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Though Artificial Intelligence (AI) technologies have supported industries in multiple ways, the key is to identify areas specific to each industry where AI solutions are the most relevant. In the case of the food industry, solving operational efficiencies seems to be the area where AI-based solutions can make the maximum impact. And no wonder, with the relatively short timelines that food can be stored before consumption, make this an understandable challenge.
AI or machine learning relies a lot on historic data and uses this information to make predictive solutions or suggestions that can help in foreseeing certain outcomes. The more data at hand, the more closer to accuracy the solution / suggestion is. Considering this, here are the potential avenues for the use of AI in food business in ways that could transform conventional modes of operation by increasing efficiencies and production, predicting, assessing and accurately solving more market demands and more.
Forecasting
Companies have used AI to determine and analyse demand variations, shopping trends during marketing campaigns and sales drops. Stored data for these variables helps machines identify problem areas and solve for them specifically. It answers questions like – what is the optimal shelf space for this product to ensure increased sales? Which categories perform best for a specific type of promotion? How much should a certain product be stocked during peak/low sales periods? This helps optimise processes and reduce wastes through AI’s intelligent data-back prediction systems.
Boosting Productivity
Cloud computing technology, Big Data analytics and data-driven machine learning has equipped a lot of industries to streamline their operational efficiencies. In the case of food industries, the manufacturing arm in particular, AI assists in aiding the production processed by making certain decisions easier through its predictive features. These real-time solutions can potentially save a lot in time and moolah. These cost benefits will in turn be reflected in market satisfaction through pricing.
Automation
Technology’s increased agility in handling fragile produce helps in automating manufacturing tasks in the food industry’s operational chain. This means, tools have become advanced enough to handle delicate food items and process them without damaging them, such as eggs or tomatoes.
Not only this, but automation helps in reducing manual effort in repetitive tasks therefore adding time efficiency. This is especially useful for tasks where is lower decision-making potential.
Consumer Preferences
Through AI’s capability to handle large amounts of data with multiple variables and therefore make accurate predictions, consumer preferences can be assessed through their older buying / consuming patterns. Not only does this help in the development of newer products and services but also capitalize on the key sale-drivers with eagle-eyed consistent focus.
Applications
Some ways to apply AI or machine learning in these industries would be through smartphone apps that fit into the consumer’s lifestyle, such as fitness apps, food suggestion apps based for certain body types etc. Chatbots for online food partners could be another potential application. Quick food manufacturing machines independent of human assistance is another use case.
Conclusion
What this means for the food industry is that there is a constant need to keep an eye on AI trends and the way it is affecting businesses. Choosing the right AI tool for a certain business is a sure-shot way of intelligently increasing efficiencies and reducing costs. There are many more upcoming AI solutions in the market – keep your eyes on the radar to assess the best solution for your business!

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