AI in Food Processing Market By Food (Fruit and Vegetable, Dairy, Meat & Poultry, Convenience Food & Snacks, Others), By Technology, By Application - Global Industry Outlook, Key Companies (ABB, Rockwell Automation Inc, Sight Machine, and others), Trends and Forecast 2024-2033

AI, or Artificial Intelligence, is creating big changes in how food is made. It's using smart technology like machine learning (ML) and computer vision to make the production of food faster, safer, and better. In food processing, AI does jobs like checking the quality of products, assisting them, and even anticipating when machines might need fixing. By looking at lots of data, AI can look into patterns & problems that humans might miss, helping to keep the food safe to eat.

The reason AI is becoming popular in food processing is that one needs to make food more efficiently and sustainably. With more people to feed, one finds ways to make food without losing too much energy or resources. AI helps do that by building production processes smarter, using less energy, and getting more food out of each harvest, which helps in producing food in a way that's better for the environment and people.

Further, there are many opportunities for companies working with AI in food processing. One big area is making machines smarter so they can do a lot of the work. By using AI, machines can do operations like sorting and packing food without requiring as much human help. Another opportunity is in making better quality control systems. With AI, one can spot problems with food faster & more accurately, making sure that what one eats is safe and tasty. Companies that aim to develop AI technology for these tasks have a chance to grow & make a real difference in how we make and enjoy food.

Key Takeaways

• Market Growth: The AI in Food Processing Market size is expected to grow by 13.1 billion, at a CAGR of 8.6% during the forecasted period of 2025 to 2033.
• By Food: The Fruits and Vegetables segment is expected to lead in 2024 with a major & is anticipated to dominate throughout the forecasted period.
• By Technology: Machine learning as technology is expected to lead AI in the food processing market in 2024.
• By Application: Quality Control & Safety Compliance is expected to get the largest revenue share in 2024 in the AI in Food Processing market.
• Regional Insight: North America is expected to hold a 37.5% share of revenue in the Global AI in Food Processing Market in 2024.
• Use Cases: Some of the use cases of AI in Food Processing include quality control & inspection, predictive maintenance, and more.

Use Cases

• Quality Control and Inspection: AI can be used in food processing to improve quality control & inspection processes. Machine learning algorithms can look into images of food products to detect defects, contaminants, or deviations from quality standards, which ensures that only safe & high-quality products reach consumers, minimizing the risk of foodborne illnesses & enhancing brand reputation.
• Predictive Maintenance: AI-driven predictive maintenance can maximize equipment performance & reduce downtime in food processing plants. By analyzing data from sensors & machine logs, AI algorithms can look into when machinery is likely to fail or need maintenance, which helps prevent unexpected breakdowns, reduces maintenance costs, and ensures constant operation of production lines.
• Optimized Production Planning: AI algorithms can look into historical production data, market forecasts for demand, and other relevant factors to improve production planning in food processing. By looking into patterns & trends, AI can recommend production schedules that reduce waste, minimize inventory holding costs, and meet fluctuating consumer needs more effectively, which leads to better efficiency and profitability for food processing companies.
• Ingredient and Recipe Optimization: AI can assist food processors in optimizing ingredient formulations and recipes to meet different objectives like cost reduction, nutritional enhancement, or flavor betterment. By looking at a large data set on ingredient properties, consumer preferences, and sensory perceptions, AI algorithms can provide optimal ingredient combinations and proportions, which allows food processors to create products that better align with market demands and regulatory needs, while also reducing development time and costs.

Market Dynamic

Driving Factors

Food manufacturers experience pressure to make their operations better, cheaper, and more productive. AI can help by automating tasks, improving how things are made, and making supply chains simple and easy. It also makes food safer by keeping an eye on quality & tracing where it comes from. As many focus on making things work well and keeping food safe, the need for AI in food processing keeps going up. In new markets where a lot of people are immigrating to cities & have more money to spend, so there's a higher need for processed food.

