[{"data":1,"prerenderedAt":150},["ShallowReactive",2],{"s70FSdupUHXt_1isTsdq-ORQcrd00BNKxMvNd0HLxSg":3,"_apollo:default":148,"_apollo:identified":149},{"allSettings":4,"seo":10,"posts":21},{"customSettings":5,"__typename":9},{"urlFront":6,"urlPreview":7,"__typename":8},"https://blog.3ds.com","https://blog-build-prd.itvpc.3ds.com","CustomSettings","Settings",{"social":11,"openGraph":17,"__typename":20},{"twitter":12,"__typename":16},{"cardType":13,"username":14,"__typename":15},"summary_large_image","dassault3ds","SEOSocialTwitter","SEOSocial",{"defaultImage":18,"__typename":19},null,"SEOOpenGraph","SEOConfig",{"nodes":22,"__typename":147},[23],{"id":24,"slug":25,"title":26,"uri":27,"excerpt":28,"locale":29,"featuredImage":32,"tableOfContents":40,"content":47,"date":48,"translations":49,"author":50,"tags":63,"globalTags":79,"brands":94,"industries":97,"keywords":125,"seo":135,"__typename":146},"cG9zdDozMDMwODg=","how-ai-is-cutting-rd-time-and-costs-in-food-formulation","How AI Is Cutting R&D Time and Costs in Food Formulation","/industries/consumer-packaged-goods-retail/how-ai-is-cutting-rd-time-and-costs-in-food-formulation","\u003Cp>R&D must now play a key role in next-generation formulation, transforming how innovation is conceived, designed and delivered.\u003C/p>\n",{"locale":30,"__typename":31},"en_US","Locale",{"node":33,"__typename":39},{"large":34,"__typename":35,"medium_large":34,"thumbnail":36,"srcSet":37,"sizes":38},"https://blog-assets.3ds.com/uploads/2026/06/food-formulation.png","MediaItem","https://blog-assets.3ds.com/uploads/2026/06/food-formulation-150x150.png","https://blog-assets.3ds.com/uploads/2026/06/food-formulation-300x168.png 300w, https://blog-assets.3ds.com/uploads/2026/06/food-formulation.png 690w","(max-width: 300px) 100vw, 300px","NodeWithFeaturedImageToMediaItemConnectionEdge",[41,42,43,44,45,46],"The Old Model Is Breaking Down|the-old-model-is-breaking-down-0","Key Trends Driving AI Adoption in Formulation|key-trends-driving-ai-adoption-in-formulation-1","Breaking Down Silos with Cross-Functional Intelligence|breaking-down-silos-with-cross-functional-intelligence-2","What This Looks Like in Practice: BIOVIA as an Example|what-this-looks-like-in-practice-biovia-as-an-example-3","Common Pitfalls to Avoid When Adopting AI Formulation Tools|common-pitfalls-to-avoid-when-adopting-ai-formulation-tools-4","The Road Ahead for Food and Beverage Formulation|the-road-ahead-for-food-and-beverage-formulation-5","\n\u003Cp>The pressure on food and beverage formulation teams has never been more intense. Consumer preferences shift faster than product development cycles. Regulatory requirements grow more complex. Ingredient supply chains remain unpredictable. And the demand for cleaner, more sustainable products keeps rising—all while costs must stay under control.\u003C/p>\n\n\n\n\u003Cp>Traditional formulation approaches weren’t built for this pace. The answer, increasingly, is artificial intelligence.\u003C/p>\n\n\n\n\u003Cp>AI-powered formulation tools are changing how R&D teams work—not by replacing human expertise, but by amplifying it. Here’s what formulation leaders need to know about where the technology is heading and why it matters now.\u003C/p>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"the-old-model-is-breaking-down-0\">\u003Cstrong>The Old Model Is Breaking Down\u003C/strong>\u003C/h2>\n\n\n\n\u003Cp>For decades, food and beverage formulation followed a familiar path: hypothesis, bench trial, sensory evaluation, iteration. Repeat. It works, but it’s slow, expensive and increasingly misaligned with market reality.