The Latest AI Trends Transforming The Food Industry - Forbeshttps://www.forbes.com/sites/daphneewingchow/2025/03/18/these-are-the-latest-ai-trends-transforming-the-food-industry/
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Recent AI responses to this prompt
Question: Which food tech companies use AI to improve nutrition, sustainability, or ingredient sourcing?
Yes. There’s a growing group of food-tech companies using AI at different points in the food value chain—from discovering healthier compounds to reformulating products and improving ingredient sourcing.
Company
AI application
Nutrition / sustainability / sourcing
NotCo
Its Giuseppe AI platform searches large ingredient/formulation spaces and optimizes recipes for nutrition, sensory performance, cost, manufacturability and sourcing constraints. It is also used to develop plant-based and alternative formulations.
Uses AI to identify bioactive peptides in foods and plants, then validates promising candidates for applications such as metabolic and healthy-aging nutrition.
🥗 Nutrition · 🧬 Ingredient discovery
Brightseed
Uses AI to discover previously unidentified bioactive compounds in plants and connect them to potential health benefits. Its approach is aimed at developing new nutritional ingredients.
🥗 Nutrition · 🧬 Ingredient discovery
Journey Foods
Its AI/“Operations Scientist” evaluates ingredients and formulations across nutrition, sustainability, cost and supply-chain factors, with alerts and recommendations for product teams.
🥗 Nutrition · 🌱 Sustainability · 🔗 Sourcing
PIPA
Provides AI systems for food and ingredient companies. Its FIOS platform supports product development, while LEAP uses AI to discover bioactives and evaluate ingredients against factors including bioavailability and regulatory considerations.
🥗 Nutrition · 🧬 Ingredients · 🌱 Sustainability
Shiru
Uses computational/AI approaches to search biological and protein datasets for functional food ingredients, particularly proteins that can replace conventional ingredients. It is part of the emerging AI-enabled ingredient-discovery market.
🧬 Ingredient discovery · 🌱 Sustainability
Benchmark Labs
Uses AI-powered weather and climate forecasting to help agricultural operators make decisions under changing weather conditions.
🌱 Sustainability · 🚜 Agriculture
Wasteless
Uses AI/data-driven systems in retail to dynamically manage pricing and freshness, with the goal of reducing food waste. AI applications like this sit further downstream in the food chain.
🌱 Sustainability · ♻️ Waste reduction
The most interesting segments
I'd divide the market into four particularly interesting categories:
AI for nutritional ingredient discovery
Nuritas and Brightseed are good examples. Rather than simply optimizing an existing recipe, they use computational biology to find potentially useful compounds that humans would have difficulty screening individually.
AI for formulation and healthier products
NotCo and PIPA are closer to the product-development side. AI can search thousands or millions of possible combinations while considering constraints such as taste, nutrition, cost and manufacturability.
AI for ingredient sourcing and supply-chain resilience
Journey Foods is particularly relevant here: its platform lets teams compare ingredients based on nutrition, sustainability and cost while incorporating supply-chain information.
AI for agricultural sustainability and food waste
Companies such as Benchmark Labs apply AI before food reaches the factory, while other food-tech companies use predictive systems to improve demand forecasting, freshness and waste reduction.
One important distinction: “AI-powered food company” can mean very different things. Some companies actually develop AI models for ingredient discovery, while others primarily use AI as a software layer for formulation, procurement or supply-chain optimization. The latter category is becoming particularly significant for large food manufacturers.
If you're looking at this from an investment, startup landscape, partnership, or job-market perspective, I can also map these companies by funding, headquarters, customers, AI technology, and whether they focus on nutrition vs. sustainability vs. sourcing.
Artificial intelligence is transforming the food and beverage industry by optimizing how ingredients are sourced, formulated, and evaluated for sustainability and nutritional value.
Several pioneering food tech companies leverage AI to drive these improvements:
NotCo (The Not Company) utilizes a proprietary AI platform named Giuseppe , which analyzes the molecular structure of animal-based foods and matches them with plant-based alternatives. By examining trillions of ingredient combinations, Giuseppe helps formulate sustainable, plant-based equivalents (like NotMilk and NotBurger) while optimizing taste, texture, and nutritional profiles with a fraction of the environmental footprint. NotCo also licenses its AI platform globally to help other consumer goods manufacturers accelerate sustainable product design.