 
These places often struggle with keeping food safe & making sure it's good quality. AI can help fix these problems by making production smoother, checking quality, & tracking where food goes. It can also help manage the supply chain better, cutting down on waste, and making sure food gets to people on time. Companies that work with AI can look into new customers in these growing markets and become important parts of how food is made across the world.

Opportunities

There is fast urbanization in emerging markets, where the middle class is growing, there's a higher demand for processed and packaged foods. However, these markets often have issues like food safety, supply chain efficiency, and quality control. AI technology provides solutions to these challenges by easy production, ensuring product quality, and allowing traceability.

 
In addition, AI can optimize supply chain logistics, reduce waste, and allow timely delivery of food products to meet the higher consumer demand. Expanding into these emerging markets provides a major opportunity for AI providers to unlock new revenue streams and establish themselves as major players in the global food processing industry. With AI's potential to improve efficiency and address important issues, it becomes a vital tool for businesses aiming to expand in these dynamic market environments.

Restraint Factors

Despite the growth, there are certain challenges to the AI in food processing market, as it costs a lot at first, and companies have to spend money on new equipment, software, and ways to use AI with their existing systems. They also have to train their workers how to use it, which can be hard for smaller companies that don't have much money. But as AI gets better & cheaper, and as many companies look into the good things it does, it will be easier for everyone to use.

 
Further, AI needs a lot of information to work well, including things that are private or important to a company. Keeping this information safe and private is important to make sure people trust AI and the companies that use it. Further, Food companies have to use better ways to keep data safe, like codes and special rules about who can see it. They also need to make clear rules about who owns the data and who can use it, which will help people trust that AI is being used in the right way and help it work better for everyone and if not done rightly, could heavily impact the growth of the market.

Trends

The increase in demand for personalized food products is driving the expansion of the AI in food processing market, which has caused the integration of AI technologies into food processing, making consumers personalize their purchases to their preferences. With AI-driven solutions, customers can easily review and personalize their orders, supported by AI chatbots providing suggestions and assistance throughout the ordering process.

 
The availability of these innovative tools is attracting more consumers to engage in product customization, thereby creating the growth of AI technology within the food processing sector. As businesses look to meet changing consumer demands for personalized experiences, the adoption of AI in food processing not only improves customer satisfaction but also supports innovation and competitiveness in the industry, which highlights AI's role in shaping the future of food processing, driving efficiency, and delivering personalized solutions to meet different consumer needs and desires.

Research Scope and Analysis

By Food

In the AI in Food Processing market, the Fruits and Vegetables segment is expected to take a leading role, securing a major portion in 2024, which is due to many factors that make it a major target for AI integration in food processing. Fruits & vegetables across the globe are essential parts of a healthy diet, driving higher consumption. However, processing these items provides other challenges like their sensitive nature, varying quality, and the need for accurate handling. AI technologies offer solutions to address these challenges and optimize the processing of fruits & vegetables effectively.

Further, the main reason for the dominance of the Fruits and Vegetables segment is the critical importance of quality control and sorting. AI-powered computer vision systems are capable of looking into live images of fruits and vegetables, quickly identifying defects, assessing ripeness, and sorting them based on many parameters like size, color, and shape, which ensures consistent quality while highly reducing manual labor, making it an appealing solution for processors in the fruit & vegetable industry.

 
In addition, AI algorithms play a major role in optimizing processing parameters for fruits & vegetables. By analyzing data related to factors like temperature, humidity, and processing duration, AI systems can look into the optimal conditions for preserving freshness, flavor, & nutritional value, which results in better product quality, higher shelf life, and lower waste within the fruits and vegetables segment. In addition, the rising need for convenient and ready-to-eat products benefits this segment, as AI technologies allow efficient processing and packaging, meeting consumer choice for healthy and convenient food options.

