Given the ever increasing consumer demands and preferences for quality and taste, food industry is turning to Artificial Intelligence to achieve more at lesser costs. Whether it be understanding consumer preferences, or reducing waste, whether it be aligning supply chain capabilities, Machine Learning and Artificial Intelligence have come to the fore.
Artificial Intelligence is impacting every sector of the food industry, enabling companies to keep-up with consumer demands, better demand forecasting, and improving food quality insurance.
Some of the myriad ways in artificial intelligence is being currently used by food industry ranges from more efficient inventory management to waste reduction. For consumers, artificial intelligence applications would lead to targeted consumer offers as well as personalized nutrition plans and food recipe recommendations.
Here are some of the back end applications of AI in the food industry, from the farm to the consumer:
AI for Farming: Artificial Intelligence can support in disease detection and pest control, as well as in improving soil health and yield. Artificial Intelligence solutions can help farmers to grow better and efficient food yield, through ensuring optimal growth conditions. Such solutions can support farmers by monitoring heat, water stress, salinity, and ensuring good yield.
Sorting Fresh Produce: One of the biggest challenges faced by food processing plants relates to the irregular availability of feedstock. Food processing plants depend on manual sorting to sift and sort vegetables, leading to loss of efficiency and increased costs.
By using Artificial Intelligence, food processing companies can achieve significant automation for food cataloguing, using a combination of cameras, lasers and machine learning to enable food sorting with enhanced efficiency. For instance, by deploying Artificial Intelligence involving sensor-based optical sorting solutions, the tardy time-consuming processes for sorting fresh produce can be removed, leading to higher yield with better quality and lesser wastage.
Efficient Supply Chain Management: By embracing Artificial Intelligence and Machine Learning, companies can prioritize their supply chain capabilities, and improve their efficiencies. For instance, companies can monitor the food safety quality, and ensure product testing, at every stage of the supply chain, right from procurement.
In addition, food companies can leverage Artificial Intelligence to make better and more accurate forecasts of their requirements, resulting in lower food wastage, better pricing and better inventory management. For instance, food companies can update their inventory needs by taking simple photo of products needs, reducing time taken to send orders. AI-based image recognition technologies enable better and more efficient procurement of produce.
AI also helps in efficient and transparent tracking of produce from farm to the consumer, leading to increased confidence amongst consumers.
Ensuring Clean Food Processing Equipments: Artificial Intelligence based sensor systems can help in ensuring cleanliness and efficiency of food processing equipments. The benefits of such sensor systems range from increased savings on energy costs, and water, as well as reducing time needed to clean equipments. Such sensor systems integrate data to an artificial intelligence programme that screen the amount of food produce and microbes placed in the equipment.
Anticipating Consumer Preferences: Food manufacturers can adopt new artificial intelligence-based solutions that enable them to clearly anticipate and model the flavour preferences of their target consumers, and predicting their response to such new tastes.
Such Artificial Intelligence-based predictive analytics will help food manufacturers in developing new food products that are closely aligned with consumer tastes and preferences.
Some of the front-end or consumer facing applications of Artificial Intelligence include the following:
Food Discovery:
Artificial Intelligence-based food discovery and recommendation engines can help consumers make informed choices on what to eat and what not to eat through applications that learn about consumer’s food preferences and requirements.
Apps and Chatbots: By leveraging Artificial Intelligence-based Virtual Assistants, food restaurants can ensure that customers do not need to wait endlessly before placing orders, or making queries. The process is simplified, and contributes to better customer experience.
Self-Ordering AI-based Kiosks: Artificial Intelligence-based self ordering machines can contribute to enhanced customer experience by reducing their waiting time, and the need to stand in line for making payment. Such machines can take consumer order, and enable them to make payments directly without human assistance through integrated card readers.
Robots: In restaurants, robots are making an appearance and enhancing the speed and capacity of food preparation as well as shortening the time for food delivery.
Barriers to Adoption
Despite so many benefits, Artificial Intelligence uptake in food industry continues to be low.
Cost: One major limiting factor pertains to the cost of AI deployment. As a result, AI usage has been limited to large food chains and large food companies.
Cultural Challenges: One of the biggest challenges for food companies to embrace AI relates to organizational culture and trust, and adapting to change management. The process of digital transformation is slow and tough, leading to companies getting detested from embracing AI.
Fear of the Unknown: It is still early days to know the true value that Artificial Intelligence can deliver, making companies hesitate in investing early in the technology cycle.