How AI Is Helping Unilever Foods Stand Out Online and In-Store
Artificial intelligence is rapidly transforming the way consumers discover, choose and purchase food. From the recipes people search online to the brands they ultimately place in their shopping carts, algorithms now play a powerful role in influencing everyday food decisions. For global consumer goods leader Unilever, this shift presents both a challenge and an opportunity—and the company is leaning heavily into AI to ensure its €12.9 billion Foods business remains visible, relevant and competitive.
Across its portfolio of globally recognized food brands—including Knorr, Hellmann’s and Unilever Food Solutions—Unilever is deploying artificial intelligence to accelerate product innovation, improve digital visibility and deliver personalized consumer experiences.
As food discovery increasingly moves online, brands must do more than secure shelf space in stores—they must also earn a place in digital search results, AI-powered recommendations and large language model responses.
Winning Attention in the Age of AI Search
Consumer shopping habits have evolved dramatically in recent years. AI-powered search tools, recommendation engines and conversational assistants are becoming trusted decision-making tools, especially in food and beverage purchasing.
According to recent research, nearly half of consumers who use AI search platforms now rely on these tools to inform food and drink purchase decisions. With users asking tens of thousands of questions every second on platforms like OpenAI’s ChatGPT, competition for digital visibility has never been more intense.
For Unilever Foods, this means adapting marketing strategies to ensure its brands are “algorithm-ready.”
“Our goal is not just to be seen by consumers—but to be found and recommended by the technologies they increasingly trust,” explains Meenakshi Burra, Foods Chief Digital and Information Officer and Chief Data Officer at Unilever.
To achieve this, the company uses advanced AI visibility platforms that monitor how its brands appear across large language models (LLMs) and AI-driven search engines. These tools help teams identify gaps in discoverability and optimize content accordingly.
A notable success story came during preparations for the 2026 “Big Game” in the United States, one of the year’s biggest food-consumption events. Unilever’s Hellmann’s brand discovered it was underperforming in AI search rankings for the phrase “Game Day sandwich recipes.”
The reason? A lack of AI-friendly “listicle” content.
In response, the marketing team rapidly revamped Hellmann’s digital content strategy. They developed new recipe-based list articles, optimized keyword placement, updated recipe descriptions and expanded website content specifically tailored for AI search systems.
The results were immediate and measurable. Hellmann’s improved its visibility ranking by 10 positions and boosted its overall AI visibility score by 19%, dramatically increasing the likelihood that consumers would see and choose its recipes during game-day planning.
Accelerating Product Innovation with AI
While visibility is essential, staying relevant requires continuous innovation—and that’s another area where AI is reshaping Unilever’s food business.
Food trends now move faster than ever. Viral recipes on social media can influence consumer preferences overnight, creating pressure on brands to innovate faster than traditional product development timelines allow.
“Food trends used to evolve over years. Today, they can change in days,” says Olivia Kirby, Director of Integrated Demand Generation for Foods at Unilever. “To stay desirable, brands must innovate at the speed of culture.”
To keep pace, Unilever’s research and development teams are using AI to streamline and accelerate product design.
Traditionally, developing a new food product required lengthy physical testing, multiple iterations and significant resource investment. AI changes that equation by allowing scientists to simulate thousands of recipe variations digitally before moving into physical production.
This technology analyzes ingredient combinations, flavor profiles, texture data and consumer feedback to predict which formulations are most likely to succeed.
According to Heike Steiling, Chief R&D Officer for Unilever Foods, the impact goes beyond efficiency.
“AI isn’t replacing human creativity—it’s enhancing it,” she says. “By handling repetitive testing tasks, it gives our product developers more time to focus on culinary imagination and breakthrough ideas.”
One of the strongest examples is Knorr’s Fast & Flavourful Paste, a recent innovation that benefited directly from AI-driven development.
Using advanced modeling tools, Unilever’s R&D teams digitally tested multiple flavor and texture combinations before beginning physical trials. This significantly reduced the number of real-world experiments needed and ultimately cut development time in half.
That faster speed-to-market enables Unilever to respond more effectively to shifting consumer demand and launch trend-driven products faster than competitors.
Delivering Hyper-Personalized Solutions Through AI
Beyond product development and digital marketing, AI is also helping Unilever deepen customer relationships through personalization.
Today’s consumers increasingly expect tailored brand experiences. Studies suggest that more than 70% of shoppers prefer companies that deliver recommendations and interactions customized to their preferences.
Unilever Food Solutions (UFS), the company’s foodservice division serving restaurants and professional kitchens, is using AI to meet that expectation in a highly targeted way.
Unlike generic recommendation systems that pull information from the open internet, UFS has built its AI ecosystem on a proprietary knowledge base. This includes:
- more than 35,000 chef-created recipes,
- extensive culinary trend research,
- product performance insights,
- and expertise from over 250 professional chefs operating across 75 markets worldwide.
This proprietary data allows UFS to deliver hyper-personalized business recommendations to restaurant operators and chefs.
By combining operational details—such as menu offerings, customer reviews, social media content and website data—with AI analytics, the platform can identify opportunities specific to each foodservice business.
For example, a restaurant might receive recommendations on:
- menu optimization,
- new dish opportunities,
- ingredient substitutions,
- or ways to align with emerging consumer trends.
“This is AI with purpose,” says Nuria Hernández-Crespo, CEO of Unilever Food Solutions. “It turns complex data into practical solutions that help our customers succeed.”
AI as a Competitive Advantage
For Unilever, artificial intelligence is no longer just an efficiency tool—it is becoming a core strategic advantage.
From making brands more discoverable in digital ecosystems to accelerating innovation and enabling deeper personalization, AI is embedded across every stage of the consumer journey.
As algorithms increasingly influence what people eat, buy and cook, food companies that fail to adapt risk becoming invisible.
Unilever’s strategy is clear: if consumers are relying on AI to make decisions, its brands must be the ones AI recommends.
That approach is helping ensure that in a world driven by digital discovery, brands like Knorr, Hellmann’s and Unilever Food Solutions remain not just visible—but truly unmissable.
Source Link:https://www.unilever.com/
