AI in Food Innovation Market to Surge at a CAGR of 37.3%,

Ottawa, Dec. 12, 2025 (GLOBE NEWSWIRE) -- The global AI in food innovation market size stood at USD 1.67 billion in 2024 and is predicted to increase from USD 2.29 billion in 2025 to reach around USD 39.76 billion by 2034, according to a report published by Towards FnB, a sister firm of Precedence Research. Driven by advancements in AI, machine learning, and predictive analytics, the market is accelerating as these technologies optimize R&D, enhance product quality, and cater to growing consumer demand for personalized food options.

The market's growth is fueled by rising demand for customized food products and automation. AI is enabling food companies to innovate in ingredient formulation, streamline production, and improve food safety, ensuring efficiency while meeting changing consumer preferences.

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Key Highlights of AI in Food Innovation Market

By region, North America held the largest share of the AI-driven food innovation market in 2024.
By region, Europe is expected to experience growth in the AI food innovation market in the foreseeable future.
By technology/platform, the machine learning and predictive analytics segment dominated the market in 2024.
By technology/platform, the AI-powered recipe and flavor development tools segment is anticipated to grow in the coming years.
By application, the new product development and formulation optimization segment captured the largest share in 2024.
By application, the nutritional and health-focused product innovation segment is projected to grow in the near term.
By service type, the AI software and platform solutions segment led the market in 2024.
By service type, integration with IoT and smart manufacturing systems is expected to see growth in the forecast period.
By end user, food and beverage manufacturers were the leading segment in 2024.
By end user, startups and SMEs in the food innovation sector are likely to grow in the coming years.
By deployment mode, cloud-based solutions dominated the market in 2024.
By deployment mode, on-premises solutions are expected to experience growth in the foreseeable future.
By distribution channel, direct-to-enterprise solutions led the AI in food innovation market in 2024.
By distribution channel, B2B partnerships and collaborations are anticipated to grow in the near term.
By innovation focus, health and functional food innovations were the market leaders in 2024.
By innovation focus, sustainability-focused product innovation is expected to see growth over the forecast period.

Technological Advancements Aiding the Growth of AI in Food Innovation Industry

The AI in the food innovation market has been growing recently due to factors such as automation, food safety, and personalization. Technological advancements such as AI, ML, predictive analytics, and data collection help understand consumer preferences, which in turn inform trend analysis and future predictions. Hence, it enables the food and beverages industries to manufacture food ingredients and recipes, further fueling the market's growth. AI also helps with customization, tailored diet plans, and nutritional development, further propelling the market's growth.

New Trends of AI in Food Innovation Market

Use of AI for personalized and tailored diet plans for enhanced nutrition is one of the major factors for the growth of the market.
Higher demand for automation and robotics, which helps to enhance food safety and quality, further helps to enhance the market’s growth.
Technologically advanced methods also help in maintaining cost-efficiency and lower food wastage, further propelling the growth of the market.

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Recent Developments in AI in Food Innovation Market

In December 2025, AKA Foods LTD announced the completion of a 17.2 million dollar seed funding led by renowned AI experts. The funding marked the official launch of AKA Studio, a secure AI system and proprietary platform.
In September 2025, Starday, an AI-driven product innovation platform, announced the launch of Starday Innovation, a strategic partnership offering for food and beverage teams. The new platform brings together AI and data-powered R&D.