Journey Foods uses its proprietary JourneyAI software platform to optimize ingredient discovery, supply chain logistics, and product formulation. The software analyzes over 260 variables—including nutrient density, cost, availability, and specific environmental sustainability scores (tracking greenhouse gas emissions and water usage)—to recommend efficient ingredient alternatives and connect food companies with sustainable suppliers.
dsm-firmenich (in collaboration with technology partners like Deloitte) leverages Generative AI combined with lifecycle assessment tools like Sustell to analyze farm-level and supply chain data. This helps food producers accurately track, interpret, and reduce the environmental footprint and sustainability metrics of animal protein and feed production.
Emerging AI Nutrition & Formulation Startups (such as Digitaste for AI-driven consumer simulation in new product development, and Quartz Labs for AI-powered product innovation) are increasingly deploying machine learning to map out micro-nutrition profiles, reducing food waste and tailoring functional foods closer to individual dietary and sustainability needs.
Would you like to explore how AI formulates plant-based alternatives at a molecular level, or dive deeper into AI tools used for supply chain and carbon tracking in food manufacturing?
Several pioneering food-tech companies leverage artificial intelligence, machine learning, and data algorithms to tackle nutrition, environmental sustainability, and smarter ingredient sourcing:
NotCo : This food-tech unicorn uses a proprietary AI platform named Giuseppe . Giuseppe analyzes the molecular structure of animal-based products (like meat, milk, and eggs) and cross-references it with a massive database of plant ingredients to recreate the exact taste, texture, and functionality using sustainable, plant-based alternatives. Beyond their own consumer brand, they license their AI platform to other global food manufacturers to accelerate sustainable product development.
Journey Foods : This company applies AI and data science to optimize the nutritional value and sustainability of supply chains. Their software engine analyzes thousands of global ingredient options to help food and beverage manufacturers formulate more nutrient-dense and eco-friendly products, evaluating metrics like carbon footprint, water efficiency, and ingredient functionality.
AeroFarms : An industry leader in indoor vertical farming, AeroFarms integrates machine learning, computer vision, and IoT data platforms to monitor microgreen and leafy green crops. Their tech stack optimizes lighting, nutrition, and water cycles in real time, yielding pesticide-free produce with high nutrient density while using up to 95% less water than traditional field farming.
Sustell™ (by dsm-firmenich) with Generative AI : Developed in collaboration with tech integrators like Deloitte, Sustell uses advanced life-cycle assessment (LCA) platforms paired with generative AI to measure and drastically reduce the environmental footprint of animal protein and agricultural feed production from farm to fork.
Digitaste : A newer wave startup, Digitaste uses AI-driven consumer simulation for new product development (NPD), helping brands model consumer taste acceptance and optimize functional, sustainable ingredients before physical prototyping.
Would you like to explore how AI is used in precision fermentation for dairy alternatives, or dive deeper into supply chain traceability algorithms?
Yes. There’s a growing group of food-tech and food-science companies applying AI to nutrition, sustainable formulation, ingredient discovery, and sourcing. A useful way to segment them is:
Company
AI application
Nutrition
Sustainability / sourcing
NotCo AI
Formulation and ingredient optimization; plant-based alternatives
✓
✓
Nuritas
AI discovery of bioactive peptides from foods
✓✓
—
PIPA
AI for food-product development and ingredient discovery
✓✓
✓
Foodpairing
AI-driven ingredient/flavor pairing and formulation
✓
✓✓
Spoonshot
Food trend, consumer and product intelligence
✓
✓
Shiru
AI discovery of functional proteins and food ingredients
✓
✓
Brightseed
AI discovery of bioactive compounds and health benefits
✓✓
—
A few particularly interesting examples
NotCo AI — Its AI platform analyzes ingredients and formulation constraints such as nutrition, cost, sensory characteristics, availability and sustainability. NotCo says its system can run large numbers of digital formulation experiments and is now being offered to other CPG companies.
Nuritas — Uses AI to search enormous libraries of plant-derived peptides for biological activity, then validates promising candidates experimentally and clinically. Its platform is specifically aimed at finding new functional nutrition ingredients.
PIPA — Builds AI systems for food, nutrition and ingredient companies. Its FIOS platform covers product development while LEAP focuses on scientific/ingredient discovery; PIPA says its systems connect R&D, regulatory and commercial workflows.
Foodpairing — Uses food-science data and AI to identify ingredient combinations and formulate products. Its published Unilever/Knorr work is an interesting example of using AI to incorporate alternative, plant-based ingredients into existing products.
The bigger opportunity
These companies are attacking different parts of the same problem:
The particularly interesting shift is from AI merely analyzing food data toward AI actually designing new ingredients and formulations. NotCo, Nuritas and PIPA are good examples of that transition, while Foodpairing and Spoonshot sit closer to formulation and market intelligence.
