A way to tackle the “wicked problem” of food waste

The global market for artificial intelligence is worth about $235 billion, and it is projected to grow to over $631 billion by 2028. Also, the Artificial Intelligence (AI) in FoodTech is projected to increase from $6.38 billion in 2024 to $27.73 billion by 2029, and North America is the biggest regional market in 2024. The report shows a consistent growth in global start-up funding of about $304 billion in 2023 to a significant leap to $314 billion in 2024, with AI over $100 billion in AI-related companies. Examining the U.S. within a broader international context, this article argues that AI has the potential to strengthen food security worldwide, hence reducing food waste from farm to table. The introduction of AI into the food industry would create a significant opportunity to address food waste management and sustainable business. 

Introduction

In 1973, Horst Rittel and Melvin Webber introduced the concept of “wicked problem” to describe the complexity of social problems that are difficult to solve due to a lack of clarity in definition, contradiction, and a one-size-fits-all solution.⁵ The global food waste seems to have similar characteristics of complexity, definitive articulation, and known straitjacket solutions. The advent of Artificial Intelligence (AI) promises innovative ways to tackle the food waste problem by supporting agricultural activities, the food supply chain, and consumer food management. In 2024, USDA/NIFA invested $8.9 million in data science and $100 million in AI research, all projects that will combine data science and AI to combat food waste & loss. The US National Institute of Food and Agriculture & NSF have invested $220 million in an AI research institute to support agriculture, supply chain, and food waste reduction. 

The consistent investment in Artificial Intelligence (AI) is gradually transforming the food industry across the globe. An AI-driven commercial solution like Winnow has helped reduce food waste by 30% after upgrading to computer vision.¹¹ AI enables technological systems to observe their environment, process the acquired data, and identify strategies for execution.⁶ The AgFunder Report 2024 found that global investment in agri-food technology surpassed $32 billion, with AI-focused solutions claiming a growing share of that capital. 

AI investment trend and case studies 

According to Deloitte, the food industry is investing in AI, which is transforming restaurant waste management and reinforcing the executive's belief in Artificial Intelligence as a way to transform work processes. Chef Robotics raised a $43 million fund to support an AI-enabled robotic meal plant to increase productivity and reduce manual labor shortages. Grubmarket secured about $50 million to build AI for the $1 trillion food distribution industry. Created GrubAssist, a voice-activated AI assistant that works on mobile devices and can get information and place orders right online in real time. Leanpath has saved over 150 million meals from waste, avoided over 400,000 metric tons of greenhouse gas, and saved 50 billion gallons of water.  

Case study 1: Metafoodx is using 3D AI cameras to reduce food waste 

Metafoodx has secured $9.4 million in funding to combat food waste, with a focus on driving sustainability by using advanced AI innovation to track food in commercial kitchens. A technology that can view the end-to-end kitchen activities, from food preparation to consumption and leftovers, using 3D AI cameras and scanner devices. Metafoodx devices are data-driven, ensuring proper production planning, ordering optimizations, and have recorded a significant reduction in temperature-related food waste.  Metafoodx tracker shows 95% accuracy in identifying food menu, with a bid to identify the consumption, and identify leftovers, which will help track cost and waste management in the kitchen. Pomona College's kitchen reduced overproduction by 54% and the food waste decreased by one-fifth after adopting Metafoodx devices. In 2022, Guckenheimer cut food waste by 64%, and also saved over $1 million in food costs annually by leveraging an AI-driven tracker. The result highlights the ability of technology to manage waste and propel business financial performance

Case study 2: Orbisk uses advanced AI to create a smart kitchen

Orbisk is using advanced AI and image recognition to identify waste quantity, creating a smart commercial kitchen, and helping reduce food waste. Orbisk raised EUR8 million in Series A venture capital, aiming to fight food waste and generate a return on investment. An automated commercial kitchen features an “orbi device” that allows staff to hold waste under the camera to measure how much is discarded. In 2024, the company successfully deployed about 1000 Orbi devices in over 40 countries worldwide, saving 1.9 million kilos of food. Example: Accor Group, which is a major player in the hospitality business, was able to save 22% of food in its first year and expects to cut food waste by 50% within two years. This demonstrates the scalability of AI-driven solutions in commercial kitchens, colleges, universities, and hotels, aiming to halve food waste by 2030.