\u003C/p>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"980\" height=\"636\" src=\"https://blog-assets.3ds.com/uploads/2026/06/old-formulation.png\" alt=\"a black and white image of coffee beans in test tubes meant to reflect older, more data methodologies to test food\" class=\"wp-image-303090\" style=\"aspect-ratio:1.54091270630344;width:407px;height:auto\" srcset=\"https://blog-assets.3ds.com/uploads/2026/06/old-formulation.png 980w, https://blog-assets.3ds.com/uploads/2026/06/old-formulation-300x195.png 300w, https://blog-assets.3ds.com/uploads/2026/06/old-formulation-768x498.png 768w\" sizes=\"auto, (max-width: 980px) 100vw, 980px\" />\u003C/figure>\n\n\n\n\u003Cp>\u003C/p>\n\n\n\n\u003Cp>A single reformulation can take months and dozens of trial runs. Multiply that across a portfolio and the resource cost becomes significant. Add clean label targets, supplier volatility and cross-functional pressure from R&D, quality, regulatory and procurement teams, and the strain becomes clear.\u003C/p>\n\n\n\n\u003Cp>The industry needs a smarter approach. AI-powered formulation platforms are delivering exactly that.\u003C/p>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"key-trends-driving-ai-adoption-in-formulation-1\">\u003Cstrong>Key Trends Driving AI Adoption in Formulation\u003C/strong>\u003C/h2>\n\n\n\n\u003Cp>\u003Cstrong>Accelerated Ingredient Screening\u003C/strong>\u003C/p>\n\n\n\n\u003Cp>AI processes vast ingredient databases—functional properties, compatibility data, regulatory status and cost profiles—in a fraction of the time it takes a human team. Rather than trialing 20 candidate ingredients, a formulator can narrow the field to three or four with high predicted performance before a single experiment begins. According to the \u003Ca href=\"https://www.ift.org/food-technology-magazine/how-ai-is-revolutionizing-product-development\">Institute of Food Technologists\u003C/a>, leading companies like Unilever are already running millions of recipe combinations before any bench trial begins.\u003C/p>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"983\" height=\"621\" src=\"https://blog-assets.3ds.com/uploads/2026/06/ai-formulators.png\" alt=\"Two formulators leveraging AI to develop cleaner and more sustainable food and beverage formulations\" class=\"wp-image-303091\" style=\"aspect-ratio:1.5829333060974364;width:571px;height:auto\" srcset=\"https://blog-assets.3ds.com/uploads/2026/06/ai-formulators.png 983w, https://blog-assets.3ds.com/uploads/2026/06/ai-formulators-300x190.png 300w, https://blog-assets.3ds.com/uploads/2026/06/ai-formulators-768x485.png 768w\" sizes=\"auto, (max-width: 983px) 100vw, 983px\" />\u003C/figure>\n\n\n\n\u003Cp>\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Predictive Formulation and Digital Experimentation\u003C/strong>\u003C/p>\n\n\n\n\u003Cp>Machine learning models trained on historical data, sensory outcomes and quality parameters can suggest starting formulas, predict how ingredient changes affect texture or shelf life, and flag failure points before physical trials begin. \u003Ca href=\"https://forwardfooding.com/blog/foodtech-trends-and-insights/ai-powered-innovation-in-food-formulation-and-production/\">Forward Fooding’s analysis of AI in food formulation\u003C/a> shows that companies adopting predictive tools have cut R&D cycles by up to 60%, with faster go-to-market timelines across both reformulation and new product development.\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Reformulation for Clean Label and Regulatory Changes\u003C/strong>\u003C/p>\n\n\n\n\u003Cp>Clean label has moved from trend to expectation. AI tools flag ingredients that may conflict with emerging regulations, suggest functional alternatives and model how a reformulation affects the nutritional profile. A peer-reviewed review in \u003Ca href=\"https://www.sciencedirect.com/science/article/pii/S2590157524007557\">\u003Cem>Food Chemistry: X\u003C/em>\u003C/a> confirms that AI techniques—including machine learning and neural networks—are increasingly central to product development, quality compliance and regulatory alignment.