Five recommendations guide how The Universities at Shady Grove builds AI readiness, supports student learning and career development, and expands collaboration among university and employer partners. The recommendations support USG’s mission to strengthen affordable educational pathways, career readiness, student success, and regional workforce development.
Throughout the recommendations, the principle of building on existing strengths and conducting assessments will guide teams as they consider technology purchases, custom development, and resourcing. USG will explore coordinating access to AI tools, services, and resources across partners, including consortium purchasing.
As we learn and innovate together around AI, watch this space for key updates, project initiatives and team contributions. Share your feedback or let us know you'd like to get involved at usg-execdirector@umd.edu.
AI Fluency and Responsible Use
Purpose: Prepare students, faculty, and staff to understand, evaluate, and use AI effectively and responsibly.
Recommendation: Develop an adaptable AI fluency framework supported by practical learning. Topics should include AI capabilities and limitations, verification of outputs, bias, appropriate disclosure, privacy, security, accessibility, and human oversight. Academic partners and units should adapt the framework to their disciplines and institutional requirements.
AI Faculty Champions
Purpose: Build faculty capacity to guide the thoughtful adoption of AI within academic disciplines.
Recommendation: Establish a network of interested faculty champions, supported through professional learning and peer collaboration. Champions could develop instructional examples, explore assessment, mentor colleagues, and connect classroom applications with employer needs. Employer engagement or faculty externships could inform this work where feasible. As an example of work USG can build upon, USM Generative AI Pedagogy Fellows Program, administered by the William E. Kirwan Center for Academic Innovation. The program focuses on AI literacy and Critical Thinking, AI for Active Learning, and AI for Accessibility and Inclusive Pedagogy.
AI-Enabled Learning and Career Support
Purpose: Expand access to academic and career support throughout the student journey.
Recommendation: Evaluate existing AI capabilities for learning assistance, career exploration, resume development, interview practice, and job discovery. Learning applications should meet guidelines for assistance as tools, not as a replacement for critical thinking and other core competencies. Evaluation should include instructional quality, accessibility, privacy, integration, cost, and referral to human support.
AI-Idea Lab and Shared Innovation Environment
Purpose: Create a shared environment that enables AI experimentation, collaboration, and innovation across USG, its university partners, and external partners.
Recommendation: Establish an AI Idea Lab for students, faculty, staff, university partners, employers, and community partners to explore and test AI applications. The model could include a secure AI sandbox for testing tools and applications; shared repositories, resources, and best practices; access to AI technologies and computing resources; and cross-institutional collaboration. Initial implementation should identify existing resources, determine gaps, establish appropriate governance and access requirements, and define how the environment can support academic, operational, and workforce-focused experimentation.
USG AI Applied Learning and Credential Pathway
Purpose: Create clearer, accessible routes to AI learning and workforce development
Recommendation: Develop a pathway that connects AI learning and credentials with applied learning. Inventory relevant AI courses and credentials offered by partner institutions and external providers. Assess their audiences, learning outcomes, costs, recognition, and connections to academic programs. As an example, USG Google NASH Career Certificates, through which students, faculty, and staff gain career-focused certificates and AI essentials.
Use the findings to identify gaps and opportunities to connect formal and non-credit learning with internships, capstones, employer-sponsored projects, hackathons, AI labs, career coaching, and other project-based learning. Where appropriate, employers and community partners could contribute authentic problems for multidisciplinary teams of students, faculty, and staff to address, including through USG's Industry Sector Hubs.
Any future stackable or credit-bearing offering should be developed with academic partners and proceed through applicable institutional approval processes.
Applied learning activities should define the problem or learning objective, expected deliverables, available support, and appropriate arrangements for data use and ownership of project outputs.