The global Artificial Intelligence In Food & Beverages market, which was estimated at about 2.97 (USD Billion) in 2019 and is predicted to accrue earnings worth 28.87(USD Billion) by 2026, is set to record a CAGR of nearly over 44.75% during 2020-2026.
Over the last few years, Artificial Intelligence has gained a lot of traction, with many corporations investing heavily in researching the technology’s possibilities in the industry. AI is assisting food and beverage industries with supply chain management via logistics, predictive analytics, and transparency.
Organizations are increasingly digitizing their supply chains in order to differentiate themselves and drive revenue growth, which is enhancing supply chain efficiency. Supply chains generate vast volumes of data, and Artificial Intelligence is assisting organizations in analyzing this data and gaining a better knowledge of supply chain variables by foreseeing future scenarios.
Artificial Intelligence in Food & Beverages Market is assisting firms in their efforts to innovate quickly by shortening time to market and developing an agile supply chain capable of anticipating and dealing with uncertainty. This is propelling Artificial Intelligence’s rise in the food and beverage industry. The F&B industry benefits from AI in many ways, but the exorbitant cost of large-scale adoption is limiting market growth. One of the difficulties in the food processing sector is the feedstock, which is rarely consistent. Food storage appears to be done with the use of manual labor. However, with AI, this sorting process may be automated, lowering labor costs, increasing speed, and increasing yields.
For example, Kewpie Corporation, a Japanese food processing company, employs TensorFlow machine learning powered by AI to detect food irregularities. According to the organization, they intend to expand their usage of Artificial Intelligence in the future, which will assist them in adhering to tight safety standards.
Companies with established data analytics capabilities and a team of capable engineers can construct their own AI platform with confidence. Without such resources, F&B players look for solutions and providers based on clearly defined goals, needs, and budgets.
Scope of the Report Global Artificial Intelligence In Food & Beverages Market in Future
Artificial Intelligence (AI) is the process of creating intelligent machines that act and react in the same way that people do. The goal is to teach computers to think intelligently in the same way that people do. Until recently, the machines have done exactly what they were told. However, AI will allow machines to think and act like humans. AI is being used in the food processing business to improve varied offerings, optimise processes, and provide a better consumer experience.
- By Application: Food Sorting, Quality Control and Safety Compliance, Consumer Engagement, Production and Packaging, Maintenance, Other Applications
- By End User: Food Processing Industry, Hotel and Restaurant, Beverage Industry
- Geography: North America, Europe, Asia-Pacific, Rest of the World
Restraint
Stringent Regulatory Compliances to food safety and regulatory requirements
Manufacturers of food and beverage products are faced with the problem of adhering to increasingly stringent food safety and regulatory requirements. As a result, there is a pressing need to keep an eye on inventory and maintain food quality at all times. A great deal of money can be lost for businesses as a result of these circumstances.
Increased Costs of Machine/Equipment Upgrades
As a result, automation in food processing and packaging is seen as a means of improving productivity and efficiency. However, because machines perform jobs continuously and at a faster rate, these machines must be improved or new equipment must be purchased to keep up with client demand. Because of the high cost of food processing and packaging machinery, businesses will have to take more time to decide how to proceed moving forward.
Artificial Intelligence in the Food and Beverage Industry: Global Trends and Uses
It is expected that the production and packaging segment will account for the largest share of the market due to the rising demand for a wide range of modern and ready-made packaging as demand for food exports picks up. This segment is divided into food processing, quality control, customer interaction, production and packaging, maintenance, and so on.
Challenges in the Workplace (Business)
Because of rapidly changing consumer habits, technology breakthroughs, and severe regulations, the food and beverage business has undergone a series of changes over the past decade. The food and beverage business has faced numerous challenges as a result of such issues. In the global AI in food and beverage industry, factors such as consumer preferences for food that can be delivered quickly, as well as food that is easily accessible and affordable, are driving the market’s expansion.
Case studies
- Food Market Analysis: It is essential for restaurants to know which meals are most profitable to feature on their menus in order to boost sales and profits. It’s more crucial than ever to stay ahead of the curve when it comes to customer and market needs. With the use of Data Collection and Classification technologies, AI/Machine Learning models users’ preference behaviour and predicts what they desire — even before they do — by splitting them into distinct demographic categories.
- Production Optimization: Artificial Intelligence (AI) has the potential to optimise production and find the ideal operating points in manufacturing facilities to meet and even exceed KPIs. Rapid production changeovers, reducing the time needed to transition from one product line to another and the early detection of potential production bottlenecks are only some of its possible uses.
- Waste Reduction: It is possible to reduce waste by using AI/Machine Learning based ways to measuring and monitoring. Monitoring in real-time can catch anomalies before they have time to affect an entire batch or cycle, which saves time and money.
- Supply Chain Management: In order to ensure the safety and transparency of the AI food delivery and goods tracking process, algorithms based on Artificial Neural Networks can be used to monitor and check each step. Pricing and inventory forecasting are also made, preventing unexpected expenses.
- Hygiene: Food and beverage facilities rely heavily on hygiene and cleanliness, both of which may be greatly improved with AI. It is possible to use an AI-powered multi-sensor system to determine the ideal cleaning time by detecting food residue and microbiological debris on equipment.
