Reckitt Benckiser Accelerates Product Development With AI and Digital Modeling
Reckitt Benckiser Group executives outlined how the company is embedding artificial intelligence and predictive modeling across its innovation process to speed product development, strengthen launches, and cut costs. The consumer health and hygiene company said digital science capabilities are supporting its 4% to 5% growth guidance and its goal to reduce fixed costs below 19% of net revenue by the end of 2027.
Dr. Angela Naef, Reckitt's chief R&D officer, said the company has built its digital science capabilities since 2020, combining predictive science, simulation, and generative AI across the product life cycle-from ideation through optimization. The company's 4,000-plus R&D professionals now run over 10,000 virtual experiments annually, up from fewer than 100 three years ago.
Scale and Adoption Across Brands
Digital science tools are now deployed across all of Reckitt's 11 power brands in more than 20 markets. More than 2,000 colleagues in R&D and marketing have been trained on the capabilities.
The pipeline shows measurable results. Average innovation project size grew 25% year-over-year in 2026 measured by expected incremental net revenue. The power brands pipeline, measured by net revenue from innovations, increased more than 1.5 times since mid-2023. Reckitt launched 29 new innovations in the first quarter of 2026, about 20% more than the same period a year earlier.
Product Examples: Vanish, Lysol, Gaviscon, Dettol
Vanish: Using computational modeling and consumer insights, Reckitt reduced the error rate in predicting consumer perception by 75% for Vanish Turbo. Consumer liking increased from 8.4 to 9.1. The product delivered 6% net revenue growth with a core U.K. retailer after launch.
Lysol Air Sanitizer: Reckitt used computational design alongside aerobiology experts and the U.S. EPA to establish testing methods for reducing airborne viruses and bacteria. The product grew net revenue by about 20% in 2025, now contributes a mid-single-digit percentage to the Lysol portfolio, and carries a gross margin premium of about 100 basis points.
Gaviscon: Digital twins-virtual replicas of products, equipment, and processes-allow Reckitt to simulate scale-up before committing capital and resources. A small batch at Gaviscon's Hull site costs about £25,000 and 30 person hours. A large factory-scale batch costs more than £100,000 and requires more than 300 person hours. Trials can now be simulated in under two hours.
Dettol: Using 3D modeling and simulation, Reckitt redesigned its antiseptic liquid bottle with greater recyclability. The new packaging can deliver up to 400 tons of plastic savings annually, improve pallet efficiency by up to 33%, and save around £5 million per year.
Documentation and the WriteIt Platform
Documentation historically consumed 30% to 40% of R&D time. Reckitt developed WriteIt, a GxP-compliant AI platform for document drafting, literature searches, and protocol generation. The tool can make drafting and reviewing industrial trial reports up to eight times faster.
More than 650 R&D users had been trained on WriteIt by February 2026. Reckitt plans to extend training to more than 2,000 users-roughly half the R&D community-during the rest of the year.
Infrastructure and Governance
Reckitt began investing in cloud and data foundations in 2020 and started its generative AI transformation in 2024. The company built Trinity, its data and AI platform, to power scalable AI applications with compliance controls.
Reckitt's competitive advantage comes from applying AI to proprietary consumer data, product knowledge, and market context rather than relying on generic tools. The company uses a responsible AI framework developed with its legal team and maintains human accountability for AI-supported work.
Executives said adoption involved both enthusiasm and skepticism. Co-designing tools with teams and keeping humans in the lead helped drive acceptance. R&D leadership approached generative AI as a learning opportunity and made tools part of the organization's broader toolbox.
Shanghai Innovation Hub
Reckitt plans to open a global science and innovation center in Shanghai in July. The hub will include live streaming, consumer co-creation, sensory testing, advanced material science, claims development, microbiology, predictive simulation, and scale-up support.
For product development professionals, the takeaway is straightforward: Reckitt's results show that embedding AI and digital modeling into early-stage innovation-not just at the end-reduces prediction errors, accelerates timelines, and improves launch success rates. AI for Product Development and Generative AI and LLM tools are moving from nice-to-have to operational necessity for companies managing large innovation pipelines.
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