They say a wave of technological innovations is mopping up jobs around the world, but have you considered the use of AI in food supply chain? The possibilities of using predictive analytics agriculture to estimate annual global crop yields, despite the recent onslaught of climate change. Imagine the benefits of smart food supply chains that can detect spoiled shipments long before a sealiner berths.
The global food supply chain is so complex and vast that conventional appropriation will leave loopholes and cause significant food waste. With the existing initiatives, the FAO affirms that the global food chain has been bleeding about 30% of its annual supply to waste.
AI in food supply chain is unveiling a new vista of predictability and food inventory management. The interplay between artificial intelligence and the food industry may be the solution to major challenges plaguing the global food system. Permit us to walk you through some ways AI-driven logistics and predictive analytics in food supply could reduce waste and improve food safety.
Demand Forecasting and Inventory Optimization
A transcontinental and interdisciplinary study from 2023 identified the major bottlenecks in the global food supply chain as solvable with AI. The team of researchers concluded that AI logistics food and predictive analytics agriculture can help stakeholders get a step ahead of disruptions causing global food insecurity. In mugglespeak, this means artificial intelligence can be trained to identify patterns that will help transform the global food system into smart food supply chains.
Before now, some sections of the global food system experienced a glut that made produce very cheap, and a lot of it went to waste. On the contrary, some other sections experience shortages. The disconnect between food demand and supply can be addressed by trying out the possibilities of AI in food supply chain.
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Quality Control and Food Safety
Big data analytics, machine learning and artificial intelligence are continually making food safety and quality control easier. Only a few decades back, some cola companies employed watchers. A personnel sit at a strategic location along the production line to identify filled cola bottles with defects and remove them. Today, such tasks are largely automated using AI-powered image recognition.
Similar technologies are being deployed to various sections of the food chain. For example, AI inventory management can help warehouses and logistics operators detect signs of contamination and spoilage early. Public health threats are averted, and the costs of consumer claims and product recalls are also eliminated.
Logistics and Route Optimization
Remember the technology that tells you the shortest route to drive through during the evening drive from work? AI in food supply chain is helping to cut the cost of logistics to the barest minimum. For example, AI logistics food is helping personnel determine the most efficient routes to supply destinations. This, in turn, cuts food delivery cost and time.
Some food logistics companies go a step further to collect data about the efficiency of their cold chain. Using sensors and data loggers, they monitor and track the vitals of food as it moves across the supply chain. This data can be reassuring to the end user of perishable food items. Similarly, it reduces waste and aids adherence to regulatory standards.
In 2022, the Food and Agriculture Organisation of the United Nations (FAO) collaborated with Wageningen University & Research. The outcome of this collaboration was a whitepaper on early warning tools and systems in food safety. That report revealed that food suppliers and regulators can deploy AI-powered systems to identify food safety threats. Such technological interventions make it possible to issue early alerts and recall the faulty products with minimal threat to public safety.
Sustainability Benefits of AI in the Food Supply Chain
Artificial intelligence and food distribution are seeing the emergence of new areas of synergy. For the global food supply chain to become sustainable, we need to cut all forms of wastage to a minimum. Food waste, energy inefficiencies, shortages and gluts are some of the problems that AI in food supply chain can solve.
AI reducing food waste could come in the form of real-time waste tracking, analyzing waste patterns, demand forecasting, or implementing best practices for food inventory management.
Each perishable food item has a peculiar temperature-driven deterioration pattern. So, to food storage or haulage systems can optimize energy consumption by tailoring temperature control to the product. A one-size-fits-all approach will either lead to early food spoilage or energy dissipation.
Case Studies
The deployment of AI in food supply chain is not a pipe dream or a claim of UFO sightings. The fact that systems like the ones we described have only been successfully deployed by Big Food is an indication that it is capital-intensive. So, new food startups may find it difficult to integrate such systems for their operations just yet. We shall look at some food initiatives already using AI to make the supply chain sustainable.
Walmart’s Blockchain-Based Traceability
In 2021, Walmart announced a massive partnership with IBM. The collaboration gave birth to a traceability blockchain system called Hyperledger Fabric. This system makes it possible for customers buying items like pork and mangoes from Walmart to trace the source within seconds.
Nestlé’s Use of AI for Supply Chain Optimization
Nestlé is not so much for transparency as for process optimization. So, the food giant is more particular with using AI to solve in-house inventory bottlenecks than to reassure customers. So, Nestlé mainly uses AI for logistics, inventory management and demand forecasting.
Carrefour’s Use of Blockchain for Transparency
Carrefour is a French multinational that specializes in retail and has stores in over 40 countries. Like Walmart, Carrefour utilizes blockchain technology to help customers trace the journey of food items from farms to the store. All the customer needs to do is scan a QR code on the product, and the information is made available to them in a user-friendly format.
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Challenges and Limitations
It is a no-brainer that deploying AI in food supply chain would cost a leg and an arm. Economies of scale may apply in the future; however, only food companies with a robust capital base can afford these innovative technologies.
There’s also the issue of data privacy. While making efforts to be transparent with customers about the origin of food, sensitive data leaks into the public domain. Not all farmers will want information about their crop yield in the public domain. Indeed, it may even be possible to harvest trade secrets from these AI-driven food innovations.
AI-driven innovations in the food industry are virgin ground. So, as stakeholders are acclamatizing with the benefits, it is important for them to be also aware of potential loopholes. It may take regulatory interventions to address these data- and ethics-related issues.
AI in the food supply chain can only make the system smarter, faster and more sustainable. Possibly, as research in artificial intelligence evolves and accompanying technologies become cheaper, more food concerns will key into the trend.
In the future, AI won’t just help move food — it will help feed the world smarter.
