Dr. Nesma Osama Osman, PhD is an Assistant Professor in the Agricultural Economics and Social Science Department at Cairo University. She earned her Ph.D. in Agricultural, Leadership, and Community Education from Virginia Polytechnic Institute and State University in 2022. Dr. Osman has extensive experience in agricultural extension, program development and evaluation, community development, and technology integration in education. She has held academic and research positions at Mississippi State University and Virginia Tech, where she contributed to numerous nationally funded projects and taught both undergraduate and graduate courses. Her research and professional interests focus on agricultural education, participatory approaches, professional development, and promoting diversity, equity, and inclusion in community-based programs.

Towards the Integration of Generative AI into the Cooperative Extension Service: Insights for Guiding Professional Development Generative artificial intelligence (Gen AI) can enhance the efficiency, productivity and accessibility of Cooperative Extension Service’ (CES) work, yet empirically grounded guidance for its ethical and effective utilization remains limited. Guided by the Technology-Organization-Environment (TOE) framework, this study employed a three-round electronic Delphi technique involving six CES professionals experienced in Gen AI applications, to build consensus on CES-appropriate Gen AI tools, compatible Extension tasks, training and resource needs, barriers to utilization, and best practices. Within the technological context, Copilot, ChatGPT, and Gemini (Advanced) were identified as the most suitable Gen AI tools for Extension work. These tools were perceived as most effective in supporting audio-to-text and text-to-audio conversion, administrative writing tasks, and idea generation for research, Extension programming, and answering clientele questions. The organizational context revealed key barriers: limited ability to blend professional expertise with AI-generated content, low Gen AI/digital literacy, and concerns about overreliance on AI undermining critical thinking. Correspondingly, priority training and resource needs emphasized ethical AI use, evaluating the reliability of AI-generated content, distinguishing research-based information from AI outputs, prompt engineering, and institutional AI policy awareness. In the environmental context, the absence of clear AI policies and unclear accountability for AI-generated content emerged as critical constraints. Seven best practices, emphasizing ethical use, transparency, critical thinking, fact-checking, and effective prompting, were identified to guide responsible Gen AI utilization. The findings offer Extension leaders and educators evidence-based insights for designing Gen AI professional development and drafting AI policy guidelines that support responsible utilization, and advance organizational AI utilization literature.