AI in Food Market Size, Share, and Trends 2024 to 2033

AI in Food Market (By Technology: Machine Learning, Computer Vision, Robotics and Automation; By Application: Precision Agriculture, Food Processing, Supply Chain Management, Retail Services; By End-user: Food Manufacturers, Farmers and Growers, Restaurants, Others) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2024-2033

  • Last Updated : February 2024
  • Report Code : 3745
  • Category : ICT

The global AI in food market size is expected to rise with an impressive growth rate and generate the highest revenue during the period 2024 to 2033. AI in food market is revolutionizing the whole food industry by pursuing improved efficiency, personalized nutrition, and data-driven decision-making.

AI in Food Market Size 2024 to 2033

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Key Takeaways

  • Asia Pacific is observed to expand at the fastest rate during the forecast period of 2024-2033.
  • By technology, the machine learning segment held the largest share of the market in 2023.
  • By technology, the robotics and automation segment is observed to witness a significant growth during the forecast period.
  • By application, the food processing segment held a significant share of the AI in food market in 2023.
  • By application, the supply chain management segment is observed to witness the fastest rate of expansion during the forecast period.
  • By end user, the food manufacturers segment held the dominating share of the market in 2023.
  • By end user, the restaurants segment is observed to witness a significant rate of expansion during the forecast period.

AI in Food Market Overview

The AI in food market offers the application of artificial intelligence (AI) technologies in various aspects of the food industry to enhance efficiency, innovation, and overall operational processes. AI is utilized to optimize and streamline food supply chains, from production and distribution to inventory management, reducing waste and enhancing overall efficiency.

Culinary innovation

AI-powered kitchen appliances and culinary applications bring innovation to home cooking, offering personalized recipes, cooking assistance, and flavor profiling. This trend in AI food market is observed to enhance the utilization of AI technology owing to the requirement for personalized diet plans.

  • For instance, Samsung Food, an AI-powered personalised food and recipe platform, was launched, according to a statement from Samsung Electronics Australia. With more than 160,000 recipes available in eight languages, Samsung Food will serve as an online food orderer and personal chef for Australians, assisting them in creating personalized meal plans and discovering new recipes.

Menu optimization

Restaurants are leveraging artificial intelligence to analyze customer preferences, optimize menus, and tailor offerings to match trends, enhancing the dining experience and operational efficiency.

  • Leading online food delivery platform in India, Swiggy announced in November 2023 that it is utilizing AI capabilities for creating visually appealing menus for restaurants. Swiggy has launched Baked, a photoshoot feature in its Swiggy Owner app that validates restaurant menus.

AI in Food Markets Major Breakthrough

  • A food tech/e-commerce company GrubMarket operating in Canadian and United States food supply chain has launched Farm-GPT in September 2023. Farm-GPT, a revolutionary new generative artificial intelligence (AI) product from GrubMarket aims to supply American farmers and growers with useful data-driven insights for boosting earnings and improving crop selection.
  • Farm-GPT helps farmers make educated decisions with its capabilities including, data-driven decision making, regional specific recommendations, user friendly interface and real-time market intelligence.
  • In addition to giving farmers access to AI technologies to improve their decision-making, GrubMarket has established itself as the leading enterprise AI supplier for the US food supply chain sector.

AI in Food, Predictive Analytics and Cost Reduction

With its capabilities, the integration of AI in food is observed to be helpful to reduce the overall cost for food and beverage businesses. With the advanced capability of predictive analytics, AI is capable of offering solutions for product launch, success rate along with safety monitoring.

The cost reduction offered by such capabilities is observed to act as a supplement to the growth of AI in food market.

  • In September 2023, Nordic tech company Cambri announced the release of Launch AI, that offers companies with predictions and advice for NPDs. The AI, which has worked with food and beverage companies such as Carlsberg and Nestle reduces the risk of product launch while offering cost reduction for the overall production process.