Product Survey of the AI in Food Innovation Market

Product Category	Description or Function	AI Technologies Used	Key Applications or End Use Segments	Representative Products or Providers
AI-Driven Food Product Development Platforms	Software platforms that generate, optimize, or predict new food formulations.	Generative AI, machine learning formulation models, and sensory prediction algorithms	R&D teams, food formulators, ingredient companies	NotCo AI platform, IBM Chef Watson-style systems, R&D formulation suites
AI-Based Flavor and Sensory Design Tools	Systems that model flavor interactions, predict sensory outcomes, and support ingredient substitutions.	Neural networks trained on flavor chemistry, taste prediction models	Flavor houses, beverage R&D, snack development	Givaudan AI flavor engines, Firmenich AI sensory modelling
AI-Enabled Nutrition Optimization Platforms	Tools that redesign products for improved nutrition profiles while meeting taste targets.	Constraint-based optimization, nutrient algorithms	Healthy reformulation, sugar or salt reduction	PepsiCo and Nestlé reformulation AI tools, NutriScore modelling AI
AI Powered Food Safety and Quality Inspection Systems	Automated systems for detecting defects, contamination, and mislabeling.	Computer vision, deep learning classification	Meat processing, produce sorting, dairy QC	TOMRA AI sorters, Sight Machine QC platforms
AI in Shelf Life Prediction and Freshness Modelling	Predictive tools estimating product spoilage and shelf life under varying conditions.	Time series models, environmental prediction algorithms	Fresh produce, dairy, and ready meals	Apeel shelf life modelling tools, predictive modelling platforms
AI Based Food Waste Reduction Tools	Platforms that analyze demand patterns to minimize waste in retail and kitchens.	Predictive analytics, demand forecasting	Supermarkets, restaurants, foodservice operations	Winnow AI, Too Good To Go AI optimisation
AI Driven Precision Fermentation and Bioprocess Control	Real time AI systems optimizing fermentation for alternative proteins and novel ingredients.	Bioprocess ML optimisation, sensor based control	Fermentation companies, biotech foods, dairy alternatives	Perfect Day fermentation control AI, Ginkgo Bioworks strain optimisation
AI-Powered Robotics in Food Manufacturing	Robots guided by AI vision and motion planning for cutting, sorting, cooking, picking.	Computer vision, motion AI, reinforcement learning	Ready meals factories, bakeries, meat plants	Miso Robotics Flippy, GreyOrange automated picking
AI Enhanced Supply Chain Optimization Systems	Tools that manage inventory, logistics, and demand to reduce shortages and overproduction.	Predictive algorithms, neural networks for demand forecasting	Retailers, distributors, food manufacturers	Blue Yonder, SAP AI Supply Chain modules
AI for Personalized Food and Nutrition	Engines generating personalized meal plans, grocery suggestions, and custom product recommendations.	Recommendation systems, natural language AI, biomarker based analytics	D2C nutrition, fitness platforms, packaged food personalization	Zoe AI nutrition, InsideTracker food recommendation tools
AI in Alternative Protein and Plant Based Product Development	R&D engines identifying plant proteins and designing textures that mimic meat, dairy, or eggs.	Generative AI for texture mapping, protein interaction models	Plant based brands, hybrid protein developers	NotCo Giuseppe AI, Climax Foods AI protein modelling
AI Based Sensory Analysis and Digital Tasting	Replacing human panels with predictive sensory models to shorten product testing cycles.	Sensory ML models, pattern recognition	Beverage makers, snack companies, flavour producers	Companies using AI digital tongue and nose systems
AI Predictive Maintenance for Food Factories	Predicts equipment failure to avoid downtime in processing lines.	Machine learning anomaly detection	Food manufacturers, packaging plants	Augury, Siemens MindSphere
AI Driven Menu and Recipe Optimization for Foodservice	Tools that optimize menus based on cost, nutrition, and customer preference trends.	NLP recipe modelling, predictive analytics	Restaurants, cloud kitchens, institutional foodservice	Ingest AI, menu optimisation engines
AI Powered Packaging and Design Optimisation	AI tools that simulate packaging durability, material efficiency, and consumer appeal.	Generative design, predictive modelling	Packaging companies, CPG brands	Esko AI tools, packaging simulation platforms
AI Systems for Traceability and Authentication	Tools that ensure product authenticity across the supply chain.	Blockchain linked AI verification, image based authenticity checks	Seafood, spices, premium foods	IBM Food Trust integration with AI, digital traceability hubs
AI Enhanced Consumer Insights and Trend Analytics	Systems scanning consumer data to identify emerging food trends.	LLMs, natural language processing, social analytics	Marketing teams, R&D insights, brand teams	Tastewise AI, Spoonshot, Black Swan Data

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AI in Food Innovation Market Dynamics

What are the Growth Drivers of AI in Food Innovation Market?

