AI in foodtech: plans, ideas, features

While some people perceive AI as just a helper for creative tasks, and others play with generating pictures, rationalists make full use of AI at work. We decided to look into what processes AI is taking over in foodtech. Should businesses think about implementing it or is it all just a hype so far.

Who uses AI in foodtech today and how?

In fact, AI has already penetrated deep into the food tech industry, including restaurants. Experts predict that the value of AI in the food and beverage market will reach $29.94 billion by 2026 at a growth rate of 45.77%.

Restaurant order automation

Restaurant chain Wingstop, with nearly 2,000 locations, has implemented AI to handle phone orders. Digital sales now account for 60% of the company’s total revenue, a record high in the company’s history. So the plan is to digitize 100% of its operations.

Wingstop has partnered with ConverseNow to create a virtual ordering assistant. It can answer multiple calls simultaneously and speak English and Spanish. According to Restaurant Business, chains such as Del Taco, Domino’s, Panera, Checkers and Newk’s Eatery already use similar technology.

Bhavin Asher, CTO of GRUBBRR, a systems solutions company, said this is just the beginning of AI’s impact on the food industry:

In five years, AI will be widely used in both external and internal operations. It will be able to do forecasting, reporting, inventory control and workforce requirements

Food Manufacturing

Campbell Soup Co. is using AI to collect and analyze data to understand what customers want in the future. As part of the initiative, the company introduced new products, Chunky Ghost Pepper Chicken Noodle Soup and RedHot Goldfish Crackers. The AI helped determine that today’s consumers love spices.

Campbell is also using AI to analyze trends — artificial intelligence predicted the rise in popularity of fryers, which helped introduce Kettle brand Air Fried Chips.

Retail

Instacart recently announced that they are testing third-generation smart grocery carts, equipped with AI for the first time.

The updated Caper Cart has scales, sensors, touch screens and computer vision. Anything that goes into the cart is automatically scanned, and then the cost is displayed on the screen. So you can always control the total amount. And to pay for your order, all you have to do is scan the barcode on the cart screen in the self-service area of the store and pay in the most convenient way. Despite all these additional features, the new cart is thinner and lighter than the previous version.

Perhaps most importantly for retailers will be the fact that the new product comes with tiered charging — you can charge multiple carts at once, rather than doing it individually as before, or swapping batteries.

What’s the word on startups?

Optimizing Delivery with Artificial Intelligence

Swiggy, a well-known Indian food delivery startup, has integrated AI to accurately predict delivery times and determine the most efficient routes.

Personalized recommendations

Zomato, another popular food delivery platform, uses AI to analyze customer preferences, order history and ratings to provide personalized restaurant recommendations.

AI for personalized meals

Cure.fit, a health and wellness startup, uses artificial intelligence to create personalized meal plans for customers based on their health goals, dietary restrictions and food preferences.

Intelligent Inventory Management

Fasoos, a fast-casual restaurant chain, uses AI to analyze data: the system can predict demand patterns and optimize inventory levels, reducing food waste and ensuring the availability of fresh ingredients.

Smart kitchens driven by artificial intelligence

Rebel Foods, known for its cloud kitchen model, uses AI and machine learning to automate a variety of kitchen tasks. From controlling food quality to managing kitchen workflows.

Who will Chat GPT help?

Agriculture and farming

AI can monitor crops. For example, it can analyze satellite/drone imagery and sensor data and then present the results to the farmer to choose one of the suggested solutions. What else?

Sales forecasting: farmers will be able to sell their produce at the best time, depending on market needs.

Process management: increasing or decreasing the amount of water or fertilizer needed for crops, depending on the condition of the crops.

Livestock monitoring to monitor animal health and behavior, in particular to detect and prevent disease.

Farm automation: AI can be used to pilot robots in the fields, mainly for harvesting and weed control.

In addition, AI is already being used to create “new crops” either through genetic engineering or traditional breeding methods. Here Chat GPT helps to “guess” which crosses will have the desired traits.

Producing

Discovering interesting traits in nature: many plants have yet to be explored. Some have properties that will be useful in creating a more “pure” formulation of products. So The Live Green Co. is using AI to look for alternatives to methylcellulose in plant-based meat production.

Synthetic biology: it can take years to recreate the desired protein from bacteria and then scale up the process. So scientists are looking for ways to reduce the time it takes to synthesize a protein so they can move from idea to industrial scale faster.

Bioreactor management, especially for cell agriculture. In this area, companies still only have demo versions of products, but there is no way to scale their production. Startups are trying to solve this problem by creating AI-powered smart bioreactors to once again speed up the process.

Distribution

These processes are usually invisible to the consumer, but they affect the formation of the final value of goods. In each of them, AI will allow us to come up with the most rational solution faster.

• Food quality and safety control
• Data exchange between suppliers and retailers (the big pain)
• B2B marketplaces (one of this year’s hottest topics)
• Optimizing the supply chain
• Combating food waste in both retail stores and restaurants

In some cases, however, AI can be used in direct-to-consumer applications:

For transparency: to deliver the most up-to-date data about the food they buy (or should buy) to the consumer.

Personalization: To analyze consumers’ health and dietary preferences, and then to create individualized meal plans.

Here, in both cases, the use of Chat GPT can greatly increase efficiency and even monitor user compliance.

In general, retail is constantly evolving, and brands are increasingly using D2C to grow and scale. This is where AI comes in handy as a tool for creating personalized and targeted content aimed at each consumer. For example, it could look like an e-cookbook for a specific consumer based on what they have bought or what is currently in their shopping cart.

Restaurants

Personalization rules the ball in this area as well. There’s no denying the fact that the better you know each of your consumers, the more personalized the offer you will make to them. And that means gaining trust and getting a “brand advocate”.

AI can literally lead the customer by the hand and help them keep track of what they eat. For example, with a combined AI and IoT in the form of a smart wristband that will assess the user’s daily food choices, study their genetic code, and determine their predisposition to diet-related diseases.

Of course, ordering kiosks won’t surprise anyone anymore, but there are pioneering caterers who have gone one step further. For example, they are experimenting with kiosks and facial recognition technology to identify regular diners and make offers to them based on calorie intake, eating habits, past orders and preferences.

Bonus

Researchers at the National Institute of Standards and Technology have created an AI for wine tasting. It can taste and identify wines with more than 95% accuracy. To train the virtual tasting AI, experts assigned 13 attributes to wines, including strength, ash content, magnesium, alkalinity and color, and trained the network on 148 wine samples from different grape varieties.

Meanwhile, in Australia, an “electronic nose” that uses 8 sensors to detect flavor is “sniffing out” fraud in the whiskey industry. NOS.E can identify samples, determine the region in which the whiskey is produced and even identify the 6 brands with an accuracy of 96%.

Already, you can hear someone starting to lament that AI is stealing our cravings. But, look, it goes much deeper than that. By teaching AI to detect taste and smell, to analyze our preferences and needs (based on our health status), we can endlessly improve the taste of food and technology for making artificial products, opening up a world of innovative culinary creations that meet different preferences, dietary needs and cultural traditions.

So what does AI mean for foodtech?

Artificial intelligence is simultaneously nowhere and everywhere. It’s just a tool that every player in the industry can use to expand their audience, reduce costs, and improve the efficiency of their project. To succeed, whenever AI encounters users, it must be invisible and make sure that the end result meets or even exceeds our expectations.

We think the impact of AI on food will be huge, but it will be slow to manifest itself as it requires adaptation and change across the supply chain. However, the big players already have more chances and opportunities to stand out. So keep an eye on the giants, learn from their experience and make plans on how to implement in your business.