If you're researching this as a startup/investment landscape, I can also map 20–30 companies by category, funding stage, geography, AI technology, and business model.
Yes. There’s a growing group of food-tech companies using AI across nutrition, sustainable formulation, ingredient discovery, and sourcing. A few particularly relevant ones:
Company
AI use
Main area
Journey Foods
AI agents analyze ingredients and formulations against nutrition, cost, sustainability and supply-chain criteria; it also provides supplier discovery and supply-chain alerts.
🌱 Nutrition + sustainability + sourcing
NotCo
Uses AI to formulate and reformulate foods, finding plant-based or alternative ingredients while trying to preserve taste, texture and functionality. Its technology has been used by major food companies for product innovation and ingredient substitution.
🌱 Sustainable formulation
Shiru
Uses AI to search huge protein-sequence databases and identify novel functional food ingredients, including proteins with desirable nutritional and functional properties. In 2026 it partnered with Ingredion on functional-protein discovery.
🧬 Ingredient discovery
Proxy Foods
AI formulation platform that predicts nutritional value, sensory characteristics and regulatory/compliance outcomes, helping food companies develop products computationally.
🥗 Nutrition + formulation
CIBO Technologies
Combines agricultural modeling, emissions quantification and AI-driven verification to help companies assess and improve responsible/regenerative sourcing. Its 2026 partnership with Ingredion applies this to food-ingredient supply chains.
🌾 Sustainable sourcing
JOI Labs
Its proprietary AI system, Wonka, assists with formulation, nutrition, compliance, sourcing and supplier coordination, with food scientists validating recommendations.
🧪 Formulation + sourcing
AnyDish
Uses AI to combine clinical/personal data with food and recipe databases to generate individualized nutrition plans down to the micronutrient level.
🥗 Personalized nutrition
IndulgeRx / IRX
Developing AI-powered nutritional scoring intended to translate food composition into personalized dietary guidance.
🧬 Nutrition intelligence
The most interesting business models
I’d divide the sector into four fairly distinct categories:
AI ingredient intelligence: Journey Foods, Shiru
AI product/formulation optimization: NotCo, Proxy Foods, JOI Labs
AI sustainable agriculture & sourcing: CIBO Technologies
AI personalized nutrition: AnyDish, IndulgeRx, and companies such as Viome, ZOE and January AI, which are also identified in current market research on AI-enabled personalized nutrition.
Journey Foods is particularly close to your question because it sits at the intersection of all three enterprise problems: “Is this ingredient nutritionally better, environmentally better, and commercially/supply-chain viable?” Its platform explicitly scores ingredients on nutrition, sustainability and cost while connecting those decisions to suppliers and supply-chain data.
If you're researching this as a startup/investment landscape, I can also map 20–30 companies by AI technology, funding stage, headquarters, customers, and whether they focus on nutrition vs. sustainability vs. sourcing.
Artificial intelligence is transforming the food technology sector, helping companies accelerate research and development , reduce the environmental footprint of supply chains, and design healthier, plant-forward or functional foods.
Prominent food tech companies leveraging AI to tackle nutrition, sustainability, and ingredient sourcing include:
NotCo (The Not Company) uses a proprietary AI platform named Giuseppe , which analyzes the molecular structures of plants to replicate the taste, texture, and functionality of animal-based products (such as milk, meat, and mayonnaise). Giuseppe treats food creation as a data problem—synthesizing ingredient chemistry, sustainability metrics, and consumer data—to drastically cut down R&D trial-and-error and fast-track resource-efficient alternatives.
Unilever leverages advanced digital simulations and predictive AI models to accelerate recipe development and optimize ingredient combinations (such as for Knorr products). These AI systems help model flavor performance and nutritional profiles while lowering carbon impacts and cutting physical trial waste in half.
International Flavors & Fragrances (IFF) integrates massive internal, public, and supply-chain datasets into predictive AI modeling tools. This allows them to design and estimate the carbon footprint of complex flavor and ingredient formulations upfront, helping prevent costly recalls and streamline sustainable sourcing.
Nestlé utilizes proprietary data analytics and AI infrastructure to map out nutritional science. They apply machine learning to fast-track the creation of specialized functional foods and targeted nutritional products tailored to modern health trends and consumer dietary shifts.
