AY2025-26 Campus AI Curriculum Task Force | Office of the Provost

Task Force Members

Derek Hoiem, Professor, Grainger College of Engineering, Co-chair
Shaowen Wang, Associate Dean for Life & Physical Sciences, College of Liberal Arts & Sciences, Co-chair
Brandon Batzloff, Interim Associate Dean for Academic Affairs, School of Information Sciences
Amanda Brantner, Senior Director of Content & Educational Portfolio Strategy, Gies College of Business
Nerissa Brown, Executive Associate Dean of Academic Programs, Gies College of Business
Elhan Ersoz, Clinical Assistant Professor, College of Agricultural, Consumer & Environmental Sciences
Colleen Lewis, Associate Director of Graduate Programs, Grainger College of Engineering
Ismini Lourentzou, Assistant Professor, School of Information Sciences
Liam Magee, Professor, College of Education
Luc Paquette, Associate Professor, College of Education
John Reid, Executive Director, Center for Digital Agriculture
Kevin Scharp, Professor, College of Liberal Arts and Sciences
David Ward, Associate Professor, University Library
Wojtek Chodzko-Zajko, Vice Provost for Graduate Education and Dean, Graduate College, ex officio
Ingrid Fulmer, Advisor for Strategic Initiatives, Office of the Provost, ex officio
Kevin Jackson, Vice Provost for Undergraduate Education, Office of the Provost, ex officio
Allison McKinney, Assistant Dean, Graduate College, ex officio

Charge Letter

Dear Colleagues,

Artificial intelligence, in its traditional forms as well as its more recent generative form, has the potential to transform our educational enterprise in ways we are beginning to imagine. We have much to imagine still for its impacts, and its opportunities, for how we teach, how we learn, and how we launch the learner-leaders of tomorrow towards their exciting future. Our campus is known for interdisciplinary collaborations in education, creating unique and high-value blended degrees, and providing transformative educational experiences for our students. The moment is right to leverage this collaborative spirit in conjunction with our deep and broad expertise in AI, putting us in a great position to lead the nation in educating our students in AI.

The campus is advancing on the development of a comprehensive AI education strategy and implementation across our colleges and units. The initiatives include, but are not limited to: (i) facilitating and supporting regular structured conversations on a broad range of AI topics; (ii) supporting our instructors to infuse AI concepts and usage in their courses; (iii) supporting the development of general education elective courses in AI; (iv) supporting the development and launch of AI certificates; (v) developing a campus-wide AI minor; and (vi) developing blended X+AI (or AI+X) degrees.

Creating meaningful, lasting, and rigorous transcriptable credentials require careful consideration of learning outcomes, course and curriculum design, and resource allocation. In the AI space, consideration must also be given to whether students will approach AI as a tool within a discipline, or a discipline on its own. The educational background and prerequisite knowledge of the broad swath of learners that would want to engage in earning these credentials also must be taken into consideration.

On behalf of the Office of the Provost and Deans Bashir, Bollero, Chodzko-Zajko, Elliott, Knox, Mouza, Patton, and Stewart, I am pleased to appoint and charge each of you as members of the Campus AI Curriculum Task Force.

We specifically request that your committee address the following:

Articulate the framework for the development of a campus wide undergraduate AI-minor that could be available to all students at the University. What would be the learning objectives, specific courses, and resources needed for this minor? When could such a minor be launched and where should it be housed?
Leveraging our success in developing and offering blended degrees, what would a blended X+AI (or AI+X) undergraduate degree model look like on our campus? What would the AI core look like and how do we learn from our CS+X and X+DS model to formulate these future X+AI degrees? How would such a degree differ from a campus-wide AI minor? Articulate any administrative and financial considerations for such blended degrees. Would there be a benefit to a centralized structure to manage multi-college X + AI degrees?
Incorporate the development of a campus-wide undergraduate AI certificate that would be stackable into the AI minor and blended X+AI (or AI+X) offerings.
Give consideration to an accessible and scalable delivery model for coursework offered in the AI minor and the +AI (or AI+) components of a blended degree model. Articulate any administrative and financial considerations for a scalable model.
In developing a blended X+AI (or AI+X) degree model, give consideration to how that model could be transferred to graduate education.
Consider how social, ethical, environmental, and economic concerns should be integrated into these programs.

We expect your work to include engaging faculty outside the schools and colleges represented on this committee. For example, the Teaching Advancement Board consists of instructors from across campus and has expressed a particular interest in AI curriculum. Please reach out to Vice Provost Kevin Jackson to meet with the Board. Another useful conversation would be to engage with members of the Senate Education Policy Committee. Please reach out to Dean Brooke Elliott or to Advisor to the Provost Ingrid Fulmer for an introduction.