\u003C/p>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"228\" src=\"https://blog-assets.3ds.com/uploads/2026/06/clean-label-examples-1024x228.png\" alt=\"an assortment of food claims that could represent 'clean label' formulation\" class=\"wp-image-303092\" style=\"aspect-ratio:4.48874085873579;width:368px;height:auto\" srcset=\"https://blog-assets.3ds.com/uploads/2026/06/clean-label-examples-1024x228.png 1024w, https://blog-assets.3ds.com/uploads/2026/06/clean-label-examples-300x67.png 300w, https://blog-assets.3ds.com/uploads/2026/06/clean-label-examples-768x171.png 768w, https://blog-assets.3ds.com/uploads/2026/06/clean-label-examples-1536x342.png 1536w, https://blog-assets.3ds.com/uploads/2026/06/clean-label-examples-2048x456.png 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" />\u003C/figure>\n\n\n\n\u003Cp>\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Supplier and Ingredient Volatility Management\u003C/strong>\u003C/p>\n\n\n\n\u003Cp>Supply chain disruptions have forced companies to reformulate on short notice. AI platforms model alternative ingredient scenarios in advance, identifying substitutes that maintain formula integrity without compromising quality or compliance. \u003Ca href=\"https://beyond.ai/blog/a-case-for-embracing-ai-for-blend-formulation-in-the-food-and-beverage-industry\">Beyond AI’s assessment of blend formulation\u003C/a> highlights how real-time cost analysis and AI-driven substitution modeling help \u003Ca href=\"https://blog.3ds.com/brands/delmia/the-future-of-food-beverage-manufacturing-efficiency/\" type=\"link\" id=\"https://blog.3ds.com/brands/delmia/the-future-of-food-beverage-manufacturing-efficiency/\">manufacturers \u003C/a>stay profitable as markets fluctuate.\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Sustainability by Design\u003C/strong>\u003C/p>\n\n\n\n\u003Cp>Leading companies are building sustainability into formulation from the start—evaluating ingredients for carbon footprint, water use and sourcing transparency alongside functional performance. AI tools let formulators weigh those trade-offs within a single workflow, so sustainability decisions get made during formulation, not as an afterthought. Research in \u003Ca href=\"https://doi.org/10.1038/s41538-025-00441-8\">\u003Cem>npj Science of Food\u003C/em>\u003C/a> makes the case that AI has a critical role in designing nutritious, sustainable food systems at scale.\u003C/p>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"breaking-down-silos-with-cross-functional-intelligence-2\">\u003Cstrong>Breaking Down Silos with Cross-Functional Intelligence\u003C/strong>\u003C/h2>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"683\" src=\"https://blog-assets.3ds.com/uploads/2026/06/centralized-data-1024x683.jpeg\" alt=\"Hand touching central node of connected digital network interface. Concept of system integration, data connectivity, network structure, digital ecosystem, technology solution, information management.\" class=\"wp-image-303093\" style=\"aspect-ratio:1.5000120980425367;width:467px;height:auto\" srcset=\"https://blog-assets.3ds.com/uploads/2026/06/centralized-data-1024x683.jpeg 1024w, https://blog-assets.3ds.com/uploads/2026/06/centralized-data-300x200.jpeg 300w, https://blog-assets.3ds.com/uploads/2026/06/centralized-data-768x512.jpeg 768w, https://blog-assets.3ds.com/uploads/2026/06/centralized-data-1536x1024.jpeg 1536w, https://blog-assets.3ds.com/uploads/2026/06/centralized-data-2048x1365.jpeg 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" />\u003C/figure>\n\n\n\n\u003Cp>R&D, quality, regulatory and procurement teams too often work from separate systems with separate data. The result is decisions made on incomplete information.