Automation, food robotics, innovation, food safety, and quality control are major factors driving market growth. The market also observes growth as technologically advanced methods help understand data analytics and, when paired with predictive analytics, suggest novel, safe food ingredients and recipe combinations, further fueling the market's growth.

Challenge

Weak Data Quality and Integration are hampering the Market’s Growth

AI and data analytics help gather large amounts of data reflecting consumers’ current choices. If this data is not managed properly, it may lead to inappropriate solutions and future predictions, which could hamper the market’s growth. The businesses may not find the right solutions, which may hamper their food and beverage qualities in the future, along with high food wastage and poor operational management. Hence, these factors collectively hamper the market's growth.

Opportunity

Food Innovation and Product Development are helpful for the market’s Growth

AI, using data analysis and predictive analytics together, helps frame consumer demands and needs for the future. Hence, it helps in manufacturing and in making changes to food and beverage options, which are beneficial for the market’s growth in the foreseeable period. Food innovation is also aided by rapid urbanization, rising disposable income, and globalization, allowing consumers to experience the flavors and cultures of various regions.

AI in Food Innovation Market Regional Analysis

North America Dominated the AI in Food Innovation Market in 2024

North America led the AI in food innovation market in 2024 due to higher demand for automation and technologically advanced procedures, which are driving market growth. The availability of technologically advanced procedures in the region helps enhance food safety and quality, further fueling the market's growth. Product innovation and lower wastage are other major factors driving the market's growth in the foreseeable period. The US has a major role in the region's market growth, as AI helps enhance food safety and quality, as well as supply-chain management.

Europe is Observed to Grow in the Foreseen Period

Europe is expected to grow over the forecast period as the region focuses on key factors such as farm-level optimization, new product development, personalized consumer experiences, and major investments from startups, all of which are supportive of market growth. Product innovation, food safety and quality, and lower wastage are other major factors driving the market's growth in the foreseeable period. Germany has a major contribution to the market's growth, as it supports a smooth supply chain, uses technologically advanced methods, and has a higher demand for automation.

Asia Pacific is observed to have a Notable Growth in the Foreseen Period

Asia Pacific is observed to be experiencing notable growth due to factors such as urbanization, rising disposable income, technological development, and increased AI adoption. Such factors enhance the safety and quality of food and beverage options, which are beneficial for the market’s growth. AI helps understand consumers’ future preferences and suggest ideal remedies, further fueling market growth. India has made a major contribution to the market's growth due to the country's high use of AI, which helps with seamless supply chain operations, enhances food safety and quality, and supports the market’s growth.

AI in Food Innovation Market Report Scope

Report Attribute	Key Statistics
Base Year	2024
Forecast Period	2025 to 2034
Growth Rate from 2025 to 2034	CAGR of 37.3%
Market Size in 2025	USD 2.29 Billion
Market Size in 2026	USD 3.15 Billion
Market Size by 2034	USD 39.76 Billion
Dominated Region	North America
Fastest Growing Region	Europe
Regions Covered	North America, Europe, Asia-Pacific, Latin America and Middle East & Africa

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AI in Food Innovation Market Segmental Analysis

Technology Analysis

The machine learning and predictive analytics segment led the AI in food innovation market in 2024 due to its ability to analyze data and provide analyses that help food manufacturing businesses understand future consumer demand. Such actions help fuel the market's growth. It also helps to understand the future trends and make the required innovations. It also helps to streamline supply chain operations.

The AI-powered recipe and flavor development tools segment is expected to grow in the foreseen period due to high demand from food manufacturing businesses to understand consumer demand in depth and to save the time and resources required for R&D to drive market growth. The segment focuses on understanding and analyzing consumer data and developing novel, safe, and unique flavor profiles, which is helpful for market growth.

