Generative AI Readiness and Workforce Competencies in Agribusiness Infrastructure Delivery and Farm Operations

The rapid adoption of digital technologies into agribusiness operation systems has continued to draw attention towards the use of Generative Artificial Intelligence (GenAI) technologies to enhance day-to-day business operations, agribusiness infrastructure delivery and farm operations tasks. However, there are limited research works have been conducted to study organizational readiness, workforce digital skills and trust factors associated with GenAI adoption within agribusiness. This research study determined GenAI readiness and workforce digital skills among agribusiness professionals in infrastructure delivery and farm operations, and examined the moderating effects of GenAI trust on the relationship between workforce digital skills and GenAI adoption. This study employed a quantitative research methodology and distributed self-administered questionnaires among practicing professionals in the agribusiness infrastructure delivery and farm operation tasks. The study used Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyse the data using SmartPLS 4.0. The study findings showed that there is a very low GenAI readiness level among agribusiness operation system professionals. The results also demonstrated that workforce digital skills significantly determine GenAI adoption while Generative AI trust showed no statistically significant moderation on the relationship between workforce digital skills and GenAI adoption. This study advances Human Capital Theory by focusing on workforce capability towards technology adoption. Pedagogical Responses to Generative AI in Architecture Education in Southeast Nigeria Udochukwu Marcel-Okafor Architecture, Federal University of Technology, Owerri. Imo State, Nigeria umarcelokafor@gmail.com The emerging prominence of generative artificial intelligence (Gen AI) in architecture education, particularly studio-based learning spaces has disrupted existing learning patterns. In Nigeria, this shift presents conspicuous potentials as well as constraints influenced by local socio-economic settings, infrastructural limitations, and existing design practices. Consequently, this study sought to investigate how generative