AWARENESS STATUS AND PERCEIVE SOCIETAL EFFECTS OF ARTIFICIAL INTELLIGENCE IN AGRICULTURE BY FARMERS, EXTENSION AGENTS AND LECTURERS IN AKWA IBOM STATE, NIGERIA

Abstract

This study examined the awareness status and perceived societal effects of Artificial Intelligence (AI) in agriculture among farmers, extension agents, and lecturers in Akwa Ibom State, Nigeria. Two research questions guided the study. One hypothesis was formulated and tested at .05 level of significance. The design of the study was a descriptive survey. Using a multi-stage sampling technique, the study selected 319 respondents (123 farmers, 56 extension agents, and 140 lecturers) from three agricultural zones (Uyo, Eket, and Ikot Ekpene). Data were collected through structured questionnaires assessing socio-demographic characteristics, awareness of AI technologies (e.g., drones, precision farming tools, decision-support systems), and perceptions of AI’s societal effects using a 4-point Likert scale (1 = Strongly Disagree, 4 = Strongly Agree). Descriptive statistics (frequencies, percentages, mean scores) and inferential statistics (Analysis of Variance, ANOVA) were employed for data analysis, with post-hoc tests conducted to identify group differences. Results revealed significant disparities in AI awareness, with lecturers (92.1%) and extension agents (89.3%) demonstrating higher familiarity than farmers (58.5%). Perceptions of AI’s societal effects varied markedly: farmers expressed concerns about job displacement (mean = 2.08) and cultural misalignment (mean = 1.92), while lecturers emphasized productivity benefits (mean = 3.85) and overall positive impact (mean = 3.71). ANOVA results confirmed significant differences (p < 0.05) across all societal effect dimensions, rejecting the hypothesis of no differences among stakeholders. The study concludes that AI adoption in Akwa Ibom’s agricultural sector requires stakeholder-specific strategies addressing farmers’ socio-cultural concerns while leveraging extension agents and lecturers as change agents. Recommendations include targeted farmer education, strengthened extension services, and inclusive innovation platforms to ensure equitable and culturally sensitive AI integration.