AI-BASED MARKET INTELLIGENCE AND PRICE PREDICTION FOR AGRICULTURAL PRODUCE

*Catherine Mueni Peter1, Dr. Supriya1, Dr. Joginder Singh2 and Dr. Mwenjeri G. W.3

Abstract: Market intelligence software gathers and processes information on demand, supply, competition and customers to help managers, farmers and other stakeholders in the value chain of agriculture. When such software is combined with artificial intelligence (AI) it becomes well-suited for predicting market movement and price fluctuation of farm produce. This integration encourages market orientation and enables stakeholders to identify opportunities and make strategic choices about what, when, where and how to produce, overcoming limitations associated with conventional pricing models and forecasting such as overlooking the impact of weather uncertainty, evolving consumer preferences, global trade shocks and policy actions. Artificial intelligence techniques of machine learning, deep learning, and natural language processing facilitate the use of diverse datasets such as satellite imagery, transaction records, logistics data and digital signals with forecasting models. There are, however, challenges to this, particularly related to data quality, digital divides, algorithmic discrimination and implementation costs-barriers that are heavily experienced in developing countries, thus its implementation requires intentional investment in digital infrastructure, collective approaches and facilitative policies that ensure inclusivity and equitable access.

Also available via: European Organization for Nuclear Research