• Project No. and Title: WERA72 - Agribusiness Scholarship Emphasizing Competitiveness
• Dates: 06/03/2026 to 06/04/2026
• Contacts: [Tanner McCarty]

This authorizes the annual meeting: .
The meeting will be held on 06/03/2026 at Utah State University, Agricultural Science Building room 437, Logan Utah. :

Admin Advisor: Eric Belasco (eric.belasco@montana.edu)

Location: Utah State University, Agricultural Science Building room 437, Logan Utah<br /> <br /> Adress: 4800 Old Main Hill, Logan, UT 84322<br /> <br /> Topic Overview<br /> Artificial intelligence (AI) is rapidly transforming how agribusiness firms operate, how knowledge is generated and disseminated, and how students are trained for careers across the food and agricultural system. From precision decision-making and supply chain optimization to curriculum design and extension delivery, AI generally and generative AI specifically presents both significant opportunities and important challenges.<br /> This call for proposals invites scholars, educators, extension professionals, and industry practitioners to explore how AI is reshaping agribusiness teaching, extension, and industry practice. We welcome conceptual, empirical, pedagogical, and applied contributions that examine AI’s role, and particularly generative AI’s role, in improving decision-making, productivity, learning outcomes, and stakeholder engagement across the agribusiness sector.<br /> <br /> Suggested Topic Areas<br /> The following suggest some potential topic areas but any proposal that explores artificial intelligence and its impact on agribusiness will be considered:<br /> 1. AI in Agribusiness Education and Curriculum Design<br /> • Use of AI tools in undergraduate and graduate agribusiness instruction<br /> • Implications of AI for skill development, experiential learning, and workforce readiness<br /> • Challenges related to academic integrity, ethics, and student reliance on AI<br /> 2. AI-Enabled Extension and Knowledge Transfer<br /> • Applications of AI in extension programming, outreach, and advisory services<br /> • Decision support tools for farmers, agribusiness managers, and rural stakeholders<br /> • Barriers to adoption and trust in AI-driven extension tools<br /> 3. AI Adoption and Decision-Making in Agribusiness Firms<br /> • Use of AI for strategy and management decisions<br /> • Firm-level adoption decisions, costs, and returns to AI investments<br /> • Case studies of AI implementation in agribusiness supply chains<br /> 4. Data, Analytics, and Competitive Advantage in Agribusiness<br /> • AI-driven analytics as a source of competitive advantage<br /> • Integration of AI with farm-level, market, and consumer data<br /> • Implications for market structure and industry concentration<br /> 5. Workforce, Organizational, and Equity Implications of AI<br /> • Effects of AI on labor demand, job design, and skill requirements<br /> • Organizational change and management challenges associated with AI adoption<br /> • Distributional impacts of AI across firm sizes, regions, and producer groups