The Shift From Tool to Partner
Food manufacturers are embedding AI across new product development, evolving the technology from a back-office research aid to a core engine driving decisions from concept to launch. Major companies including Nestlé, The Coca-Cola Co., Diageo, Mondelez International, PepsiCo and Mars are now deploying AI at multiple stages of NPD, according to industry consultants and software providers working with these firms.
The shift reflects what some call a move from "AI-assisted to AI-agentic" workflows. Rather than using AI to answer discrete questions, manufacturers are deploying systems that autonomously move through entire innovation cycles, identifying trends, generating concepts, screening them against consumer data and producing launch-ready briefs without constant human intervention at each step.
Trend Detection and Consumer Insights
Manufacturers are using AI to identify emerging consumer behaviours earlier in product development. According to Patrick Young, managing director at PRS In Vivo, "manufacturers are using AI to get closer to consumer needs earlier in the process, analysing trends, testing concepts and refining propositions before they ever reach the shelf."
Swiss ingredients supplier Givaudan has built an in-house system called Customer Foresight that combines AI with big data to spot what the company calls "weak signals" of future trends, then refines those signals through human analysis and pattern recognition to suggest product ideas. The ability to reduce guesswork matters in an industry where new product failure rates are high.
Formulation and Reformulation
AI is proving particularly useful in reducing sugar, a persistent challenge for beverage and food brands. Ingredion, a US ingredients company, uses AI to analyse datasets and identify flavour and taste combinations that appeal to consumers. The company says AI has helped develop stevia-based solutions that reduce sugar content by up to 50 percent while maintaining taste, and has created 100 percent sugar reduction options that do not compromise flavour.
AI also accelerates reformulation cycles by modelling ingredient changes and their implications. Will Telford, co-founder and chief technology and product officer at Point74, a UK food lifecycle management software company, says AI helps compress iterations when teams need to test multiple "what if" scenarios around ingredient tweaks.
Data as the Foundation
The deployment of AI in food NPD has become possible partly because food companies have already spent years building rich datasets. These include recipes, cost structures, nutritional profiles and supplier specifications that feed machine learning systems. Telford explains that the real movement is not standalone AI tools being dropped into workflows but rather AI being layered over structured product data that already exists in manufacturing and product lifecycle management systems.
Broader Supply Chain and Sustainability Applications
Beyond NPD, food makers are using AI to address competing pressures: cost targets, regulatory compliance, clean-label demands and shorter launch windows. Sam Stark, CEO and founder of Green Project Technologies, an AI-enabled carbon management platform, says the technology is helping companies model carbon implications of formulation changes or supplier switches before committing to them, shifting sustainability from a constraint to an input in product decisions.
AI is also being paired with robotics and machine vision to improve inspection, handling and consistency during early-stage production, according to Nigel Smith, CEO of TM Robotics, a UK-based robotics distributor specialising in food processing automation.
The Human Role Remains Central
Industry experts generally agree AI is not replacing human creativity in food NPD. Patrick Young notes that "AI is not replacing human creativity. It's acting more as a filter or a co-pilot. It can surface patterns and optimise ideas but it still takes human judgement to create something distinctive, emotionally engaging and brand-relevant."
At Valio, the Finnish dairy company, Dr Kevin Deegan, vice president for innovation, says AI is freeing up time for staff to focus on bigger strategic questions rather than routine work. He argues that time savings from AI-assisted tasks may allow innovation teams to "think beyond the next year, beyond the next two years" and to challenge categories rather than simply maintain existing products.
Even so, staff understandably wonder about job implications. Deegan says the approach should frame AI as enabling creativity rather than replacing it, allowing employees to test ideas with lower risk of failure and to raise voice and suggest innovations without fear.