Application Analysis

The new product development and formulation optimization segment led the AI in food innovation market in 2024, as it focuses on helping the food and beverage industry make the required changes to food and recipes to help the market grow. The segment also observes growth as it understands future consumer preferences and helps the business reduce food wastage and drive innovation, fueling market growth.

The nutritional and health-focused product innovation segment is expected to grow in the foreseeable future as the population of health-conscious consumers expands, thereby fueling market growth. The segment focuses on studying consumers’ demands and, using predictive analysis, recommends the right, nutritious, and beneficial choices by suggesting the right recipes and ingredients. The segment also focuses on recommending the right health-focused, ideal food preparation methods.

Service Type Analysis

The AI software and platforms solutions segment led the AI in food innovation market in 2024 due to high demand for automation, technological innovation, and new solutions to drive market growth. Advanced technology, such as data analysis and predictive analytics, is used to study consumer behavior and forecast future demand, further fueling the market's growth. The segment also helps suggest new and safe ingredients and recipes, further fueling market growth.

Integration with the IoT and smart manufacturing systems segment is expected to grow in the expected timeframe as it helps to focus on parameters such as enhancing quality control, improving supply chain management, improving the quality of the food and beverage industry, and various similar actions, further fueling the market’s growth in the foreseen period. The segment also focuses on understanding future consumer demands, further fueling market growth.

End User Analysis

The food and beverage manufacturers segment dominated the AI in food innovation market in 2024 due to the multiple benefits of technology, which are beneficial for market growth. Technological innovations help ensure food safety, improve food quality, better understand future consumer demands, and suggest new and innovative food ingredients and combinations to drive market growth. Hence, these factors collectively help fuel the market's growth.

Startups and SMEs in the food innovation segment are expected to grow over the foreseeable period as the market adopts AI for food safety and innovation, further fueling the market. The technology also helps suggest food ingredients and recipes that consumers will demand in the future through data analysis. Hence, such factors help to fuel the growth of AI in the food innovation market in the foreseeable period.

Deployment Mode Analysis

The cloud-based solutions segment led the AI in food innovation market in 2024, as it primarily focuses on technologically advanced options such as precision agriculture, quality control, and generative AI to better support product innovation and fulfill consumer demand in the future. Hence, such actions help to fuel the market’s growth. Cloud-based solutions, along with other technologically advanced options, support the food and beverage industry, further fueling market growth.

The on-premises solutions segment is expected to grow over the forecast period due to high demand and adoption in the food and beverage industry. The segment focuses on suggesting immediate actions to support the market’s growth, along with the required and beneficial remedies. The segment also helps manage data control and provide customization, further fueling the market's growth.

Distribution Channel Analysis

The direct-to-enterprise solutions segment dominated the AI in food innovation market in 2024, as it focuses on providing personalized solutions to enterprises through customized applications. It also helps provide customized solutions to food and beverage manufacturers, retailers, and processors to improve food safety, efficiency, and product development, which is beneficial for market growth.

The B2B partnerships/collaborations segment is expected to grow over the forecast period, as it highlights the importance of collaboration between technology and the food and beverage industry for market growth. It helps enhance food safety, quality, and efficiency, which is beneficial for the growth of AI in the food innovation market in the foreseeable future. AI also plays a major role in enhancing food quality, product innovation, and enabling novel food creation, further fueling the market’s growth.

Innovation Focus Analysis

The health and functional food innovation segment led the AI in food innovation market in 2024, as it helps enhance the nutritional levels of functional food, further fueling the market's growth. The segment also helps improve food safety and quality through technologically advanced methods, further fueling market growth. It also highlights consumer demand using data analytics.

The sustainability-focused product innovation segment is expected to grow over the forecast period, as it highlights the importance of AI for product innovation, reducing waste, and maintaining sustainability. The segment also highlights the importance of environmental balance, emphasizing the need for a lower carbon footprint.

