Unilever and Reckitt Cut Development Timelines Using AI for Search and Product Testing
Unilever and Reckitt are embedding AI across their organizations to speed up product development and improve how consumers find their brands online. Both companies report measurable gains: Unilever doubled its search visibility for certain products, while Reckitt expects 25% incremental revenue growth on average projects.
Unilever's AI Search Strategy
Unilever's foods business uses AI search visibility platforms to track how its Hellmann's and Knorr brands appear in large language models and AI-driven search results. The company identified gaps where its content wasn't showing up and adjusted its strategy accordingly.
Before the 2026 Super Bowl, Unilever discovered that Hellmann's had poor visibility for the search prompt "Game Day sandwich recipes." The brand lacked listicle-style content that AI search tools favor. Unilever created a dedicated Game Day sandwich listicle, updated keyword descriptions, reformatted existing recipes into AI-friendly formats, and expanded its recipe section.
The changes produced a 10-position boost in visibility rankings and nearly doubled the visibility score above Unilever's 10% benchmark.
Meenakshi Burra, chief digital and information officer for the foods business, said the company uses these platforms to "understand how our brands perform across large language models, identify any gaps and refine content strategies as needed."
Accelerating Product Development
Unilever also uses AI to test product variations faster. Instead of evaluating individual recipe ideas, the company can now test thousands of variations in seconds, identify patterns in taste and customer feedback, and predict which variants will resonate before physical trials begin.
Heike Steiling, chief R&D officer of foods, said AI is "changing how we discover, collaborate and innovate" for the company's scientists.
Reckitt's Approach: Digital Science at Scale
Reckitt deployed AI-enabled tools across more than 20 countries and trained over 2,000 employees in R&D and marketing to use the new capabilities. The company combines predictive science and simulation technology with proprietary data to reduce physical testing and accelerate time to market.
The results so far:
- Up to 70% time savings on lower-value tasks in R&D
- 25% year-over-year expected incremental net revenue for average project sizes
Angela Naef, chief R&D officer at Reckitt, said the shift changes how innovation works. "Innovation is no longer about having good ideas," she said. "It's about how quickly you can prove them, how confidently you can scale them and how consistently you can repeat that success."
Both companies expect to extend these capabilities further through 2026. For product development teams, the pattern is clear: AI reduces cycle time and lowers the cost of testing ideas before committing to full-scale production.
Learn more about AI for Product Development and how Generative AI and LLM are being applied in practice.
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