How AI is Improving Food Waste in the Food & Beverage Industry… and More!
Waste Not, Want Not
An area where AI has made inroads is in reducing food loss. Harvard’s Nutrition Source website defines food ‘loss’ as that occurring before the food reaches the consumer as a result of issues in the production, storage, processing, and distribution phases. Food ‘waste’ refers to food that is fit for consumption but then discarded at the retail or consumption phases.
At the retail level, food loss due to spoilage can be curbed by using AI to track expiry dates and monitor the shelf-life of products. AI can optimise inventory management, which goes a long way toward eliminating waste since the stores will better meet consumer demand, thereby reducing excess inventory and in turn, food waste. It is important to know what is on store shelves in real-time to plan if discounts need to be done to move goods nearing their sell-by date.
How to Bring AI into the Fold
Large amounts of data is a mainstay of generative AI and sometimes a barrier to entry for smaller companies. That is why industry-specific AI offers based on subscriptions are a way for all companies to take advantage of AI. There exist practical AI applications that can make a difference to food companies right now.
The Power of AI
AI’s powerful search capabilities beyond what users input—which often has to be exact wording, or exact ingredient numbers—can catch formulations with similar ingredients that would otherwise not have been flagged. Now imagine being able to call up all formulas in an instant that have some type of corn starch in them, from among tens of thousands of formulations, saving time and effort.
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For more details on AI’s use in food & beverage including: a brief rundown of how some companies are using AI, examples of practical applications that are already here, a look at the energy needed to run generative AI, how AI saves time/money, reduces compliance risk and ways to bring AI into your company through product lifecycle management (PLM).