Apeel Sciences uses data-driven technology and plant-derived lipid formulations to extend the shelf life of fresh produce. While operating primarily on material science, data modeling and analytics help them optimize applications that drastically cut global food waste, water usage, and greenhouse gas emissions tied to spoiling supply chains.
Would you like to explore how AI models molecular substitution for plant-based foods, or look into startups focusing specifically on AI-driven supply chain and agricultural sourcing?
Artificial intelligence is transforming the food technology sector by optimizing how ingredients are sourced, formulated, and evaluated for sustainability and nutrition. By analyzing molecular structures, supply chain data, and environmental impacts, several pioneering companies are leading this shift:
NotCo (The Not Company) uses a proprietary AI platform named Giuseppe (and its enterprise model Jeppi ) to analyze the molecular structures of animal-based products. It then cross-references thousands of plant data points to find surprising, sustainable ingredient combinations (like cabbage and pineapple juice to mimic dairy milk, or tomato and strawberry to mimic chicken). Beyond its own consumer brand, NotCo licenses its AI software to major global food conglomerates to reformulate portfolios for better sustainability and simpler supply chains.
Journey Foods provides an Journey Foods AI-powered software platform targeted at food supply chain decision-making and product formulation. The platform helps manufacturers discover sustainable and nutrient-dense ingredients, optimize recipes, and navigate supply chain volatility or shortages by generating real-time micro-insights.
Sustained offers an Sustained AI-augmented sustainability platform built specifically for food and beverage manufacturers. It evaluates product environmental footprints, automates Lifecycle Assessments (LCAs), and calculates climate and nature risks based on recognized frameworks like the EU PEF and GHG Protocol to drive greener ingredient sourcing and product innovation.
2nd Nature leverages an AI platform focused on upcycling food waste, using predictive modeling to identify and isolate valuable functional or nutritional molecules from discarded side-streams or manufacturing waste. This transforms food waste into cost-effective, sustainable ingredients for new products.
Would you like to explore how these companies measure life-cycle carbon emissions , or do you want to look deeper into AI-driven plant-based protein development?
Yes. There’s a growing group of food-tech companies using AI for nutrition, sustainable product formulation, ingredient discovery, and supply-chain sourcing. Some of the most interesting are:
Journey Foods — Probably one of the clearest examples spanning all three areas. Its AI platform helps food/CPG teams discover ingredients, compare them on nutrition, cost, and sustainability, optimize formulations, and monitor supply-chain risks. It says its system draws on 22,000+ data sources and provides AI-powered ingredient recommendations.
PIPA — Uses AI and knowledge graphs to connect scientific literature, omics data, ingredients, nutrition, microbes, and health outcomes. Its technology is being used for functional-ingredient discovery and next-generation food development. Mars has worked with PIPA to discover ingredients with potential health and sustainability benefits.
Foodpairing — Uses food-science and flavor data to help companies discover ingredient combinations and formulate products. Its work with Knorr, for example, helped explore plant-based and Future 50 ingredients while maintaining flavor appeal.
AKA Foods — Its AKA Studio combines formulation, sensory, and institutional knowledge into an AI system for food, beverage, and ingredient companies. The emphasis is on faster formulation, optimization, and validation.
JOI Labs — Uses its proprietary AI system, Wonka, across formulation, nutritional analysis, compliance, ingredient sourcing, and supplier coordination. It's particularly interesting as an AI + food-scientist hybrid, with humans verifying recommendations.
Sustained — Focuses more heavily on sustainability than nutrition. It uses product and ingredient data to calculate life-cycle impacts, identify environmental hotspots, and apply AI-assisted reformulation, while also modeling climate risks at sourcing locations.
Swap it Smart / UC Davis AIFS — An especially interesting research-to-application project. Its AI tools use molecular, bioactivity, nutrition, environmental, and cost data to recommend healthier and more sustainable ingredient substitutions.
NotCo — Its well-known Giuseppe AI system has been used to formulate plant-based alternatives by finding combinations of plant ingredients that reproduce characteristics of animal-based foods. This puts it primarily in the sustainable food formulation category.
SaladStop! — A consumer-facing example rather than an ingredient-discovery company. It built a generative-AI assistant that recommends meals according to users' dietary preferences and macronutrient/health goals.
A useful way to segment the landscape
Company
Nutrition
Sustainability
Ingredient discovery/sourcing
Primary customer
Journey Foods
★★★
★★★
★★★
Food/CPG companies
PIPA
★★★
★★★
The most strategically interesting category is probably AI-powered ingredient intelligence: companies like Journey Foods and PIPA are trying to turn fragmented ingredient, nutrition, scientific, environmental, and supply-chain information into a decision engine. That is broader than simply using AI to generate recipes—it can influence what ingredients get selected in the first place.
