues that brands must now win the attention of both people and algorithms — a dual audience that will define future growth.

AI is helping Unilever:

• optimise visibility across LLM‑driven search
• accelerate innovation by predicting winning product variants
• deliver personalised support to foodservice operator
• stay relevant as food trends evolve at unprecedented speed

For the food and drink industry, the implications are far‑reaching. AI is becoming a frontline driver of brand relevance, product success and customer engagement. Companies that embrace AI‑powered visibility, development and personalisation will be better positioned to thrive in a market where algorithms increasingly shape what consumers see, cook and buy.