AI in Food Market Scope

Report Coverage Details
Largest Market North America
Base Year 2023
Forecast Period 2024 to 2033
Segments Covered By Technology, By Application, and By End-user
Regions Covered North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa


AI in Food Market Dynamics

Driver

Utilization of AI by online food delivery businesses

  • Zomato, a food delivery platform, has launched 'Foodie Buddy,' a chatbot that is tailored and controlled by artificial intelligence (AI) in September 2023. In a recent blog post, the business stated that the chatbot's purpose is to help clients choose restaurants. Zomato AI functions through a framework of many agents, providing it with a wide variety of cues for different activities.

Online food delivery businesses are customizing consumer experiences by using AI technologies. By monitoring user behaviour and preferences, recommender systems make relevant meal recommendations that increase user pleasure and loyalty. AI assists in anticipating client demand trends, which enables companies to maximise their stock levels. This reduces food waste and lowers the possibility of stockouts by ensuring that popular foods are sufficiently stocked. Thereby, the rising utilization of AI technology by online food delivery platforms is observed to act as a driver for the AI in food market.

Restraint

Lack of standardized data

Without standardized data formats and structures, interoperability between different systems becomes challenging. This can hinder the seamless integration of AI solutions across various stages of the food supply chain, from production to distribution and retail. A degree of quality and consistency is guaranteed by standardised data. The accuracy and dependability of AI algorithms may be severely impacted by inconsistent data formats, inaccuracies, and insufficient information in the absence of standards.

Opportunity

Rising emphasis on understanding consumer patterns

AI algorithms can analyze vast amounts of consumer data to understand individual preferences, dietary restrictions, and consumption patterns. This enables the delivery of personalized food recommendations, creating a more tailored and satisfying culinary experience for consumers. This acts as a significant opportunity for AI in food market. Restaurants and food services can leverage AI to analyze customer preferences and tailor their menus accordingly. This allows for dynamic menu adjustments, promoting dishes that align with popular trends and individual tastes.

  • American company Campbell Soup Company, that deals with canned soup products stated that it is utilizing artificial intelligence to understand the consumer behavior patterns. The company believes that the technology has helped them in launching products such as spicy chicken noodles and spicy sirloin burger.

Technology Insights

The machine learning segment held the dominating share of the AI in food market in 2023. Machine learning algorithms are employed to optimize supply chain processes, from predicting demand and optimizing inventory levels to streamlining logistics and distribution. This helps reduce waste, lower costs, and improve overall supply chain efficiency. Machine learning is used to analyze customer preferences, popular trends, and historical sales data to optimize menus for restaurants and cafes. This assists in creating appealing and profitable menu offerings.

The robotics and automation segment is observed to witness a significant rate of growth during the forecast period. AI-driven robotics are used in precision agriculture for tasks like planting, harvesting, and monitoring crop health. Autonomous vehicles equipped with AI can navigate fields, analyze data, and optimize farming practices, leading to increased crop yields and resource efficiency.

  • LTC Hospitality in August 2023 launched a robotic restaurant in Lucknow, India. This robot restaurant has a seamless integration of cutting-edge AI technology. Robots integrated with AI capabilities at the restaurant hold excellence in accessing data from tables while maintaining health protocols.

Application Insights

The food processing segment dominated the AI in food market in 2023 and the segment is observed to witness a notable growth in the upcoming years. AI systems enable better traceability of food products throughout the processing journey. In case of recalls, the technology helps identify affected batches swiftly, enhancing food safety. AI facilitates predictive maintenance in food processing equipment. By analyzing data from sensors and machinery, AI systems can predict when equipment might require maintenance, minimizing downtime and disruptions in the processing line.

  • Bangalore-based Mukunda Foods has developed multiple machines with the integration of artificial intelligence and Internet of Things (IoT) that are capable of producing or cook global cuisines while reducing the overall cost and time required for the production. Eco-fryer, dosa maker, noodle and rice maker are few examples of machines the company has installed.

On the other hand, the supply chain management segment is observed to expand at a rapid pace during the forecast period. AI-powered systems automate inventory management by continuously monitoring stock levels, expiration dates, and other factors. This ensures better control over inventory, minimizes stockouts, and reduces excess inventory holding costs.

