For years, packaged food companies and the agricultural manufacturers they work with have used AI to increase crop yields and create more desirable food formulations for consumers. Today, the food manufacturing industry has new AI tools to increase productivity on farms and factories.
This type of generation AI allows food companies to combine different information, such as global tariff alerts, predicting the outbreak of fungi that may require pesticides, or strong winds that may affect moisture levels, and using that data can make more informed decisions about cultivation and purchasing key ingredients.
According to the 2024 McKinsey & Company report, the global food production industry, worth an estimated $4 trillion, could generate $250 billion in annual profits from AI productivity potential. According to the UN Food and Agriculture Organization, if global food commodity prices rise to the highest levels in the two years of July, these potential savings from improving operational efficiency in more targeted labor and manufacturing will come at a critical time.
For effective implementation, leaders need to fight the way AI is applied to complex agricultural systems. The challenges include uniformly organizing data across recruit engineers, software developers, data experts and supply chains, and evenly organizing data from limited resources to farmers and large national retail chains, according to a McKinsey & Company report.
Despite these challenges, leading food manufacturers such as Lake Landor, PepsiCo and Cargill, a global agricultural service provider, are implementing AI to improve farm yields, increase productivity for food manufacturing factory workers, and ensure product delivery such as the expected retailer demand for butter, milk and protein cereal conferences.
Cargill's AI Tools Make Delivery to Walmart More Efficient
Cargill uses an AI computer vision tool called Carve. This detects how much beef a company worker removes from the corpses of a particular animal, said Jennifer Hartsock, the company's chief information and digital officer.
If there's too much meat left, Curve flags it and shares those insights with Cargill's shift manager.
“It's a very expensive item in the market and we don't want to send waste down streams and out of the back of the factory,” Hartsock told Business Insider. Damage to meat increases more wasted supply chains and costs, especially for Cargill and consumers, especially when ground beef prices have recently reached record highs.
Further down the supply chain, Walmart is sharing sales data with Cargill, Hartstock said. Cargill then uses AI to analyze the data and generate production recommendations. If there is a demand for foods like ground beef or London grilled, for example, the Cargill factory can quickly adjust plans to keep the shelves full, avoiding expensive surplus.
AI helps land O'Lakes plans for spikes in dairy demand
This year, Land O'Lakes operates both the farm business and the dairy business, but has partnered with Microsoft to debut the Generation AI Tool. Agriculturalists can use this tool to help farmers make more data-based decisions about crop production and soil management.
According to the company, farm experts can enter details about the farm they are visiting, including the farm they are visiting (such as the time of year, type and amount of soil used, crop maturation, etc.), and get AI-generated suggestions to increase productivity without increasing costs for a particular farm.
Another application of AI includes forecasting demand for the company's dairy business. Land O'Lakes works with nearly 1,300 dairy producers across the United States. These farm cows produce milk at a consistent level throughout the year, but on holidays like Christmas, there is a demand for land-o-lake dairy products like Butter Peak. This creates an imbalance between food production and sales, said Teddy Bekele, chief technology officer at Lando Lakes.
“You can't go to the cows and say, 'It's time for the game, let's produce as much as possible,'” Bekele said. “They're going to do the same thing every day.”
To predict fluctuations in demand for these types, Landoake uses AI to use AI to demand large quantities of Landoakes branded butter, or if the company needs to focus on selling milk at retail stores.
Predictive AI helped PepsiCo create new, high protein oats
For the past two years, Pepsico has used AI's predictive capabilities to help create new oat types that contain more protein. This allows the company to develop and sell quaker oats that protein-hungry consumers are increasingly looking for.
Using AI in this way has environmental consequences as well. Before growing oats, where protein is naturally high, PepsiCo raises protein levels in oat crops with whey, a milk by-product that usually produces a higher environmental footprint than standard OATs.
He added that the AI algorithms will help Pepsico predict two parental lines of plants to create varieties that use less water and land and require less fertilizer or agricultural chemicals compared to previous generations of those plants.