Artificial Intelligence impacts on food system efficiency 

Agriculture sector

The investment value of generative AI in agriculture in 2024 is valued at USD 227.40 million and is projected to reach USD 2,705.7 million by 2034. AI-powered precision agriculture has the potential to transform food production worldwide. Adoption of AI in the farm environment helps to predict weather, rainfall, or possible natural disasters, and where fertilizer is needed, which will help farmers make data-driven decisions. The report shows that about 20%-40% of agricultural produce never makes it out of the farm due to the effects of pests and crop diseases. In the U.S., predictive analytics, sensors, and drones enable farmers to optimize the use of pesticides, water, and fertilizer, leading to both cost savings and environmental benefits.⁹ AI in the farm will help detect early signs of infection, which will prompt a response, hence saving food loss.³ The use of AI on the farm will help improve global farm yield, enhance the supply chain, and reduce food waste.¹⁰

In India, AI-driven advisory apps such as Hungrify, which helps rescue food surplus from groceries and restaurants, and Famveg, which helps deliver farm-fresh produce to larger populations. Going forward, a larger number of farmers will adopt AI-driven technologies in their farm processes to increase efficiency and productivity. 

Supply chain activities

Supply chain in the food industry is getting food from one point to the other, either distribution or redistribution, can always be enhanced with the introduction of AI. Anytime the supply chain process is broken, it will affect how and when food gets to consumers and largely result in delay and possible decay in food items. AI-driven inventory management helps optimize stock levels, improve the supply chain, and possibly reduce food waste. Research shows that about 40% of supply chain businesses are investing in GenAI, and the numbers will increase in the future.

Reducing food waste

Food waste costs the retail, restaurant, and hospitality sector about $100 billion every year. According to the ReFED 2025 US Food Waste Report, businesses lost about $108 billion in revenue attributed to food waste. This wicked problem of food waste, therefore, requires more investment in Artificial Intelligence (AI) and strategic deployment in the food industry. AI is a better way to cut down on food waste because it can make farming more efficient, improve inventory management, and encourage responsible consumer behavior through predictive analytics and personalized applications.¹ 

An analysis of case studies, including AI-driven solutions from Shelf Engine and Afresh, demonstrates that food waste per shop has gone down by 14.8%, which means CO₂ emissions have reduced by 26,705 tons. IKEA also used AI-powered monitoring to cut kitchen food waste by 30% in only one year.⁷ Generally, when food waste is reduced, society conserves the associated resources, which include energy, water, and human hours.²

In Japan, the new technologies, AI-powered apps that utilize smartphone photos, help to predict food freshness. Also, help families cut down on waste by determining the safety of food without opening the packaging. In Europe, food expenditures make up 30% to 50% of a restaurant's operational costs. The AI platforms like ClearCOGS and Restoke.ai help restaurants buy the right amount of food, keep track of it, and lower the costs. 

AI impact on the food industry and sustainability

The chart below is extracted from the AI in Food Tech report by Market.us, which suggests a continuous growth rate of 29.3% (CAGR) in the global AI market. The adoption of AI is expected to have a significant impact on the food industry in 2025, and more investment is expected to reach USD 62.6 billion by 2033. 

Source: https://www.market.us (AI in Foodtech Market, June 2024)

Conclusion

This article reviewed the trajectory of AI investment, performance, and the future of food waste management. The adoption of Artificial Intelligence (AI) food industry seems to offer hope and opportunity to tackle the complexity of the “wicked problem” of global food waste right from farm to table. However, realizing these benefits requires coordinated policy action and strong public–private partnerships to ensure equitable access, ethical deployment, and measurable impact. Continuous investment in artificial intelligence (AI) will present great opportunities for both corporate businesses and individual kitchens. It helps create a smarter, more efficient, and sustainable global food system, as well as effective food waste management. AI has demonstrated a positive impact on farm yields, resource management, and food waste reduction from farm to automated kitchens. This review shows that to achieve a substantial cut in food waste, the global community should continue AI-investment, the trajectory in agriculture, supply chain, and the consumer level. 

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