\u003C/p>\n\n\n\n\u003Cp>Modern AI formulation platforms create a shared environment where formulation data, quality requirements, regulatory constraints and procurement variables live together. This speeds up decision-making and reduces costly errors that come from cross-functional miscommunication.\u003C/p>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"what-this-looks-like-in-practice-biovia-as-an-example-3\">\u003Cstrong>What This Looks Like in Practice: BIOVIA as an Example\u003C/strong>\u003C/h2>\n\n\n\n\u003Cp>Dassault Systèmes BIOVIA provides a connected platform where food and beverage scientists can manage formulation data, screen ingredients, design experiments digitally and track regulatory status—all in one environment. \u003Ca href=\"https://www.3ds.com/products/biovia/ai-powered-formulation-development\" type=\"link\" id=\"https://www.3ds.com/products/biovia/ai-powered-formulation-development\">BIOVIA’s capabilities\u003C/a> support AI-powered predictive modeling, data-driven ingredient selection and structured experimental design. Teams move from concept to compliant formula faster, with better traceability throughout the development cycle.\u003C/p>\n\n\n\n\u003Cp>It’s not a replacement for scientific expertise. It’s a platform that makes that expertise more productive.\u003C/p>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"common-pitfalls-to-avoid-when-adopting-ai-formulation-tools-4\">\u003Cstrong>Common Pitfalls to Avoid When Adopting AI Formulation Tools\u003C/strong>\u003C/h2>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>\u003Cstrong>Underinvesting in data quality.\u003C/strong> AI models are only as good as the data they learn from. As noted in a \u003Ca href=\"https://doi.org/10.3389/fnut.2025.1553942\">comprehensive review on AI in food safety\u003C/a>, poor data governance is one of the leading barriers to effective AI adoption across food manufacturing.\u003C/li>\n\n\n\n\u003Cli>\u003Cstrong>Treating AI as a black box.\u003C/strong> Scientists need to understand the logic behind AI recommendations to trust and act on them. Look for platforms that explain their outputs.\u003C/li>\n\n\n\n\u003Cli>\u003Cstrong>Skipping change management.\u003C/strong> Buy-in from scientists, quality teams and leadership is essential. Without it, even the best platform gets underused.\u003C/li>\n\n\n\n\u003Cli>\u003Cstrong>Expecting instant results.\u003C/strong> AI tools improve with data and use. A \u003Ca href=\"https://www.sciencedirect.com/science/article/pii/S0924224424005314\">decade review of AI applications in food safety\u003C/a> notes that the most successful implementations build progressively on high-quality, well-structured datasets.\u003C/li>\n\u003C/ul>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"the-road-ahead-for-food-and-beverage-formulation-5\">\u003Cstrong>The Road Ahead for Food and Beverage Formulation\u003C/strong>\u003C/h2>\n\n\n\n\u003Cp>The adoption of AI in food and beverage formulation is still early, but the direction is clear. Teams that build AI-enabled workflows now will have shorter development cycles, more resilient \u003Ca href=\"https://blog.3ds.com/brands/delmia/driving-a-responsive-sustainable-and-efficient-food-supply-chain/\" type=\"link\" id=\"https://blog.3ds.com/brands/delmia/driving-a-responsive-sustainable-and-efficient-food-supply-chain/\">supply chain strategies\u003C/a> and better-positioned products. Research in \u003Ca href=\"https://doi.org/10.1007/s44163-025-00296-8\">\u003Cem>Discover Artificial Intelligence\u003C/em>\u003C/a> points to food and beverage as one of the sectors where AI-driven innovation will deliver the most measurable gains over the next decade.