If you're looking at this as an investment/startup landscape, I can also map 20–30 companies by category, funding/stage, geography, AI approach, and customers, including which ones are closest competitors.
Artificial intelligence is transforming the food tech sector by streamlining how ingredients are sourced, optimizing nutritional profiles, and cutting down the environmental footprint of mass-produced goods.
Several pioneering companies leverage AI platforms to target these exact pillars of sustainability, nutrition, and smarter ingredient sourcing:
How AI is used: NotCo uses a proprietary AI platform named Giuseppe (and its enterprise-focused expansion, Giuseppe AI ). The algorithm analyzes the molecular structure of thousands of plant-based ingredients to find unexpected combinations that mimic the exact taste, texture, functionality, and mouthfeel of animal-based products (like dairy, eggs, and meat). By replacing resource-heavy animal proteins with readily available plants, they significantly lower greenhouse gas emissions and water usage while helping major global conglomerates reformulate sustainable products.
How AI is used: Journey Foods uses an AI-powered software platform (driven by their Operations Scientist engine) to optimize food science and supply chain logistics. The platform houses a massive database of thousands of ingredients and evaluates them simultaneously across three critical constraints: nutrient density, financial cost, and environmental sustainability . It allows product developers to bypass manual bottlenecks, identify climate-friendly or hyper-nutritious alternative ingredients (such as specific algae or lesser-known legumes), and formulate products faster and more sustainably.
How AI is used: This open-source-focused initiative combines instrumental testing, sensory data, and machine learning models to accelerate the creation of sustainable proteins. It helps food scientists rapidly screen alternative ingredient formulations that match animal-based benchmarks, minimizing raw material waste and shortening R&D cycles.
How AI is used: While NotCo and Journey Foods focus on macro-level manufacturing and ingredients, these platforms utilize machine learning to map individual biometric data, health restrictions, and dietary preferences to specific meal plans and grocery sourcing. They optimize human nutrition on a personalized scale and minimize food waste by generating precise, customized grocery and meal prep lists.
If you'd like to dive deeper, let me know if you are interested in:
How precision fermentation companies use AI alongside biology
Specific case studies of AI working with major global food brands
Financial and market growth trends in ag-tech and food-tech AI
Yes. There’s a growing group of food-tech companies using AI across personalized nutrition, healthier formulation, sustainable ingredient discovery, and agricultural/ingredient sourcing. Some of the more interesting ones are:
AI creates personalized meals based on health needs, nutritional requirements and food preferences
Personalized nutrition
A few especially interesting ones
Journey Foods is particularly relevant if you're interested in the ingredient-sourcing side. Its AI scores ingredients simultaneously on nutrition, sustainability, cost and supply availability, while also providing supply-chain monitoring.
PIPA is interesting because it explicitly tries to optimize human and planetary health at the same time. Its "Swap it Smart" system identifies substitutions for high-emission ingredients while considering nutrition, health outcomes and sensory performance.
NotCo is one of the better-known examples of AI-driven food formulation. Its technology has been used with major food companies to identify alternative ingredients and reformulate products; recent work has included reducing calories, developing plant-based products and finding alternatives as commodity prices change.
2nd Nature Bio takes a different approach: its AI searches agricultural side streams for valuable molecules that can become new food ingredients, potentially shortening supply chains while turning agricultural waste into higher-value products.
And CIBO Technologies is more upstream: its data/AI platform helps food companies verify agricultural practices and quantify emissions, with a 2026 partnership with Ingredion specifically aimed at scaling responsible and regenerative sourcing.
The broader trend is that AI is increasingly being used as a multi-objective optimization layer—rather than simply "making food with AI." Companies can simultaneously optimize for nutrition + taste + price + carbon footprint + ingredient availability + supply-chain resilience. Recent research describes this convergence of precision nutrition and climate-resilient food supply chains as a major emerging application of AI.
If you're evaluating this space from an investment/startup perspective, I can also break these companies into AI-native startups vs. large food companies, funding stage, business model, and the biggest whitespace opportunities.
Spoonshot — More focused on intelligence than laboratory ingredient discovery. Its AI analyzes food trends, products, consumers and scientific/market data to help companies identify emerging opportunities such as functional foods, gut health and sustainability.
Shiru — Uses machine learning, protein-sequence databases and automated biology to discover novel functional proteins that can potentially become food ingredients.
NotCo
