Artificial intelligence is impacting every industry and every place, and as AI-enabled technologies evolve and are adopted more and more, so will their impact.
AI is already pervasive in many processes in the food industry, and technological advances show no signs of slowing down. Looking to the future, AI, machine learning, and next-generation algorithms will continue to bring about disruptive changes.
How will AI change the food industry five years from now?
AI takes over routine tasks in food industry
“I want an AI to do my laundry and the dishes so I can do my art and writing, not an AI to do my art and writing so I can do my laundry and the dishes,” the future-thinking author Joanna Maciejewska recently wrote.
For those using large-scale language models like ChatGPT or Midjourney, or those who do the laundry or dishes, it's clear that AI is better suited to creative activities than household chores.
Did the industry get it wrong? Probably, but not for long. Looking to the future, it's the mundane tasks that AI is best suited to tackle, says Olaf van der Veen, founder and CEO of Orbisk, an AI-powered food waste monitoring tech startup.
Van der Veen believes artificial intelligence and datasets have the potential to make the entire food system more efficient, more sustainable and less wasteful. This is particularly important in the restaurant industry, where AI can manage “routine” and “repetitive” tasks for operators, van der Veen suggested at food and agriculture technology conference F&A Next in the Netherlands.
When it comes to food waste, chefs rarely take the time to monitor exactly where it is occurring in their establishment. Considering that an average-sized restaurant throws out around 30-60 kg of food per day, this equates to over 10,000 kg of food per restaurant per year, which is not good news for either the environment or the restaurant's bottom line.
Aubisque will use image-tracking relight technology to identify which ingredients are being wasted and how much of them, and this is just one way AI can act as a “co-pilot” for the industry, he explained.
AI-enabled technologies will enable industry players to avoid routine tasks and focus on what they do best – providing ‘great products’ and ‘great services.’ “That’s what I think AI will do in the food system – it will provide efficiency, sustainability and economics. [benefits]. “
Understand what consumers want from food and beverages
One of the main challenges facing the food industry is understanding consumer trends: what types of foods, flavors, formats and ingredients do consumers want to buy?
Traditionally, food and beverage brands have relied on sensory panels, market analysis and field trials to develop new products, and to a large extent still do.
But five years from now, AI could revolutionize how brands understand what consumers want from food.
That's the perspective of Alon Chen, head of Tastewise, an Israeli startup that uses AI to analyze online restaurant and delivery menus, social media interactions and home recipes to help food and beverage innovators find market opportunities.
“We're looking at consumer decisions and inferring what their intent is,” explains Tastewise co-founder and CEO of F&A Next. “Over the next five years, consumer intent and decisions will be visible and fully understood by the industry.”
Chen is troubled that with all the data now available, including from food delivery platforms, the industry still doesn't know what's on consumers' plates. “There's so much information out there…
“Five years from now, it will be very clear to everyone what people are eating and drinking and why.”
Deeper insight into fruit and vegetable cultivation
Other challenges facing the food industry are logistics and quality control, and Jonathan Belté, founder of Belgian computer vision AI platform Robovision, believes AI-enabled technology has the potential to improve both.
For outdoor growers of fresh produce such as tomatoes and peppers, bad weather can have a significant impact on quality and quantity, with obvious knock-on effects for retailers who may suffer supply shortages.
But if a retailer’s AI-powered weather forecasting model predicts an upcoming heatwave that will negatively impact tomato supplies, it could avert a shortage by ordering more tomatoes from greenhouse growers.
RoboVision is using deep learning techniques to develop agricultural robots for greenhouses that can apply “sensory innovations,” Berthe explained, which could include robotic “grippers” for harvesting fresh produce and hyperspectral imaging to help identify and eradicate diseases.
The founders expect that over the next few years, such technology will give the industry better control over how fresh produce is grown, with implications for players further down the supply chain.
“We will know everything about each fruit and vegetable, which will create a huge continuum of choices for both consumers and retailers.”
Food retail industry must prepare for massive AI disruption
The food retail industry needs to prepare for massive disruption from AI.
That's the view of Sabine Benoist, a marketing professor at the University of Surrey in the UK, who believes AI-powered technology will completely change the way consumers shop.
AI-enabled technology won't replace food stores, but food stores that have AI-enabled technology will replace those that don't, she told delegates at the IFE in London.
For example, AI-powered in-store navigation can provide shoppers with a Google Maps-like tool: consumers can search for a specific food item on their phone and be guided to the item, with a flashing digital price tag indicating its location.
For those who suffer from food allergies, AI technology can be used to scan barcodes and notify consumers if the product in question is unsafe to eat, while image recognition scales for fresh produce will be able to detect not only the weight of fruits and vegetables, but also their specific variety.
In retail, AI disruption won't just be aimed at shoppers. It could also change the way employees interact with shoppers in-store. In large retail stores, employees often communicate with each other using headsets, what Benoit calls “first generation” headsets.
In the future, these headsets may enter a “second generation” phase: by linking to ChatGPT, employee headsets will be able to automatically respond to staff and customer queries.
