How AI is Reducing Waste in the Food and Grocery Sector

General interest in AI is soaring due to the availability of ChatGPT and the novelty of it answering questions in a human-like manner.

Despite common misconceptions, AI has been around for 40 years. Leading food and beverage companies are already adopting AI to improve operations, innovate new products and get closer to consumers based on conclusions that come from large dataset analysis.

For example, Campbell Soup’s innovation pipeline is informed by AI, analysing billions of data points to produce spicy versions of old favourites[1]. Kraft Heinz and PepsiCo predict market trends with AI modelling to design and develop innovative new products. ShopperAI, a tech company specialising in shopper behaviour recognition uncovers in-store data blind spots, recommending shelf rearrangement so snack multipacks are merchandised in one place, resulting in an 18% increase in revenue[2].

Reducing food waste with AI

An area where AI has made inroads is in reducing food loss. Harvard’s Nutrition Source[3] 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. In grocery retail, food loss due to spoilage can be curbed by using AI to track expiry dates and monitor the shelf-life of products. AI can optimize inventory management, which goes a long way toward eliminating waste since 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 is AI accessible for food and grocery?

Loyalty programs, point-of-sale systems and e-commerce means millions of data points are collected daily by key players in grocery on consumers, enabling data-driven decisions and informing stock replenishment. For smaller food & beverage companies, AI applications exist. Tastewise’s TasteGPT, whose dataset includes food social media, consumer preferences and trending flavour profiles are ready to tap into without needing vast learning algorithms. The similarity search function in Centric PLM and integration with PIM systems reduces guesswork leading to more fact-based decisions for a fraction of the cost of generative AI.

Unlock powerful, AI-driven technology

 AI’s powerful search capabilities go beyond exact user inputs — often requiring precise wording or specific ingredient numbers — and can identify formulations with similar ingredients that might not have been flagged otherwise. Now, imagine being able to instantly retrieve all formulas containing any type of corn starch from tens of thousands of formulations, saving both time and effort.

Centric Software offers cutting-edge AI-driven solutions for planning, merchandising and product teams, revolutionising product lifecycle management from pre-season planning to in-season execution and beyond. By augmenting AI with human intelligence, PLM teams are empowered to navigate the future confidently.

Get more insights on AI for the food and grocery industry in the eBook, How AI is Reducing Risk, Saving Time and Boosting Innovation in Food & Grocery. Discover AI’s impact on the industry: from usage by leading F&B companies and practical applications to its role in saving time, optimising costs, reducing risk and ways to integrate it through Product Lifecycle Management (PLM).

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[1] Dale Buss, “AI Advances in Product Development,” December 5, 2023, www.ift.org

[2] Richard Kestenbaum, “Artificial Intelligence Is Already Taking Over Grocery Stores,” September 27, 2023, www.forbes.com

[3] https://www.hsph.harvard.edu/

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