Issue Statements


  1. Determining where AI adds real value: Experimentation with AI will give way to thoughtful evaluation of and investment in uses that help fulfill institutional missions
  2. Future-proofing students for a volatile world: Students need durable, transferable learning outcomes that emphasize how they think, adapt, and apply skills in a rapidly changing world
  3. Balancing cybersecurity boundaries with autonomy and trust: Security teams can build an institutional culture that values both clear and transparent security boundaries and individual responsibility and discretion
  4. Designing AI structures for responsible innovation: AI governance and management must balance clear guardrails, institutional values, and standards with spaces for autonomy and experimentation in how AI is adopted and used
  5. Designing human-centric technology experiences: Usability, accessibility, and the human experience are vital aspects in the design of systems and tools
  6. Working creatively within real-world constraints: Exploring new, innovative ways of approaching their work will help technology teams sustain and evolve their services and impact in an uncertain future
  7. Building a strong and adaptive data governance backbone: The ability to scale and evolve data and analytics capabilities alongside rapidly evolving technologies depends on a foundation of trustworthy and adaptive data governance
  8. Measuring and navigating enrollment shifts: Institutional leaders need data and analytics to understand and respond to demographic and other factors impacting enrollments
  9. Meeting stakeholders where they are with AI: Technology teams must deliver AI training and support that accommodates different levels of stakeholder familiarity, comfort, and readiness
  10. Reducing friction for more seamless technology experiences: Simplified, integrated technology systems and processes provide easier student, faculty, and staff access to important services and support
  11. Exploring agentic AI for learning and work: Institutions need to understand the implications of emerging agentic AI capabilities for student learning and the higher education workforce
  12. Staying ahead of technology change: Cultivating environmental-scanning and risk-sensing capabilities enables technology teams to anticipate and manage opportunities and threats before they become urgent
  13. Maintaining agility in the technology workforce: Responding to evolving institutional needs and emerging technologies requires technology teams to reorganize, reskill, and redesign roles
  14. Leveraging automation for institutional efficiencies: Implementing systems and tools to streamline and automate processes can enable staff across the institution to focus on their highest-priority work
  15. Implementing long-term strategies for digital literacy: Effectively supporting digital literacy among faculty, staff, and students requires broad and sustained investments of funding and other resources
  16. Telling data-informed stories of institutional value: Compelling, transparent stories about student outcomes and community impact can help institutions regain public trust
  17. Positioning technology leaders as institutional integrators: Technology leaders need to be skilled at pulling together and integrating disparate ideas, people, and resources to effectively accomplish their work
  18. Enabling lifelong learning for evolving careers: Institutions can design lifelong, continuous learning and credentialing that will help students carve out nonlinear, flexible career pathways
  19. Moving students beyond textbooks and into practice: Technology and instructional design teams can support experiential pedagogy through virtual spaces, collaborative tools, and AI-enabled practice for enhancing applied skills
  20. Accomplishing more through strategic partnerships: Developing internal and external partnerships can help technology teams extend capabilities, reduce duplication, and accelerate progress toward their goals
  21. Personalizing the student journey: Institutions can use AI and data analytics to support students through individualized, adaptive learning experiences and support systems