By Technology

The machine learning segment is expected to dominate AI in the food processing market in 2024, using specialized algorithms to transform supply chain management. These algorithms play an important role in improving many supply chain processes, ranging from demand prediction and inventory optimization to logistics streamlining and distribution efficiency. By using machine learning, businesses can reduce waste, trim costs, and support overall supply chain efficacy, thus providing sustainable operations and profitability. Moreover, machine learning algorithms look into customer preferences, market trends, and historical sales data to refine menus for restaurants and cafes, supporting the creation of attractive and economically viable menu offerings customized to evolving consumer tastes.

Further, the robotics and automation sector is anticipated to experience significant growth throughout the forecast period, driven by AI-powered innovations transforming precision agriculture. AI-driven robotics play an important role in modernizing agricultural practices, undertaking tasks like planting, harvesting, and monitoring crop health with the most accuracy and efficiency. 

Furthermore, autonomous vehicles combined with AI capabilities look into fields autonomously, analyze complex datasets, and optimize farming methodologies, ultimately supporting crop yields and resource usage, which not only improves productivity but also promotes sustainable farming practices, contributing to global food security and agricultural sustainability initiatives. As the need for efficient and sustainable agricultural solutions intensifies, the robotics and automation segment is expected to come out as an important driver of innovation and transformation within the food processing market.

By Application

The Quality Control & Safety Compliance segment is expected to hold a leading position as an application in the AI in Food Processing market in 2024, capturing a major share, which is mainly due to the higher importance of upholding food safety standards & regulatory compliance within the food processing industry. Quality control & safety compliance are important aspects of food processing, essential for safeguarding consumers against health risks and maintaining the reputation of food manufacturers. AI technologies provide specialized solutions to tackle the complexities & challenges associated with ensuring quality control and safety compliance.

Further, the key factor driving the dominance of the Quality Control & Safety Compliance segment is AI's capability to quickly detect and prevent contaminants and quality defects. AI-powered systems, integrated with advanced computer vision technology, can look into images and videos to identify foreign objects, contaminants, and irregularities in food products, which not only enhances consumer safety but also helps food manufacturers meet strict regulations and standards. In addition, AI algorithms excel in analyzing large datasets to recognize patterns and anomalies indicating potential quality issues or deviations in food processing.

 
By constantly monitoring parameters like temperature, humidity, pH levels, and production metrics, AI systems can look into deviations from desired standards & prompt alerts or corrective actions, which supports effective quality control and compliance management, ensuring that only safe and high-quality products reach the market. Also, the Quality Control & Safety Compliance segment benefits from the increase in the adoption of AI in food traceability systems, where AI-powered data analytics allow complete tracking & tracing of products throughout the supply chain, which helps in swiftly identifying potential issues or recalls and ensures compliance with traceability regulations.

The AI in Food Processing Market Report is segmented on the basis of the following:

By Food

• Fruits and Vegetables
• Dairy
• Meat & Poultry
• Convenience Food & Snacks
• Others

By Technology

• Machine Learning
• Computer Vision
• Robotics and Automation

By Application

• Quality Control & Safety Compliance
• Customer Engagement
• Production & Packing
• Food Sorting
• Maintenance
• Others

Regional Analysis

North America is expected to lead the global AI in food processing market, by accounting for a major share of 37.5% in 2024, which is due to various factors contributing to the adoption of AI in the region's food industry. Firstly, North America supports a stronger technological infrastructure & a well-developed food processing sector. With many leading technology firms & research institutions driving innovation in AI, companies in the region can build and implement advanced solutions customized to the unique demand of food processing.

In addition, North America gives importance to food safety and quality control, supported by strict regulatory frameworks. AI technologies provide advanced capabilities for live monitoring & quality assurance, aligning smoothly with the region's aims on food safety standards, with the culture of adopting technology, combined with a skilled workforce in AI, using the quick integration of these solutions into food processing operations. Moreover, North America's consumer need for processed & packaged foods, driven by busy lifestyles, drives the need for efficient processing techniques. AI allows automation, optimization, and customization in food production, meeting the expectations of consumers for high-quality, convenient food options.

