The paper explores the application of artificial intelligence (AI) technologies in addressing digital divide challenges and enhancing socio-economic equity in Uganda. The digital divide, characterized by disparities in access to digital resources, internet connectivity, and digital literacy, significantly impacts socio-economic development. This research focuses on AI technologies such as machine learning, image recognition, natural language processing (NLP), and GIS-integrated AI, which are mildly actively used in Uganda’s agricultural sector. Studies have shown that digital technologies can address key challenges in agriculture, such as access to extension services, marketing systems, and financial inclusion. For example, mobile money has significantly increased financial inclusion among Uganda's unbanked populations, including women, youth, and rural households. However, barriers such as low digital literacy, limited smartphone ownership, and inadequate internet access hinder the adoption of these technologies, especially among disadvantaged groups. Therefore, while digital innovations have the potential to improve productivity and inclusiveness in agriculture, their limited use could exacerbate existing inequalities by leaving behind those who cannot easily access or afford these technologies. Leveraging these technologies, the study examines how they contribute to improving crop yield predictions, pest and disease management, and precision agriculture. Through the analysis of initiatives undertaken by the National Agricultural Research Organization (NARO), including the use of AI-driven image recognition for plant disease identification and NLP for farmer support systems, highlighting the practical applications and benefits. The findings emphasize the critical infrastructure requirements, ethical considerations, and potential challenges in deploying AI solutions in low-resource communities [9]. Ultimately this research aims to provide a comprehensive framework for utilizing AI to foster digital inclusivity and promote socio-economic growth in developing regions, using Uganda as a case study