AI in Agriculture: Paving the Way Towards a Sustainable Food Future
The world is facing a significant challenge—feeding a population of 10 billion people by 2050 in a sustainable manner. Current agricultural practices are unsustainable, contributing to 11% of global emissions, while water, land, and biodiversity are declining rapidly, and over 800 million people suffer from hunger. However, the application of Artificial Intelligence (AI) in the food system is emerging as a promising solution to address these complex issues.
AI, particularly vertical AI, which is specialized and deeply understands a single industry, holds vast potential in transforming the food system. While the technology has already been successfully utilized in financial markets and cancer treatments, its application to agriculture offers new hope for creating a more abundant and sustainable future.
Several innovative companies have started applying AI to various aspects of the food system, paving the way for positive change. For instance, India-based Cropin leverages machine learning to help farmers monitor the health and biodiversity of crop varieties, track weather cycles, predict yields, and assess soil health and water stress. Similarly, Chirrup tracks bird populations on farms in the UK countryside, serving as an indicator of biodiversity.
Food insecurity is a critical concern, especially during natural disasters, economic shocks, or conflicts. AI enables organizations to interpret large amounts of data in real-time to predict hunger and ensure efficient food distribution. Companies like San Francisco-based Replate use AI to optimize food distribution, redirecting surplus food to nonprofits while considering nutritional value, dietary needs, and demographics of recipients.
Food waste is another pressing issue, with nearly 40% of food wasted in the United States. AI can help track food from farm to plate, assisting farmers, retailers, restaurants, and food banks to ensure timely harvest and consumption. Aibono, for example, predicts farmers’ yields and suggests optimal harvest windows based on retailer data, minimizing spoilage.
Improving farmer livelihoods is crucial for ensuring food security, as many farmers face financial challenges. AI can connect farmers to markets, predict yields, reduce waste, and help with crop pricing, enhancing farm profitability.
Antibiotic resistance is a looming threat, with overuse in animal agriculture being a major factor. Companies like myAnIML and Serket employ computer vision to detect illness in livestock, allowing farmers to treat sickness promptly and minimize antibiotic use.
Aquaculture offers a sustainable solution to diminishing ocean resources, but it requires careful monitoring. AI and machine learning can help in monitoring the health and weight of fish and the quality of their environment in both offshore and land-based fish farming.
AI has the advantage of navigating the complex web of information in the food chain, from farming to food distribution, enabling higher-quality decision-making at every step. Entrepreneurs are encouraged to address agricultural challenges using AI as a tool, ensuring sustainability remains a core focus.
By using machine learning, computer vision, and predictive analysis, AI can break down complex issues into manageable solutions, making food production and distribution more efficient. The continuous emergence of new AI-driven companies in the agricultural sector promises a hopeful future for tackling global food challenges.
Written by Carole Wilay ’25