CLAS Outlines Strategic AI Priorities for 2026

December 1, 2025

About the CLAS AI Task Force

The responsible and effective use of artificial intelligence (AI) is a top priority in the College of Liberal Arts and Sciences (CLAS) and across the University.

In 2024-2025, CLAS established an AI Task Force comprising faculty and staff from across academic and administrative units. The group was charged with considering the pros and cons of AI across the college, and producing a report with recommended actions the college should take to ensure the responsible and ethical use of AI by CLAS staff, faculty, and students.

In spring 2025, the task force submitted a report (UConn NetID access required) to the Dean’s Office outlining key recommendations. Beginning spring 2026, the college will begin following the recommendations of the task force by implementing the steps described below. These steps will help CLAS establish priorities, address evolving needs, and position itself as a leader in advancing and supporting University-wide AI initiatives.

College Strengths and Priority Areas

CLAS faculty are preparing students to use AI thoughtfully and critically, and are conducting world-class research on the ethical, social, and technological dimensions of AI. Their work is advancing our understanding of topics such as bias, equity, literacy, and human impact, and applying AI across a broad range of disciplines.

We also see the transformative potential of AI to improve how we operate. From administrative workflows to research, teaching, and communication, CLAS will use AI responsibly to improve operational efficiency, expand the reach of our research, and strengthen the college’s reputation within UConn and beyond.

Beginning in 2026, CLAS will implement the following priorities, based on recommendations from the CLAS AI Task Force. Our approach emphasizes both the human impact of AI and its practical use across teaching, research, and operations, laying a strong foundation as institutional capabilities and University support continue to evolve.

Coordination and Governance

  • Establish a Standing Committee on AI Implementation. CLAS will form a permanent committee (e.g., CLAS AI Innovation Committee) to guide the strategic implementation of AI across operational areas. This group will identify needs related to policy development, training, education, and support. It will also consider ethical implications and ensure alignment with University-wide initiatives while reflecting the unique perspectives of the liberal arts and sciences.
  • Participate in University-Level AI Governance. CLAS will actively contribute to the development of AI governance at the University level, bringing expertise in ethics, policy, and pedagogy.

    Needs Assessment and Curricular Guidance

    • Inventory Existing and Potential AI Uses. In spring 2026, CLAS will conduct a survey of faculty, staff, and students to gather information on current and potential uses of AI. The survey will collect self-reported benefits, challenges, and concerns. Results will inform local policy development, guide support services, and help identify emerging best practices.
    • Develop Guidance on Curriculum and Course Delivery. The college will recommend that the CLAS Courses and Curricula (C&C) Committee develop guidance for incorporating AI into course content and curriculum across the college.

      Training, Education, and Support

      • Training Partnerships. CLAS will partner with campus groups (e.g., CETL, OVPR) to deliver training on AI use in teaching, research, and administration. The goal is to ensure that faculty and staff across disciplines are supported in using AI tools effectively, ethically, and in ways appropriate to their roles.
      • Centralized Resources. CLAS will create a centralized AI resource hub where community members can access CLAS-specific AI policies and guidelines, as well as curated links to University-wide AI information, guidance, and support tools.

        Operational and Digital Innovation

        • Increase Operational Efficiency. CLAS will expand and evaluate pilot projects that use AI to improve administrative workflows, with the goal of reducing manual tasks and increasing staff capacity for strategic work.
        • Optimize Web and Digital Content for AI-Driven Discovery. CLAS will take steps to modernize its websites to ensure they are optimized for AI-based search and discovery. This will include implementing machine-readable formats, accessible content structures, and metadata that enhances visibility to generative AI platforms.