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Additional Topics Worth Exploring:

Dietary Supplements Market: The dietary supplements market size is projected to reach USD 464.58 billion by 2034, growing from USD 192.68 billion in 2025, at a CAGR of 9.2% from 2025 to 2034.
Frozen Food Market: The global frozen food market size is expected to grow from USD 214.32 billion in 2025 to reach around USD 347.01 billion by 2034, at a CAGR of 5.5% over the forecast period from 2025 to 2034.
Vegan Food Market: The global vegan food market size is evaluated at USD 22.38 billion in 2025 and is expected to reach USD 55.88 billion by 2034, with a CAGR of 10.7% during the forecast period from 2025 to 2034.
Sugar-Free Food Market: The global sugar-free food market size is expected to grow from USD 48.14 billion in 2025 to USD 83.2 billion by 2034, growing at a CAGR of 6.27% during the forecast period from 2025 to 2034.
Food Additives Market: The global food additives market size is rising from USD 128.14 billion in 2025 to USD 214.66 billion by 2034. This projected expansion reflects a CAGR of 5.9% throughout the forecast period from 2025 to 2034.
Ethnic Food Market: The global ethnic food market size is forecasted to expand from USD 93.47 billion in 2025 to reach around USD 179.21 billion by 2034, growing at a CAGR of 7.5% during the forecast period from 2025 to 2034.
Meal Kits Market: The global meal kits market size is projected to rise from USD 17.11 billion in 2025 to approximately USD 58.8 billion by 2034, registering a CAGR of 14.7% during the forecast period from 2025 to 2034.
Baking Ingredients Market: The global baking ingredients market size is projected to grow from USD 18 billion in 2025 to around USD 31.72 billion by 2034, at a CAGR of 6.5% during the forecast period from 2025 to 2034.
Fresh Produce Market: The global fresh produce market size is projected to grow from USD 3,707 billion in 2025 to approximately USD 5,653 billion by 2034. This anticipated growth represents a CAGR of 4.80% during the forecast period from 2025 to 2034.
Beverage Packaging Market: The global beverage packaging market size is projected to reach USD 271.80 billion by 2034, growing from USD 173.71 billion in 2025, at a CAGR of 5.1% during the forecast period from 2025 to 2034.
Coconut Products Market: The global coconut products market size is expected to climb from USD 14.18 billion in 2025 to approximately USD 33.71 billion by 2034, growing at a CAGR of 10.1% during the forecast from 2025 to 2034.
Pet Food Market: The global pet food market size is expected to increase from USD 113.02 billion in 2025 to USD 167.97 billion by 2034, growing at a CAGR of 4.5% throughout the estimated timeframe from 2025 to 2034.
Organic Food Market: The global organic food market size is expected to grow from USD 253.96 billion in 2025 to USD 660.25 billion by 2034, with a compound annual growth rate (CAGR) of 11.20% during the forecast period from 2025 to 2034.

