Brainstorming and Prioritization
Following the exploratory discussions of Phase 2, the study advanced into a structured prioritization process designed to convert qualitative insights into clear, actionable focus areas for the Land-grant system.
Culture, Ethics, and Public Trust
- Be transparent and build public trust: Strengthen public con idence through openness about how AI is used in research and outreach.
- Ethical governance and safeguards: Develop clear frameworks to address misinformation, bias, and data integrity.
- Human-centric education: Use AI to handle routine tasks so faculty and agents can focus on high-impact, trust-based programming.
Capacity, Infrastructure, and Policy
- Train people: Provide targeted, practical AI training for faculty, researchers, Extension staff, and communities.
- Set clear rules: Establish shared policies for safe and responsible AI use across teaching, research, and Extension.
- Shared systems, resources, and infrastructure: Strengthen broadband, platforms, and shared data resources to support AI work in labs and in the field.
Strategic Readiness and Alignment
- Future-ready workforce: Build comprehensive AI training and workforce development plans, including reskilling for those affected by automation.
- Establishment of use cases and best practices: De ine and disseminate examples of how AI can be applied effectively and responsibly across the Land-grant mission areas.
- National strategy and collaboration: Pursue coordinated national initiatives and partnerships that blend trusted human expertise with AI tools to deliver reliable results
