AI in Food Quality Control Market Size (2024 - 2030)

In 2023, The AI in Food Quality Control Market was valued at $ 7.16 Billion, and is projected to reach a market size of $ 60.05 Billion by 2030. Over the forecast period of 2024-2030, market is projected to grow at a CAGR of 35.5%.

AI in food quality control offers efficiency and accuracy in quality assessment and data analysis of food quality that can prevent food damage and reduce spoilage. AI enables visual inspection of food products that helps manufacturers detect defects, contaminants, or irregularities in packaging. Further, it helps in analyzing the shape, texture, and color of food products and classifying them based on different quality grades. Additionally, sensors in food processing and packaging machinery can analyze data that can predict equipment malfunction and reduce downtime, thereby reducing delays in the manufacturing process. Furthermore, due to the increasing demand for quality food products, there is an increase in demand for AI in food quality control in the market.

Global AI in Food Quality Control Market Drivers:

Increasing demand for food safety and regulatory compliance has boosted the demand for AI in food quality in the market.

Ensuring food safety and compliance is a crucial part of the food production and manufacturing industry and therefore food companies are putting more emphasis on food and brand protection. Moreover, food faces numerous issues during the sourcing, production, and manufacturing process, especially perishable commodities. These include issues in hygiene, wrong product labeling, allergen control, food contamination, and others. As per CDC (Center for Disease Control), 48 million people in the US get sick, 128,000 are hospitalized, and 3000 people die each year from foodborne diseases. Hence, governments and regulatory bodies continuously update regulations for food safety. These regulations aim to reduce food spoilage, protect consumers’ health, and coerce companies to maintain industry standards. Further, AI in food quality control ensures compliance and monitoring of food which helps companies to analyze the temperature, sanitation, and pH level during the production and manufacturing process. Furthermore, AI algorithms help to monitor food data from sensors, analyze the patterns, and provide real-time insights on food quality to manufacturing companies.

Advancements in technology drive the demand for AI in food quality.

Technological advancements in food quality control have made it easier for companies to reduce food spoilage and upfront costs. Further, these AI algorithms help to analyze food data during the manufacturing process which reduces future anomalies. These data include sourcing of food ingredients, shape, color, and texture of food, predicting food shelf-life, and others. With the help of these data, companies can ensure food safety and maintain brand loyalty and trust among consumers. Further, with integration with sensors, advanced cameras, and IoT devices, food companies can detect objects, classify food into different qualities, analyze packaging inconsistencies, and others. Moreover, NLP (Natural Language Processing) analyses text data such as product descriptions, labels, and customer feedback to identify food allergens and ensure compliance with labeling and safety regulations.

Global AI in Food Quality Control Market Challenges:

Data security concerns can hinder the growth of AI in food quality control in the market. In food quality control data is collected and processed by AI systems that include confidential information about the production, ingredient formulations, and customer feedback, which is exposed to unauthorized access and can result in data leaks, leading to declined demand for AI in food quality control. Moreover, cyber threats can malfunction the AI systems which can further impact the food quality control process.

Global AI in Food Quality Control Market Opportunities:

The Global AI in Food Quality Control Market is anticipated to deliver lucrative opportunities for businesses, which include acquisitions, partnerships, collaborations, product launches, and agreements during the forecasted period. Furthermore, the rising demand for hygienic food production and manufacturing solutions is predicted to develop the market for AI in food quality control and enhance its future growth opportunities.

COVID-19 Impact on the Global AI in Food Quality Control Market:

The pandemic had a significant impact on the food industry. Due to the increased focus on hygiene and safety, there was an increase in demand for AI in food quality control by manufacturers as it offered them contactless solutions for quality control, reduced food anomalies, and enhanced food safety. Additionally, it boosted the need for remote monitoring solutions for food quality control due to social distancing norms. These monitoring systems were connected to the AI systems in manufacturing facilities that automated the inspection and quality control procedures without human intervention.