Further, Asia Pacific is expected to be the fastest-growing region, as it plays a significant role in driving the growth of global AI in food processing market. The region's increase in population, rapid urbanization, and growth of disposable incomes are driving the need for processed food products. Moreover, governments and businesses are funding advanced technologies to improve food safety, quality control, and production efficiency. With an expanding food industry & a growing focus on technological innovation, Asia Pacific provides higher opportunities for the adoption and development of AI solutions in food processing.

Competitive Landscape

In the Global AI in Food Processing market, many players compete for market share by providing innovative AI solutions customized to the unique needs of the food processing industry. These competitors aim to develop advanced technologies, like machine learning, computer vision, and data analytics, to look into various aspects of food production, quality control, and supply chain management. 

In addition, companies differentiate themselves by focusing on factors like scalability, efficiency, and compliance with food safety regulations. Also, collaboration with research institutions and strategic partnerships with food manufacturers further enhance their competitive edge. The need for AI in food processing constantly grows as competition among providers intensifies, driving further innovation & development in the industry.

Some of the prominent players in the global AI in Food Processing Market are:

• ABB
• Rockwell Automation Inc
• Sight Machine
• Key Technology
• Tomra
• Martec of Whitell Ltd
• Raytec Vision
• Sesotec GmbH
• Agco Corporation
• Bratney Companies
• Other Key Players

Recent Developments

• In March 2024, Boogie Lab, a Croatian food tech company and craft bakery launched Boogie Lab USA and Boogie Bakery, the company’s first U.S.-based micro bakery opening in spring 2024, as it uses a unique approach to sourdough fermentation, combining AI with traditional techniques.
• In January 2024, Tomra Food launched two artificial intelligence-powered sorting and grading solutions focused on making the production of fresh & processed foods more efficient and profitable, as its Neon pre-grades machine harvested blueberries for the fresh market, while the new-generation Spectrum X series uses deep learning for unmatched sorting &grading precision of fruit. Further, AI is relevant for food production because of the high level of variability in the industry, from weather & climate effects to natural variations in products, which means that traditional systems can have a tough time making accurate predictions.
• In November 2023, GrubMarket launched Farm-GPT, an advanced new generative artificial intelligence (AI) product created to empower American farmers & growers with valuable data-driven insights for higher profits and optimizing crop selection. Farm-GPT uses the power of advanced AI and the latest available pricing data from both the USDA and proprietary sources to help farmers make better decisions about which imports to cultivate based on market demand and revenue potential.
• In August 2023, Samsung Electronics launched Samsung Food, a personalized, AI-powered food and recipe platform. Releasing in 8 languages in over 100 countries across the world, it would offer complete food experiences through over 160,000 available recipes, acting as a customized assistant that helps users discover new dishes, create personalized meal plans, and order ingredients online, and will also help users control their cooking appliances while giving step-by-step guided cooking & allowing users to share their favorite recipes on social media.
• In July 2023, Swiggy formed a dedicated team of about five employees looking solely at identifying new uses of artificial intelligence (AI) throughout the company, as it has been experimenting with technology by using AI to build images of food products and, in some cases, descriptions of them as well. Further, it recently launched WhatToEat, a feature that helps food discovery by enabling customers to explore curated options based on their moods and appetites. Moreover, it has also used AI, usually in the form of bots, to help customers with their inquiries.
• In June 2023, European Commission along with Member States and over 120 partners from research, industry, and public organizations launched EUR 220 million or USD 238 million worth of investment in four sectoral Testing and Experimentation Facilities (TEFs) for AI, at an event in Copenhagen, as he European Commission co-funds the TEFs with over EUR 110 million or USD 118 million for five years under the Digital Europe Programme. TEFs are created to help AI developers bring trustworthy AI to the market more efficiently and support its growth in Europe, along with acting as a sandbox for AI technologies’ development and deployment.