Staff support will be provided for this committee. The deans are committed to be available should the committee want to meet with them to hear their perspectives and answer questions.

I would like to receive a short summary update by December 19, 2025, and a written report on the items above by January 19, 2026. If you need additional time, please let me know.

On behalf of the deans and myself, thank you for your service to this task force.

Sincerely,

John Coleman
Provost

Executive Summary

Artificial intelligence (AI) is rapidly reshaping how knowledge is created, applied, and evaluated across all disciplines. Its growing role in academic work, professional practice, and civic life presents both an opportunity and a responsibility for the University of Illinois Urbana-Champaign. Students across campus are already using AI tools in their learning activities, while employers increasingly expect graduates to be fluent in AI-enabled workflows. At the same time, broader societal concerns have emerged regarding the ethical, economic, environmental, and social implications of AI adoption. In response to these dynamics, the Provost, together with Deans Bashir, Bollero, Chodzko-Zajko, Elliott, Knox, Mouza, Patton, and Stewart, convened the Campus AI Curriculum Task Force and charged it with articulating a coherent framework for AI education across undergraduate and graduate programs.

The task force has developed a comprehensive plan for AI education: grounded in research on workforce trends, structured by an innovative AI literacy framework, guided by our values of excellence, responsibility, and inclusivity, and built on our hallmark strengths in interdisciplinary teaching and innovation.

The committee’s work is anchored in two central commitments:

All students at the University of Illinois should achieve AI fluency, defined as the ability to use AI tools effectively, reflectively, and responsibly within disciplinary and professional contexts.
The University should provide accessible pathways for students to become AI innovators, including those who advance AI technologies, design AI-enabled workflows, or shape the policies and organizations that govern AI use.

To support these commitments, the committee proposes a guiding ALL-IN framework for AI education (see Table 1 and Figure 1 for explanatory figures). This framework organizes AI learning around three AI Foundations and three AI Integration competencies, providing a coherent structure that can be applied across disciplines and levels of study.

AI fluency emphasizes AI Integration competencies – Domain-specific Integration, Critical Thinking, and Responsible Use – which are integrated into teaching throughout the curriculum. To achieve universal AI fluency, the committee recommends three developments across all majors:

Integrate modules on effective, reflective, responsible AI into first-semester courses.
Teach domain-specific tools, such as AI-assisted coding, AI-assisted literature research, or AI-assisted data analysis, within existing courses.
Reinforce critical thinking, problem solving, and responsible AI use in senior-level projects and capstone courses.

AI innovation is built on AI Foundations, operationalized as three separate, specially designed course sequences that prepare students for a broad range of aims:

AI & ML Technologies: Employ math and statistics, coding, machine learning (ML), and systems engineering techniques to design, train, and deploy AI models.
Agentic Systems & Workflows: Effectively use LLMs and AI models and connect them to domain-specific data, interfaces, and decision processes.
Human-Centric AI: conceptualize, design, evaluate, critique and govern AI, in light of its existing or foreseeable impacts on society, economy, and the environment.

The committee recommends leveraging these AI foundations to establish one or more campus-wide AI certificates that stack into AI minor and multiple X+AI blended degrees.

The committee emphasizes accessibility and scalability throughout its recommendations. The proposed delivery model integrates AI education into existing courses, supported by modular instructional content and structured faculty development. Social, ethical, environmental, and economic considerations are integrated throughout AI curricula rather than isolated in stand-alone courses.

The recommended curricular developments require faculty to invest considerable time and acquire new skills. The committee recommends three developments to support these efforts:

Support an annual Illinois AI-Enabled Courses Initiative (AICI) program to foster a community of AI-equipped faculty.
Provide year-round consultative support by experts in AI and related instructional tools and best practices.
Coordinate development of modules that can be used for AI fluency and foundational topics in multiple courses.

The committee recommends steps toward AI pathways and universal fluency for graduate students, but more consideration is needed, particularly in establishing models for interdisciplinary programs and credentials.

The committee also suggests creation of a central, campus-level structure to coordinate and oversee development of AI education and offers considerations to guide the design of that structure. Further discussion is warranted regarding both the coordination structure and the administration of AI credentials. This report responds explicitly to each of the six charge items outlined by the Provost and concludes with recommendations for next steps. Appendices and supplemental reports contain materials that will be useful for further planning and implementation work. Noting that these recommendations reflect information available at the time of writing and that additional discussion and decision-making is necessary, the committee believes that the framework presented here provides a strong foundation for advancing AI education at Illinois.