Top Companies in the AI in Food Innovation Market

IBM Food Trust / IBM Watson AI: IBM Food Trust, powered by IBM Watson AI, is revolutionizing the food supply chain with blockchain technology and AI solutions to improve transparency, traceability, and efficiency. By leveraging AI, they enhance food safety, quality, and sustainability across the entire food value chain.
TetraScience (Food & Beverage AI Solutions): TetraScience offers AI-driven data science solutions to help food and beverage manufacturers optimize their operations and enhance product innovation. Their platform focuses on improving R&D efficiency and accelerating the time-to-market for new products by integrating AI with laboratory data.
NotCo: NotCo uses artificial intelligence and machine learning algorithms to create plant-based food products that mimic animal-derived ingredients. Their innovative approach in food formulation helps reduce environmental impact while meeting the growing demand for plant-based alternatives.
Plant Jammer: Plant Jammer leverages AI to help consumers and chefs create personalized, plant-based recipes based on available ingredients. Their platform empowers users to experiment with flavors and optimize nutritional value, transforming the way people approach plant-based cooking.
Spoonshot: Spoonshot combines AI and data science to provide food companies with actionable insights into consumer preferences, emerging trends, and market gaps. Their AI-powered platform helps businesses innovate and create products that resonate with evolving consumer demands.
Brightseed: Brightseed uses AI to discover plant-based compounds with health benefits, accelerating the development of functional foods and ingredients. Their proprietary AI platform, Forager, helps identify bioactive compounds that improve human health, revolutionizing the health and wellness food sector.
BASF Digital Farming / Food Innovation AI: BASF’s Digital Farming division employs AI to support precision agriculture and food innovation, helping farmers optimize crop yields while reducing environmental impact. Their AI tools also contribute to the development of sustainable food systems and innovation in food production.
Cortexica Vision Systems (Food R&D AI): Cortexica applies AI to food R&D through computer vision and machine learning to automate quality control, product testing, and ingredient recognition. Their AI solutions enhance food safety, reduce waste, and optimize food development processes.
Tastewise: Tastewise uses AI to track food trends and consumer preferences, providing food businesses with real-time insights into emerging tastes. Their platform offers data-driven recommendations to enhance product development, marketing strategies, and innovation.
Nuritas: Nuritas combines AI and biotechnology to discover new peptides in food that improve human health. Their AI-driven approach accelerates the development of functional ingredients, making it easier to create food products with added nutritional benefits.
FoodPairing: FoodPairing leverages AI to analyze flavor combinations and optimize recipes. Their technology helps chefs, food developers, and brands discover innovative food pairings, resulting in unique flavor experiences that resonate with consumers.
Givaudan (AI-Powered Flavor Innovation): Givaudan uses AI and machine learning to enhance its flavor development process, enabling the creation of novel, customized flavors. Their AI-powered tools help food and beverage companies design flavors that cater to diverse consumer preferences and market trends.
PepsiCo (AI-Enabled Food R&D): PepsiCo’s use of AI in R&D helps the company streamline product development, predict consumer trends, and optimize supply chain operations. AI-driven innovation allows PepsiCo to create healthier, more sustainable food and beverage options tailored to consumer preferences.
Nestlé (AI-Driven Product Innovation Labs): Nestlé employs AI-driven product innovation labs to develop new food and beverage products that meet health, sustainability, and taste preferences. Their AI tools help identify consumer trends and optimize product formulations for better nutritional outcomes.
Kraft Heinz (AI for Consumer Insights & Innovation): Kraft Heinz leverages AI to gain deeper consumer insights, optimizing product development and marketing strategies. Their AI-driven approach supports the creation of innovative products, improving consumer engagement and responding quickly to market demands.

Segments Covered in the Report

By Technology / Platform

Machine Learning & Predictive Analytics
Big Data Analytics & Insights
AI-powered Recipe & Flavor Development Tools
Computer Vision & Quality Inspection Systems
Automation & Robotics in Food R&D

By Application

New Product Development & Formulation Optimization
Flavor & Taste Profiling
Nutritional & Health-focused Product Innovation
Supply Chain & Ingredient Sourcing Optimization
Consumer Preference Analysis & Market Insights

By Service Type

AI Software & Platform Solutions
Consulting & R&D Services
Data Analytics & Consumer Insights Services
Integration with IoT & Smart Manufacturing Systems

By End-User

Food & Beverage Manufacturers
Startups & SMEs in Food Innovation
Research & Development Institutes
Retail & Foodservice Companies
Ingredient & Flavor Companies

By Deployment Mode

Cloud-based Solutions
On-premise Solutions

By Distribution Channel

Direct-to-Enterprise Solutions
B2B Partnerships / Collaborations
Online / Platform-based Access

By Innovation Focus

Health & Functional Food Innovation
Flavor & Sensory Enhancement
Sustainability-focused Product Innovation
Convenience & Ready-to-Eat Product Development

By Region

North America

U.S.
Canada

Asia Pacific

China
Japan
India
South Korea
Thailand

Europe

Germany
UK
France
Italy
Spain
Sweden
Denmark
Norway

Latin America

Brazil
Mexico
Argentina

Middle East and Africa (MEA)

South Africa
UAE
Saudi Arabia
Kuwait

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