Global AI in Food Quality Control Market Recent Developments:

In April 2023, Todsa Ashram School, at Etapalli in India, installed a new AI machine to determine the food quality on the student’s plate. The machine helped to analyze food quality and improved the BMI of children. This AI-based machine was provided by a Delhi-based food tech startup -Udyogyantra.

AI IN FOOD QUALITY CONTROL MARKET REPORT COVERAGE:

Global AI in Food Quality Control Market Segmentation: By Technology

• Computer Vision

• Machine Learning

• Sensor-Based Technology

• Big Data Analytics

• Others

Based on market segmentation by technology, computer vision occupies the highest share of the market. Computer vision technologies analyze the images and videos of food products and detect anomalies. These include defects in food items, perishability, presence or absence of contaminants, irregularities, discoloration, and others. Further, due to their ability to detect anomalies in food products on the spot, they are widely used in food processing industries to automate visual inspections, enhance accuracy, speed up the detection process, and ensure proper food quality.

The sensor-based technology is the fastest-growing segment during the forecast period. These include the integration of sensors with AI systems for monitoring and controlling food quality. Sensors help to measure temperature, humidity, gas levels, pH levels, chemical composition, and others to provide real-time insights about food quality and prevent food spoilage.

The machine learning segment occupies a significant share of the market. Machine-learning models analyze food data generated by AI systems assess and make predictions regarding food quality. For instance, ML models can predict the shelf life of a specific food by analyzing the patterns and historical data of the food.

Global AI in Food Quality Control Market Segmentation: By End-Users

• Food Manufacturers

• Retailers & Food Service Providers

Based on market segmentation by end-user, food manufacturers occupy the highest share of the market. Food manufacturers are the major users of AI systems for ensuring food quality. They require advanced AI solutions to inspect raw materials, monitor the production process, detect anomalies in food items, and analyze final food products.

The retailer & food service providers segment is the fastest-growing segment during the forecast period. They require AI systems to protect their brand, differentiate themselves from competitors by ensuring food quality and safety. Further, they deploy advanced AI systems to assess the quality of food, detect potential damages, separate defected or contaminated food from normal ones, and ensure that only high-quality products are available to the consumers. This further helps them to gain consumers’ loyalty to their brand.

Global AI in Food Quality Control Market Segmentation: By Deployment

• Cloud

• On-Premise

Based on market segmentation by deployment, the cloud segment occupies the highest share of the market. It involves hosting AI solutions on cloud platforms. In this deployment mode, the AI systems can enable remote monitoring and control of the food product via mobile application. Further, cloud-based AI systems ensure the storage of data at a centralized platform, thus offering easy accessibility and scalability to food companies.

The on-premise segment occupies a significant share of the market. These are deployed at the food manufacturing and processing facilities for food quality control. They include hardware and software components, that can be managed by the company itself. Moreover, on-premise AI solutions offset the data leak disadvantage posed by cloud platforms by offering greater data security and control.

Global AI in Food Quality Control Market Segmentation: By Region

• North America

• Europe

• Asia Pacific

• Middle East and Africa

• South America

Based on market segmentation by region, North America occupies the highest share of the market. The presence of stringent government regulations and technological expertise is fuelling the growth of AI in food quality control in the market. Government and regulatory bodies in the region such as FDA (Food and Drug Administration) in the USA and (CFIA) Canadian Food Inspection Agency have been updating food safety regulations to ensure that food companies comply with these regulations and safety standards and provide quality food products to the consumers. Moreover, state-of-the-art infrastructure investment such as advanced lasers, sensors, computer vision, and autonomous quality control robots is driving the demand for AI in food quality control in the region.

Asia-Pacific is the fastest-growing region during the forecast period. Government support in the form of investment for setting up advanced AI solutions and the emergence of food tech start-ups have contributed to the demand for AI in food quality control in the region.

Global AI in Food Quality Control Market Key Players:

1. KPM Analytics

2. Robovision

3. Bruker

4. Robro Systems

5. Clarifruit

6. Alpha MOS

7. Zeiss

8. Intello Labs