Application of agentic artificial intelligence in autonomous decision making across food supply chains

Abstract

The food industry is responsible for the increase in greenhouse gases, pollution emissions, and energy consumption. Social demand for food security, human health, environmental, and sustainability is growing; however, given the challenge of providing food for a world population of approximately 10 billion people in 2050, the realization of “One Health” is far from obvious. Food systems are extremely complex. The establishment of quality standards involves the cooperation of several agents, and the realization of that cooperation typically occurs in a highly controlled environment. Moreover, food supply chains are subject to unexpected disruptions caused by non-market factors, including climatic phenomena and pandemics. Agentic Artificial Intelligence would play a role in the autonomous decision-making required for the action of agents and for agent interaction in food supply chains.

The continuous increase in the adoption of information and communication technologies in society has unleashed an avalanche of data. Big Data contains a wealth of information that is little used to enhance business productivity. Companies are beginning to combine the adoption of the Internet of Things with the increasing use of Artificial Intelligence tools to extract value from the data they collect. These tools are used to enhance the decision-making process. The AI already in practical use enhances decision-making. Agentic Artificial Intelligence is an extension of the concept of Artificial Intelligence based on three pillars: autonomy, intelligence, proactivity (agentic component). It goes further: it makes decisions autonomously, in the absence of the human principle. Moreover, it interacts with other AIs agents. The usefulness of Agentic Artificial Intelligence applied to Autonomous Decision Making in Food Supply Chains is analyzed.