Upskilling Farmers and Agri-Entrepreneurs Through Artificial Intelligence (AI) Technologies

Agriculture is a key sector of the global economy. In developing nations like India, 42% of the workforce is engaged in it, and it contributes 18% to the country's gross domestic product (GDP). However, the agricultural sector faces many challenges, including low productivity, land fragmentation, vulnerability to climate change, and limited market access. The adoption of artificial Intelligence (AI) technologies in agriculture can enable farmers and agri-entrepreneurs to increase output and cut costs. These technologies can bring increased profitability, sustainability, and production. However, for farmers and agri-entrepreneurs, digital illiteracy, limited access to technology and the internet, resistance to change, traditional mindsets, high costs of AI implementation, and a lack of standardized training programs are barriers to the use of AI applications. This review focuses on the challenges and opportunities faced by farmers and agri-entrepreneurs. This review used literature from the Scopus database, published between 2015 and 2025. Five empirical case studies from India, China, the Netherlands, and the United States were reviewed to highlight participatory approaches to AI training that improve yields, resource efficiency, and income. The findings reveal that workshops, mobile platforms, and mentoring programs can be effective in increasing the use of AI. There are also hurdles, in the form of digital infrastructure limitations, cultural resistance, and a lack of training curricula that are responsive to changing contexts. The study advocates the formation of partnerships among multiple stakeholders, along with policy reforms, to create large-scale AI upskilling programs that support agricultural transformation, food security, and job opportunities for people living in rural areas.