The integration of artificial intelligence (AI) and data analytics in food technology may lead to new innovations. From personalized nutrition to smart packaging solutions, protecting IP in AI-driven food tech applications will become crucial.
One of the most interesting areas for the potential development of AI and machine learning innovation, which might not immediately come to mind when considering AI’s potential, is in the food and beverage industries. AI solutions are being presented for challenges from farm to shops to plate and we are already seeing the bow wave of AI-focused innovation in the food space through patent applications before UK and EU patent offices.
Here are some of the key areas where AI and associated innovations might have the greatest impact on the way we eat.
Crops and agriculture: The potential for AI to revolutionise modern farming techniques are wide-reaching. AI tools could be used to review images of crops to identify early-stage indicators of disease, allowing farmers to act more proactively in preventing the spread of disease and to improve crop yields as a result. AI image-detection software might also enable farmers to identify ripe produce for harvest in real-time, improving the speed and efficiency of harvesting.
Additionally, AI models can monitor the upkeep of agricultural equipment to identify faults before they happen, and even measure and predict the climate to help mitigate its effects on crop growth and harvests.
Quality control, logistics and distribution: The use of robotics and tangentially AI monitoring and control systems is a trend in distributions and logistics as a whole. The ability of AI to monitor and quality check large-scale product portfolios quickly is especially useful for perishable goods, which are of course prevalent in the food industry. AI vision models could be used to review whole batches of produce for defects more efficiently than human eyes can make out. Having AI image models review production processes in real time can support staff in managing quality control procedures during the production and packing processes.
AI models such as YOLO (You Only Look Once) can be used to better and more efficiently identify bacteria – such as E.coli – apart from other bacterial species. This enables rapid screening of food products and can vastly reduce time delays associated with these checks in distribution, with no compromises on safety.
Forecasting demand and waste reduction: By utilising AI models to analyse historical usage and demand, food producers can minimise food inventory and subsequently reduce food waste. Any leftover food or ingredients should be heavily reduced, but can then be redistributed to philanthropic organisations as food relief or sold onto consumers through apps such as Too Good to Go.
Food packaging and labelling: AI might be used to assist in the development of “Smart Packaging” for food products. AI is being used to develop a wide range of packaging solutions to improve the freshness, security, shelf-life and reusability of products. Smart packaging might also incorporate smart labels, which can incorporate QR codes to provide additional nutritional or recipe information to consumers.
In a potential glimpse of what might become more prevalent in food production and packaging creation in the near future, new energy drink Vivi Cola has been created in a collaboration between ChatGPT and Midjourney – with the recipe devised by ChatGPT and the branding design and wording created via Midjourney.
Recipe creation: AI tools are being developed to support and speed up the process of recipe creation. Major food producers, retailers and restaurants are using AI large language models to review ingredients and to speed up the development process of new recipes and products. Nestle, for example, has developed its “Gut Friendly Recipes” platform to create personalised recipe ideas for customers with conditions like Crohn’s Disease.
In another example, NotCo have made extensive use of its platform, Giuseppe, to review the molecular and chemical make up of foodstuffs and to suggest alternatives which scientists, manufacturers and restaurateurs can then incorporate into recipes and dishes suitable for varied diets and nutritional requirements. Likewise, Climax foods is using machine learning in the creation of plant-based alternatives to dairy products.
There are already consumer tools, such as Mealime which make use of AI applications to review ingredients in a user’s kitchen and to create meal ideas for consumers quickly and efficiently at home.
Personalised nutrition: Leading on from this, AI tools could be developed to review and individual’s medical and nutritional needs and to create recipe ideas and alternative ingredient lists for them for the best possible nutritional profile for them, to support their health and wellbeing. The use of AI in this way intersects with the increasing trend for personalised healthcare and has fantastic implications for managing conditions like Crohns disease, IBS and various allergies with specialised meal plans and food alternatives.
AI biotech start-up Brightseed has created Forager, an AI tool that combines biomedical research with a huge database of the chemical make-up of ingredients which can then be compared to alternatives to create recipes catering to specific dietary and medical needs.
3D printing food: To finish, one development which is AI-adjacent, but holds exciting potential for the food and beverage industry, is the 3D printing of ingredients and even whole dishes.
The use of 3d printers in food is still principally limited to use in high-end cuisine. The technology is not easily scalable, and likely to remain that way for some time. Nevertheless, some pioneers are already creating – and selling – 3d printed food to the consumer market. Revo Foods, an Austrian-based start-up, has created a vegan steak based on fungal protein that resembles salmon, called THE FILET. Other examples include BeeHex, which has raised over US$1 Million to make 3D-printed pizza a reality, and the PancakeBot – which 3D prints pancake art.
Conclusions
AI is still comparatively in its infancy but its ability to revolutionise the way we farm, shop and eat already feels apparent. We expect to see increasing levels of patent applications for AI-assisted technology relating to the food and beverage industry in the near future.
Read more about the work of our food and beverage team in bringing new food innovation to market here.
Boult’s AI practice works with AI developers and with clients in industries looking to make the most of the power of AI in supporting their own innovation and development. Read our latest thoughts on AI and its impact on IP here.
