How USask is guiding AI work
Artificial intelligence (AI) is raising new opportunities and questions across teaching, learning, research, service, and administrative work. At the University of Saskatchewan (USask), these developments are being examined in relation to the university’s mission, priorities, responsibilities, and the needs of the university community.
USask is not approaching AI as a goal in itself. Instead, the university is exploring how AI can support student success, teaching and learning, research, service, and institutional effectiveness while also considering the responsibilities that come with its use. This includes understanding where AI might be useful, where caution may be needed, and how decisions can be made in ways that reflect the university’s values and responsibilities.
Work involving AI is not being treated as a collection of disconnected projects or individual technology decisions. The work is supported through executive oversight from the Office of the Provost and Vice-President Academic and contributions from across the university, helping ensure that decisions reflect institutional priorities, responsibilities, and community needs. It is being guided through co-ordination, collaboration, consultation, and ongoing evaluation.
Faculty members from a range of disciplines contributed expertise and perspectives that helped inform university discussions about how AI may affect teaching, learning, research, and other areas of university activity. This work was supported through completed initiatives such as the AI Horizons Expert Forum and AI Task Force, alongside contributions from university leaders, staff, and institutional support units. Together, these perspectives helped the university better understand opportunities, risks, and responsibilities associated with AI.
This work builds on earlier institutional efforts and ongoing learning about AI. Experience, evaluation, and evidence continue to help inform future decisions. The focus is on building understanding and making informed choices rather than deciding outcomes in advance.
How the work has evolved
USask’s approach to AI builds on earlier institutional efforts rather than beginning with a single project, tool, or funding initiative. The work has developed through connected stages that helped the university move from establishing responsible-use foundations, to building readiness and co-ordination, to testing, learning, and evidence-building. These stages build on one another and continue to inform the university’s approach as the work evolves.
Phase 1: Creating conditions for responsible AI use
Early work focused on creating a foundation for responsible AI use. This included developing principles, guidelines, and opportunities for campus input to help clarify expectations for AI use in teaching, research, administration, privacy, security, and ethical decision-making.
This foundation helped establish a shared starting point for understanding both the possibilities and the responsibilities associated with artificial intelligence. It also helped frame AI as something to be approached thoughtfully, rather than as a technology to adopt without careful consideration.
Phase 2: Building readiness and co-ordination
As understanding grew, the work expanded to include readiness, co-ordination, engagement, AI literacy, and planning for responsible access and support. This stage focused on understanding the AI landscape across USask and identifying the structures, knowledge, collaboration, and capacity needed to support a more co-ordinated approach to AI.
This work also reinforced that AI-related activity involves academic, research, service, technology, governance, and support areas across the university. The goal was not to create a single point of ownership, but to support a more co-ordinated and informed approach across the institution.
Phase 3: Testing, learning, and informing future decisions
Recent AI-related work has focused on testing, learning, gathering feedback, and building evidence. This phase is helping the university better understand what tools, supports, safeguards, governance considerations, and engagement approaches may be needed over time.
This phase builds on earlier work rather than replacing it. It gives USask an opportunity to learn from practical experience, assess needs and risks, and gather information that can help inform future decisions about responsible AI-related work.
USask’s approach continues to evolve as the university gains experience, learns from practical use, and identifies what supports may be needed over time.
Why readiness, co-ordination, and ongoing learning matter
Readiness, co-ordination, and ongoing learning help explain how USask is approaching AI-related opportunities, risks, and responsibilities. Together, they reflect the university’s focus on preparing people, connecting expertise, and learning from experience.
Responsible use of artificial intelligence requires more than access to technology. In a university environment, decisions about AI can affect teaching and learning, research, services, information, and the broader university community. As a result, exploring AI-related opportunities involves considering not only what technology can do, but also how it can be evaluated thoughtfully and responsibly.
Readiness helps support informed decision-making. It involves building understanding, evaluating opportunities and risks, and helping ensure people are prepared to assess, use, and apply AI appropriately. This includes literacy, guidance, support, accessibility, privacy, security, and governance.
The University of Saskatchewan continues to evaluate and strengthen readiness as AI-related work evolves. The goal is not to assume that every opportunity should be pursued or that every question has already been resolved. Instead, readiness helps create the conditions for thoughtful evaluation, informed decision-making, and ongoing learning as technologies, needs, opportunities, and responsibilities continue to change.
Work involving AI often involves many parts of the university and can affect people, services, information, and priorities in different ways. Contributions from the University Library, the Gwenna Moss Centre for Teaching and Learning, Information and Communications Technology, the Office of the Vice-President Research, and other areas of the university help bring a range of expertise and perspectives to AI-related work. Because these activities can have implications across the institution, co-ordination helps connect expertise and experience so decisions can reflect a fuller understanding of opportunities and challenges associated with artificial intelligence.
Co-ordination supports shared understanding and informed decision-making. Rather than approaching AI-related work through disconnected initiatives or isolated decisions, a co-ordinated approach helps bring together different perspectives and areas of expertise. This can help the university better understand potential impacts, identify considerations that may otherwise be overlooked, surface gaps and risks, and align decisions with university priorities and responsibilities.
Co-ordination also helps the university respond to new opportunities, responsibilities, and community needs in a more consistent and informed way. By drawing on expertise, consultation, leadership involvement, and learning from across the institution, USask can support responsible approaches to AI as needs and priorities change.
Ongoing work involving artificial intelligence is helping USask learn what works, evaluate outcomes, and build evidence before making larger decisions about future approaches. As technologies, opportunities, risks, and community needs change, this learning helps the university identify what may be useful, appropriate, and aligned with its responsibilities and priorities.
Learning from experience, feedback, evidence, and changing needs can help inform future decisions. Rather than relying on assumptions or treating current activity as proof of long-term success, the university is using what it learns to better understand potential benefits, limitations, and areas where additional support may be needed.
Continued learning is part of a responsible approach to AI-related work. It helps ensure that future decisions are informed by experience, evolving needs, and a growing understanding of how artificial intelligence may affect teaching, learning, research, services, and the broader University of Saskatchewan community.
Related resources
Learn more about AI at USask through resources tailored to students, educators, researchers, and staff.