  • In January 2024, major Japanese brands Ajinomoto and Meji stated that they are focusing on the utilization of AI technology for inventory management in order to reduce the waste. Companies have aimed to focus on strengthen the production efficiency, demand forecasting as well as ingredient ordering functions.

End-User Insights

The food manufacturers segment led the market in 2023, the segment also holds a noteworthy potential for growth for the predicted timeframe. AI enables food manufacturers to optimize their supply chains by predicting demand, managing inventory efficiently, and enhancing overall logistics. This results in improved production planning and reduced wastage.

Manufacturing of food is more efficient when regular operations and procedures are automated with AI-driven robotics and machine learning. This involves operations like handling, packing, and sorting, freeing up human labour for more difficult jobs. AI technology help manufacturing plants use less energy. AI algorithms are used by smart energy management systems to improve energy use, lowering expenses and impact on the environment. By maximising resource utilisation, cutting waste, and enhancing overall environmental effect, AI assists food makers in implementing sustainable practices.

The restaurants segment is observed to witness the fastest rate of expansion in the AI in food market during the forecast period. AI technologies enable restaurants to offer personalized and seamless customer experiences. From AI-powered chatbots handling orders to personalized menu recommendations based on customer preferences, the focus is on improving overall satisfaction. AI-powered predictive maintenance ensures that restaurant equipment, such as ovens and refrigerators, is well-maintained. This reduces downtime, operational disruptions, and unexpected repair costs.

Regional Insights

North America dominated the AI in food market with the largest share in 2023.

North America is observed to sustain the dominance in the upcoming years. The United States, in North America constitute a global centre of technical innovation. Leading technological firms and academic institutions are present in the country, which encourages the creation and application of AI solutions in the food sector. With universities, research centres, and private businesses actively involved in AI research, the area has a strong ecosystem for research and development.

This cooperative setting speeds up the development of AI applications for a range of industries, including the food sector. Large sums of money are invested in AI startups and IT enterprises in North America. The development and expansion of AI solutions for the food sector, such as supply chain optimisation and precision agriculture, are made possible by this capital inflow. This element encourages the region's AI in food market expansion.

Key advancements in North America AI in food market

  • Food manufacturers in the United States are aiming to utilize AI capabilities to nutritionally optimize their food production methods.
  • In 2022, a new effort aimed at utilising AI for food production, safety, security, and disease resistance was unveiled by the U.S. Department of Agriculture.
  • Businesses such as myAnIML and Serket apply computer vision to identify disease in cattle so that farmers may treat it quickly and reduce or avoid using antibiotics.

Collaboration between tech companies, startups, and established players in the food industry is common in North America. These collaborations often lead to the development and integration of AI solutions into existing food production and distribution systems.

Asia Pacific is observing the fastest expansion in the market with noteworthy growth

While expanding at a rapid pace, Asia Pacific poses a strong position in the AI in food market owing to the ongoing technological advancements in the region. Asia Pacific countries have been quick to adopt new technologies. Increased connectivity and tech-savvy consumers contribute to the rapid integration of AI solutions in the food industry. With a large and increasingly urbanized population, the demand for convenient and tech-driven solutions in the food sector is rising. AI technologies offer efficiency in production, distribution, and delivery.

The surge in online food delivery and e-commerce platforms in the Asia Pacific region creates opportunities for AI applications in optimizing delivery routes, personalizing recommendations, and managing logistics.

  • India placed 6.5 million orders for food online on New Year Eve 2023, 18% rise from year 2022.
  • Zomato stated in its annual report 2022-23 that it has witnessed an approximate 17% growth on active food delivery restaurant partners.
  • In Financial Year 2023, online orders on Zomato India grew by 21% as compared to FY2022. According to the company’s official statement, customers placed 647.0 million orders in 2023.

Key advancements in the Asia Pacific AI in food market

  • India-based Cropin employs machine learning to assist farmers in tracking weather cycles, predicting yields, evaluating soil health and water stress, and keeping an eye on the biodiversity and health of about 10,000 crop varieties.
  • A Chennai-based restaurant chain ‘Robot’ started offering services with designated robots for dine-in consumers from 2022.

