Individual Presentation: Designing AI Workforce Literacy for Food Systems: A Practical Blueprint for Smart, Accessible Training

Artificial Intelligence (AI) is rapidly becoming embedded in product development, food safety, supply chain management, sustainability analysis, and consumer engagement. However, most students and professionals in the food sector have not been systematically trained to understand, evaluate, and responsibly apply AI tools in their work. Without intentional AI literacy training models in office and on the manufacturing floor, organizations and corporations risk missed opportunities, poor implementation, and reduced trust in both technology and decision-making.This session presents a practical framework for designing AI workforce literacy programs tailored to the needs of the food sector. Rather than centering on a single course, the framework focuses on defining competency based learning outcomes that span AI fundamentals, data literacy, and applied use cases. Food specific scenarios—such as contamination prediction, process optimization, inventory and waste reduction, and consumer insight generation—are used to anchor concepts in real workflows. Ethics and governance topics, including data privacy, bias, transparency, and regulatory alignment, are woven throughout.An online AI Applications in Food Science and Industry course developed at Purdue University will be shared as a case example of this framework in action, illustrating design choices such as mobile friendly, asynchronous modules that support nontechnical and underserved learners. Early learner feedback highlights gains in confidence when discussing AI with colleagues, identifying appropriate use cases, and engaging productively with vendors and data teams. The session will conclude with concrete design strategies and templates that attendees can adapt to build or refine AI literacy initiatives in universities, companies, and professional organizations.