This study investigated the role of Artificial Intelligence (AI) in agricultural extension for enhancing sustainable livelihoods among rural farmers in Abuja, Nigeria. Using a multi-stage sampling technique, data were collected from 200 respondents across five area councils. The socio-economic analysis revealed that 69% of farmers were male, with a mean age of 42.5 years and an average farm size of 2.1 hectares, and 42% reported access to extension agents. Findings on the role of AI tools indicated generally favourable responses, with the highest mean score recorded for "AI helps in making better farming decisions" (Mean = 3.13) and "AI improves weather-based planning" (Mean = 2.92). However, some skepticism remained, with lower mean scores reported for statements such as “AI tools reduce dependency on extension agents” (Mean = 2.37) and “AI optimizes resource use” (Mean = 2.35). Multiple regression analysis showed that age (p = 0.004), farming experience (p = 0.005), education (p = 0.021), cooperative membership (p = 0.028), contact with extension agents (p = 0.013), gender (p = 0.053) and farm size (p = 0.055) were significant predictors of AI adoption. Marital status was not significant (p = 0.289). Barriers to adoption were ranked using Kendall’s Coefficient of Concordance (W = 0.78), with the top constraints being limited internet access (Mean Rank = 6.62), low digital literacy (5.86), and high device cost (5.74). The study concludes that while AI holds promise, its integration is shaped by socio-technical, infrastructural, and institutional factors.
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Olawumi et al. (2025) studied this question.