The artificial intelligence (AI) in foodtech market size is expected to see exponential growth in the next few years. It will grow to $37.18 billion in 2030 at a compound annual growth rate (CAGR) of 33.9%. The growth during the forecast period can be attributed to increasing investments in AI-enabled foodtech platforms, growing demand for solutions focused on waste reduction, expanding applications of personalized nutrition, increasing use of AI robotics in food preparation, and greater integration of AI with smart appliances. Major trends during the forecast period include growing adoption of AI-driven food quality monitoring, increasing use of predictive analytics for demand forecasting, expanding deployment of smart kitchen automation, increasing adoption of AI-based supply chain optimization, and greater emphasis on personalized nutrition solutions.
The expansion of the food delivery business is anticipated to support the growth of artificial intelligence (AI) in the foodtech market going forward. The food delivery business refers to the industry segment that directly delivers prepared meals from restaurants, cafes, or other food establishments to customers’ locations, including homes and offices. The food delivery business is expanding due to rising consumer demand for convenience, the increasing adoption of online ordering platforms, and the growing availability of delivery services offered by a broad range of restaurants and food providers. AI in food supports the food delivery business by optimizing delivery route planning, forecasting customer preferences for personalized recommendations, and automating order management to improve operational efficiency and reduce delivery times. For instance, in May 2024, according to the Economic Times, an India-based media company, during the first half of 2023, Swiggy (an India-based online food ordering and delivery platform) recorded a 17% year-on-year increase in gross merchandise value (GMV) in its food delivery business, reaching $1.43 billion. Therefore, the expansion of the food delivery business is driving the adoption of artificial intelligence (AI) in the foodtech market.
Key companies operating in the artificial intelligence (AI) in foodtech market are focusing on developing advanced solutions such as AI-powered ingredient discovery platforms to improve the speed and efficiency of new ingredient development. AI-powered ingredient discovery platforms utilize machine learning and extensive biological datasets to quickly identify natural proteins or molecules with desired functional properties for applications in food, agriculture, personal care, or materials. For example, in May 2024, Shiru Inc., a US-based protein discovery company, launched ProteinDiscovery.ai, the world’s first marketplace and discovery platform for proteins with an AI-driven search, catalog, and licensing system. ProteinDiscovery.ai provides users with access to a database containing more than 33 million natural proteins from plants and microbes and enables companies to search, test, license, and purchase protein molecules for various applications. The platform supports the prediction of protein functionality and expression, substantially reducing research and development (R and D) timelines and costs. It supports applications such as identifying clean-label sweet proteins, highly stable proteins, or plant-based fat and texturizing proteins, and aims to accelerate the process from discovery to commercial product development.
In May 2024, GrubMarket, a US-based technology company, acquired Butter for an undisclosed amount. The acquisition will enable GrubMarket to utilize Butter's AI-powered e-commerce and payment technologies to broaden its range of innovative, AI-powered solutions developed for the food supply chain industry, while also enhancing the capabilities of its existing portfolio of advanced software products, including Grubassist AI and WholesaleWare, and strengthening its position as the enterprise AI solution provider for America's food supply chain industry. Butter is a US-based technology company that offers AI-enhanced sales tools designed to automate order entry processes.
Major companies operating in the artificial intelligence (AI) in foodtech market are Microsoft Corporation, Cargill Incorporated, International Business Machines Corporation, Oracle Corporation, SAP SE, NVIDIA Corporation, Zebra Technologies Corporation, TOMRA Systems ASA, Blue Yonder Group Inc., Grubhub Inc., Google DeepMind Technologies Limited, Rebel Foods, Tovala, Saffron Tech, Blue River Technology, Brightseed, Clear Labs Inc., Nutrino Health Ltd., FoodLogiQ, NotCo Ltd., AgShift, Zest Labs, ImpactVision.
North America was the largest region in the artificial intelligence (AI) in foodtech market in 2025. The regions covered in the artificial intelligence (AI) in foodtech market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
The countries covered in the artificial intelligence (AI) in foodtech market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
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Table of Contents
Executive Summary
Artificial Intelligence (AI) In Foodtech Market Global Report 2026 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses artificial intelligence (ai) in foodtech market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
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Description
Where is the largest and fastest growing market for artificial intelligence (ai) in foodtech? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The artificial intelligence (ai) in foodtech market global report answers all these questions and many more.The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
- The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
- The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
- The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
- The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
- The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
- Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.
Scope
Markets Covered:
1) By Component: Solution; Services2) By Application: Food Production And Processing; Product Development And Innovation; Supply Chain Management; Food Safety And Compliance; Other Applications
3) By End-User: Food And Beverage Manufacturers; Restaurants And Food Service Providers; Other End-Users
Subsegments:
1) By Solution: AI-Based Food Quality Monitoring Systems; AI-Powered Predictive Analytics For Demand Forecasting; AI in Supply Chain Optimization; Smart Kitchen Solutions; AI For Personalization In Food Recommendations; Automated Food Processing And Packaging Systems; AI-Driven Food Safety Systems; AI-Powered Robotics For Food Preparation2) By Services: AI Consulting Services; AI Integration and Implementation Services; AI Training and Support Services; Managed Services For AI Systems; AI Data Analytics Services; AI Algorithm Customization Services; AI Testing And Quality Assurance Services
Companies Mentioned: Microsoft Corporation; Cargill Incorporated; International Business Machines Corporation; Oracle Corporation; SAP SE; NVIDIA Corporation; Zebra Technologies Corporation; TOMRA Systems ASA; Blue Yonder Group Inc.; Grubhub Inc.; Google DeepMind Technologies Limited; Rebel Foods; Tovala; Saffron Tech; Blue River Technology; Brightseed; Clear Labs Inc.; Nutrino Health Ltd.; FoodLogiQ; NotCo Ltd.; AgShift; Zest Labs; ImpactVision
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain.
Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast.
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita.
Data Segmentations: Country and regional historic and forecast data, market share of competitors, market segments.
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
Delivery Format: Word, PDF or Interactive Report + Excel Dashboard
Added Benefits
- Bi-Annual Data Update
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Companies Mentioned
- Microsoft Corporation
- Cargill Incorporated
- International Business Machines Corporation
- Oracle Corporation
- SAP SE
- NVIDIA Corporation
- Zebra Technologies Corporation
- TOMRA Systems ASA
- Blue Yonder Group Inc.
- Grubhub Inc.
- Google DeepMind Technologies Limited
- Rebel Foods
- Tovala
- Saffron Tech
- Blue River Technology
- Brightseed
- Clear Labs Inc.
- Nutrino Health Ltd.
- FoodLogiQ
- NotCo Ltd.
- AgShift
- Zest Labs
- ImpactVision