Recent Developments

  • In January 2024, the modular end-to-end surplus food management solution that Too Good To Go, a mobile app devoted to lowering food waste, has introduced will help grocery retailers—from hypermarkets to convenience stores—unlock value from extra inventory. The AI system oversees and facilitates the redistribution of excess food and caters to supermarket shops of various sizes in North America and Europe.
  • In January 2024, Tomra Food introduced two artificial intelligence-driven sorting and grading systems to increase the productivity and profitability of the manufacturing of both processed and fresh food. According to the business, Spectrim X incorporates the most recent advancements in Tomra's LUCAi deep-learning technology, which was developed by a group of scientists, engineers, researchers, and professionals. Deep learning is an AI technique that teaches computers how to process data, such as intricate patterns in images, by using pretrained models.
  • In November 2023, a pioneer in the field of digital marketing, Jumboking Burgers announced the debut of its creative AI-generated campaign. The Peri Peri Nachos Burger and the fiery Schezwan Burger are two new offerings to the festive menu in the campaign, which is distinguished by state-of-the-art computer-generated imagery (CGI).

AI in food market Companies

  • Google LLC
  • IBM Corporation
  • ABB Ltd
  • NVIDIA Corporation
  • Microsoft Corporation
  • SAP SE
  • Buhler Group
  • Impact Vision

Segments Covered in the Report

By Technology

  • Machine Learning
  • Computer Vision
  • Robotics and Automation

By Application

  • Precision Agriculture
  • Food Processing
  • Supply Chain Management
  • Retail Services

By End-user

  • Food Manufacturers
  • Farmers and Growers
  • Restaurants
  • Others

By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East and Africa

Frequently Asked Questions

The major players operating in the AI in food market are Google LLC, IBM Corporation, ABB Ltd, NVIDIA Corporation, Microsoft Corporation, SAP SE, Buhler Group, Impact Vision, and Others.

The driving factor of the AI in food market is the utilization of AI by online food delivery businesses.

North America region will lead the global AI in food market during the forecast period 2024 to 2033.

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology (Premium Insights)

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on AI in Food Market 

5.1. COVID-19 Landscape: AI in Food Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global AI in Food Market, By Technology

8.1. AI in Food Market, by Technology, 2024-2033

8.1.1 Machine Learning

8.1.1.1. Market Revenue and Forecast (2021-2033)

8.1.2. Computer Vision

8.1.2.1. Market Revenue and Forecast (2021-2033)

8.1.3. Robotics and Automation

8.1.3.1. Market Revenue and Forecast (2021-2033)

Chapter 9. Global AI in Food Market, By Application

9.1. AI in Food Market, by Application, 2024-2033

9.1.1. Precision Agriculture

9.1.1.1. Market Revenue and Forecast (2021-2033)

9.1.2. Food Processing

9.1.2.1. Market Revenue and Forecast (2021-2033)

9.1.3. Supply Chain Management

9.1.3.1. Market Revenue and Forecast (2021-2033)

9.1.4. Retail Services

9.1.4.1. Market Revenue and Forecast (2021-2033)

Chapter 10. Global AI in Food Market, By End-user 

10.1. AI in Food Market, by End-user, 2024-2033

10.1.1. Food Manufacturers

10.1.1.1. Market Revenue and Forecast (2021-2033)

10.1.2. Farmers and Growers

10.1.2.1. Market Revenue and Forecast (2021-2033)

10.1.3. Restaurants

10.1.3.1. Market Revenue and Forecast (2021-2033)

10.1.4. Others

10.1.4.1. Market Revenue and Forecast (2021-2033)

Chapter 11. Global AI in Food Market, Regional Estimates and Trend Forecast

11.1. North America

11.1.1. Market Revenue and Forecast, by Technology (2021-2033)

11.1.2. Market Revenue and Forecast, by Application (2021-2033)

11.1.3. Market Revenue and Forecast, by End-user (2021-2033)

11.1.4. U.S.

11.1.4.1. Market Revenue and Forecast, by Technology (2021-2033)

11.1.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.1.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.1.5. Rest of North America