\u003C/p>\n\n\n\n\u003Cp>If your formulation team is ready to move beyond spreadsheets and disconnected data systems, exploring a connected, AI-powered formulation platform is a logical next step. BIOVIA is one place worth starting that conversation.\u003C/p>\n\n\n\n\u003Cp>\u003Cem>Interested in how Dassault Systèmes supports food and beverage formulation teams? \u003C/em>\u003C/p>\n\n\n\n\u003Cp>\u003Cem>Visit the \u003Ca href=\"https://www.3ds.com/industries/consumer-packaged-goods-retail/product-formulation\">Dassault Systèmes website\u003C/a> to learn more about their AI-powered formulation capabilities.\u003C/em>\u003C/p>\n\n\n\n\u003Cp>\u003C/p>\n","2026-06-03T17:45:07",[],{"node":51,"__typename":62},{"nicename":52,"description":53,"slug":52,"name":54,"firstName":55,"lastName":56,"avatar":57,"__typename":61},"briancarboni","Brian Carboni is the Global Marketing Director for the CPG-Retail Industry at Dassault Systèmes.","Brian Carboni","Brian","Carboni",{"default":58,"url":59,"__typename":60},"mm","https://blog-assets.3ds.com/uploads/2022/03/brian-96x96.jpg","Avatar","User","NodeWithAuthorToUserConnectionEdge",{"nodes":64,"__typename":78},[65,70,74],{"id":66,"name":67,"uri":68,"__typename":69},"dGVybTo4NjEx","Science","/topics/science/","Taxonomy_topic",{"id":71,"name":72,"uri":73,"__typename":69},"dGVybTo4MDM0","Sustainability","/topics/sustainability/",{"id":75,"name":76,"uri":77,"__typename":69},"dGVybTo4ODAz","Thought Leadership","/topics/thought-leadership/","PostToTaxonomy_topicConnection",{"nodes":80,"__typename":93},[81,86,90],{"id":82,"name":83,"uri":84,"__typename":85},"dGVybTo4ODMy","AI","/tags/ai/","Taxonomy_tag",{"id":87,"name":88,"uri":89,"__typename":85},"dGVybTo5MTA2","Digital Transformation","/tags/digital-transformation/",{"id":91,"name":72,"uri":92,"__typename":85},"dGVybTo4ODgz","/tags/sustainability/","PostToTaxonomy_tagConnection",{"nodes":95,"__typename":96},[],"PostToTaxonomy_brandConnection",{"edges":98,"nodes":122,"__typename":124},[99],{"isPrimary":100,"node":101,"__typename":121},true,{"slug":102,"name":103,"industries":104,"__typename":120},"consumer-packaged-goods-retail","Consumer Packaged Goods & Retail",{"nodes":105,"__typename":119},[106],{"translations":107,"__typename":118},[108,112,115],{"post_title":109,"locale":110,"__typename":111},"Produits de grande consommation et distribution","fr_FR","Translation",{"post_title":113,"locale":114,"__typename":111},"消費財","ja",{"post_title":116,"locale":117,"__typename":111},"소비재","ko_KR","Industry","Taxonomy_industryToIndustryConnection","Taxonomy_industry","PostToTaxonomy_industryConnectionEdge",[123],{"name":103,"slug":102,"__typename":120},"PostToTaxonomy_industryConnection",{"nodes":126,"__typename":134},[127,130,132],{"name":128,"__typename":129},"formulation","Taxonomy_keyword",{"name":131,"__typename":129},"science",{"name":133,"__typename":129},"simulation","PostToTaxonomy_keywordConnection",{"title":136,"metaDesc":137,"opengraphAuthor":138,"opengraphDescription":137,"opengraphTitle":26,"opengraphUrl":139,"opengraphSiteName":140,"opengraphPublishedTime":141,"opengraphModifiedTime":142,"twitterTitle":138,"twitterDescription":138,"readingTime":143,"metaRobotsNoindex":144,"__typename":145},"How AI Is Cutting R&D Time and Costs in Food Formulation - Dassault Systèmes blog","R&D must now play a key role in next-generation formulation, transforming how innovation is conceived, designed and delivered.","","https://blog-frontoffice-contrib-prd.itvpc.3ds.com/industries/consumer-packaged-goods-retail/how-ai-is-cutting-rd-time-and-costs-in-food-formulation/","Dassault Systèmes blog","2026-06-03T17:45:07+00:00","2026-06-03T17:46:26+00:00",6,"index","PostTypeSEO","Post","RootQueryToPostConnection",{},{},1780518305195]