AI upgrades the food industry

AI helps improve food productivity

The use of artificial intelligence (AI) tools to develop more efficient predictive models in food safety could revolutionize the industry, reducing food waste and generating up to 127 billion dollars annually by 2030, according to McKinsey & Company.

​

AI for food production

​

The report highlights that from the first moon landing to food products on store shelves, the Hazard Analysis and Critical Control Points (HACCP) system has been essential for ensuring food safety. Now, 55 years later, AI is transforming the quality control paradigm from reactive and corrective to predictive.

​

"What used to take months with a traditional approach now only takes a few days with AI tools like ChatGPT or Google’s AI Studio," says Ing. Pablo Barbuto, expert in Food Safety and Quality and professor of Quality Management at the National University of Luján. He adds that AI's ability to collect vast amounts of relevant information makes the HACCP system much more effective.

​

Currently, the AI market in the food and beverage industry is valued at 9.68 billion dollars, and it is expected to reach 48.99 billion dollars by 2029, although its application in Argentina remains limited, according to Mordor Intelligence. This underscores the importance of professionalization and training in the sector in new technologies.

​

​

​

​

​

​

​

​

​

​

​

​

​

​

"Training AI tools allows us to shift from the traditional model of waiting for a finished product to collect samples and analyze parameters to obtaining real-time information at every stage of the production process, predicting food quality and acting accordingly. The savings in time and resources are immense, as is the ability to protect the consumer," Barbuto explains.​​​​​

​

Managing resources with AI

​

Moving toward predictive models is crucial for saving resources and achieving potential economic gains, as already demonstrated globally. Anticipating risks and critical control points based on a vast network of data can reduce food waste, saving up to 127 billion dollars annually by 2030.

​

The automation of processes through AI can increase productivity by reducing waiting times and repetitive tasks, allowing human talent to focus on key activities. "For example, with a system of sensors that measure variables like temperature, pressure, and flow in real-time, it’s possible to predict the quality and safety of a finished product, taking actions in advance and avoiding the loss or reprocessing of entire batches of food," illustrates Barbuto.

​

Estimates indicate that the implementation of AI in food processing could generate returns of up to 150 billion dollars, improving sales, productivity, and operational efficiency.