Statistical Analysis of Stakeholders Perception on Adoption of AI/ML in Sustainable Agricultural Practices in Rural Development

The integration of artificial intelligence (AI) and machine-learning (ML) techniques is swiftly revolutionizing global agriculture. These advanced technologies find applications across various domains, including automated monitoring of crops and livestock, as well as predictive analytics for precision agriculture. However, the perspective and assessment of stakeholders on the adaption of these technologies to agriculture have not been evaluated. Hence, a survey with 145 stakeholders from Shonga farms in Nigeria to gather their perspectives on the implementation of AI and ML was conducted. By analyzing their responses across 11 factors, it was found that there is positive support for adopting AI/ML in areas such as training, infrastructure, productivity and economic outcomes. However, some shortcomings in terms of resources, policy frameworks, sustainability measures, and equitable access were identified. The variation in responses highlights the challenges related to training and infrastructure that need to be addressed. To fully unlock the potential of these technologies in improving productivity, sustainability, economic viability, and community well-being at Shonga farms targeted investments and policy improvements are necessary. This empirical evidence provides insights, for applying emerging technologies to promote sustainable rural development while ensuring inclusivity.