11.1.5.1. Market Revenue and Forecast, by Technology (2021-2033)

11.1.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.1.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2. Europe

11.2.1. Market Revenue and Forecast, by Technology (2021-2033)

11.2.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2.4. UK

11.2.4.1. Market Revenue and Forecast, by Technology (2021-2033)

11.2.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2.5. Germany

11.2.5.1. Market Revenue and Forecast, by Technology (2021-2033)

11.2.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2.6. France

11.2.6.1. Market Revenue and Forecast, by Technology (2021-2033)

11.2.6.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.6.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2.7. Rest of Europe

11.2.7.1. Market Revenue and Forecast, by Technology (2021-2033)

11.2.7.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.7.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3. APAC

11.3.1. Market Revenue and Forecast, by Technology (2021-2033)

11.3.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3.4. India

11.3.4.1. Market Revenue and Forecast, by Technology (2021-2033)

11.3.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3.5. China

11.3.5.1. Market Revenue and Forecast, by Technology (2021-2033)

11.3.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3.6. Japan

11.3.6.1. Market Revenue and Forecast, by Technology (2021-2033)

11.3.6.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.6.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3.7. Rest of APAC

11.3.7.1. Market Revenue and Forecast, by Technology (2021-2033)

11.3.7.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.7.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4. MEA

11.4.1. Market Revenue and Forecast, by Technology (2021-2033)

11.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4.4. GCC

11.4.4.1. Market Revenue and Forecast, by Technology (2021-2033)

11.4.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4.5. North Africa

11.4.5.1. Market Revenue and Forecast, by Technology (2021-2033)

11.4.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4.6. South Africa

11.4.6.1. Market Revenue and Forecast, by Technology (2021-2033)

11.4.6.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.6.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4.7. Rest of MEA

11.4.7.1. Market Revenue and Forecast, by Technology (2021-2033)

11.4.7.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.7.3. Market Revenue and Forecast, by End-user (2021-2033)

11.5. Latin America

11.5.1. Market Revenue and Forecast, by Technology (2021-2033)

11.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.5.4. Brazil

11.5.4.1. Market Revenue and Forecast, by Technology (2021-2033)

11.5.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.5.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.5.5. Rest of LATAM

11.5.5.1. Market Revenue and Forecast, by Technology (2021-2033)

11.5.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.5.5.3. Market Revenue and Forecast, by End-user (2021-2033)

Chapter 12. Company Profiles

12.1. Google LLC

12.1.1. Company Overview

12.1.2. Product Offerings

12.1.3. Financial Performance

12.1.4. Recent Initiatives

12.2. IBM Corporation

12.2.1. Company Overview

12.2.2. Product Offerings

12.2.3. Financial Performance

12.2.4. Recent Initiatives

12.3. ABB Ltd

12.3.1. Company Overview

12.3.2. Product Offerings

12.3.3. Financial Performance

12.3.4. Recent Initiatives

12.4. NVIDIA Corporation

12.4.1. Company Overview

12.4.2. Product Offerings

12.4.3. Financial Performance

12.4.4. Recent Initiatives

12.5. Microsoft Corporation

12.5.1. Company Overview

12.5.2. Product Offerings

12.5.3. Financial Performance

12.5.4. Recent Initiatives

12.6. SAP SE

12.6.1. Company Overview

12.6.2. Product Offerings

12.6.3. Financial Performance

12.6.4. Recent Initiatives

12.7. Buhler Group

12.7.1. Company Overview

12.7.2. Product Offerings

12.7.3. Financial Performance

12.7.4. Recent Initiatives

12.8. Impact Vision

12.8.1. Company Overview

12.8.2. Product Offerings

12.8.3. Financial Performance

12.8.4. Recent Initiatives

Chapter 13. Research Methodology

13.1. Primary Research

13.2. Secondary Research

13.3. Assumptions

Chapter 14. Appendix

14.1. About Us

14.2. Glossary of Terms

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