AI and the food industry

What does artificial intelligence have to do with food? No matter what it can or will be able to do, it will never be able to eat or drink. Nevertheless, it will influence the food industry and nutritional science just as it does many other areas.

Artificial intelligence (AI) has actually been around for a long time. It was originally developed for analysing data, recognising patterns and predicting outcomes, such as for autonomous driving. Generative AI aims to independently create new content based on learnt data and patterns; currently, this can be seen above all in the fields of art, text, language, film and music. In addition, with ChatGPT, AI is finding its way into the everyday lives of many people.

Where is AI already being used in the food sector?

Quality and productivity: The role of AI in the food industry is an example of how technology can be employed not only to increase efficiency and productivity, but above all – and this is where ORIOR sees its primary use – to further improve quality, promote innovation and create more sustainable food production processes.
Research and development: AI is already being utilised by producers and retailers to improve processes or create new recipes and products. AI has also long been used to develop targeted brand messages and predict market opportunities and trends.
Inspection: In the field of food sorting and quality control, AI is employed to recognise defective in products and remove them from the production line.
ChefGPT, Chef Watson, Tastewise: ChefGPT, Chef Watson and other AI tools can be used to call up AI-driven recipe recommendations, compile meal plans or discover out-of-the-ordinary food combinations. For example, you can enter the available ingredients and then receive a suitable recipe. Tastewise helps to identify trends ahead of the mainstream.

Opportunities of AI

Innovation: AI enables the discovery of new food compositions and product innovations by analysing large amounts of data and identifying patterns that are not recognisable to humans.
Quality: Specialised technologies allow products to be controlled more precisely, which increases consumer safety and satisfaction.
Smart farming: Smart farming involves the use of AI technology to increase yields and optimise cultivation conditions. AI can recognise plant diseases and pests, but also detect ecological influences and soil properties, and is thus able to optimise the growing conditions for crops.

Risks of AI

Data protection: Collecting and analysing large amounts of consumer data raises questions concerning data protection and security. This calls for a high level of corporate responsibility, which is correspondingly costly.
Dependence: A strong dependence on AI systems can make companies vulnerable to technical disruptions, which can have drastic financial consequences.
Ethical concerns: These relate to the potentially harmful use of AI for people and the environment – for example, through the development of unhealthy food or its use for developing more energy-intensive methods of food production.

ORIOR and AI: quality, innovation and sustainability

Within the next two years, AI will primarily be used by the communications and marketing teams. We naturally also employ AI in already established processes, such as high-bay warehouses.

As from autumn 2024, Rapelli intends to utilise AI for its online marketing, in order to present products in the shop to consumers in different ways, depending on profile, season, bestseller or bundling.

The topic of AI is being systematically pursued at Group level and its use is planned in line with the size and goals of the company. The focus here is on quality, innovation and sustainability.

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