Leading Faculty Development in AI
What, Why and How
What programming should you offer?
Here we find ourselves as teaching and learning leaders on more comfortable ground. You already know what works at your institution in terms of faculty development. You likely have existing programs and activities that have proven powerful in shifting the culture around teaching and learning, or you have a pretty good idea of what those programs and activities could be. The end of this section includes some exemplar programs from across Canada that you can consider (and envy) in your institutional context.
That said, you don’t need to create something brand new for AI; rather, we strongly encourage you to look at what programming you have already that is most impactful and ask yourself: (how) could we include AI learning here? To that end, just like our caution against a stand-alone AI policy, here we suggest you should complement any stand-alone AI programming for faculty development with existing supports.
Why faculty development on AI?
AI is changing every aspect of teaching and learning and so every program, service and support we offer at our teaching and learning centers needs to account for this impact. We believe our responsibility as teaching and learning leaders is to create positive change in teaching and learning. Our programs and activities work toward this aim, and as we adapt these programs and services to include or account for AI, we can – and should – continue to do so with this goal at the heart.
Programs and activities that include AI can – and should – continue to centre the relational aspects of teaching and learning, the friction of learning, the purpose of post-secondary as institutions cultivating curious and engaged citizens of the world. They do not need to be (all) about using AI to speed up grading, or to answer student questions, or to write learning outcomes that will satisfy your quality assurance committee. What programs and services your institution offers and how you approach these are – and should be – in line with the values of your CTL and institution.
AI in teaching and learning is a topic where you will need to lead a response while also confronting your own – and those of members of your team – personal reactions. It’s okay if you or members of your team are uncomfortable or uncertain about AI and its impact on teaching and learning (or society more broadly) – those feelings are valid and shared by many educators. Our personal perspectives on AI matter, and at the same time the impact of this technology on teaching and learning is larger than our individual reactions. Rather than holding back, consider bringing these questions to your community and listen, too, to other perspectives.
For members of your team grappling with the use of AI it can be helpful to acknowledge their concerns or questions, and to emphasize that the impact of the technology on teaching and learning necessitates the involvement of the CTL (or the area where you lead). Remind the team of how your team values and purpose are present in the work you are doing, and acknowledge where these values may be in conflict. Like any change, individuals will experience it differently and at a different pace. At the same time, it is reasonable to expect members of your team to engage with AI as it is fundamentally reshaping the work of teaching and learning in post-secondary and cannot be jettisoned to one person or program, or to when your staff feel fully comfortable.
How to lead faculty development on AI?
To that end, every member of your CTL staff needs to be (or quickly become) comfortable in the basics of AI. You could assign them the resources from Chapter One and work as a team to discuss and share. In our experience it works less well now in 2025 to have the one ‘AI person’ on staff. This work has become the work of all educational developers because AI is changing all of teaching and learning: course design, inclusion, learning outcomes, assessment, classroom activities, educator-student relationships, accessibility: it all needs to be considered with an AI lens.
Look to your institutional partners – the library, accessibility services, academic departments, IT and human resources – for support and inspiration.
If you’re working with limited resources: Start with one low-cost initiative rather than trying to implement multiple programs. Consider hosting monthly “AI office hours” where faculty can bring questions, partnering with the library to offer joint workshops, or creating a simple resource page that curates existing materials rather than developing original content. Remember that responding to faculty-initiated questions often has more impact than proactive programming that doesn’t match community interest.
Recognize that AI impacts disciplines differently. STEM fields may focus on code generation and data analysis, while humanities consider writing assistance and research applications. Professional programs need to address industry-specific AI adoption. Consider discipline-specific sessions or partner with departments to address their particular contexts and concerns.
And finally, as promised, here are some terrific examples of what our colleagues are doing across the country. We’ve organized these roughly along a low-cost/low-effort to high-cost/high-effort continuum to adopt and implement:
Examples of Faculty Development Programs Related to AI in Teaching and Learning
- Collect examples of AI use: Like UBC’s compilation of community-submitted use cases of AI in teaching and learning
- Create (or link to) an asynchronous module like McMaster’s Introduction to Generative AI for Educators or Humber’s Introduction to Generative Artificial Intelligence (genAI) for Instructors
- Create or communicate a framework for attributing AI use, like the University of Waterloo did, at the institution or in a given course
- Host AI Playgrounds focused on guided exploration and experimentation with AI tools
- Create a drop-in workshop series like University of Calgary’s “Conversations about AI in your teaching”
- Design and implement a series of linked workshops or courses for educators (and incentivize participation) or offer discipline specific programming/departmental workshops like Dalhousie University
- Create a community of practice like the one at Western University or a professional learning network following this step-by-step guide to set-up
- Guide experimentation with AI tools for teaching and learning like these teaching and learning challenges from UBC
- Develop an AI Conference or actively engage as a speaker, panelist, or participant at the University of Guelph’s Teaching with AI Conference
- Author (or link to) a Guidebook like University of Toronto’s which “offers guides, explainers, and idea generators related to planning for and integrating generative AI into courses, structured according to four key teaching phases: before the course starts, during the first week, week-to-week, and at the end of the term.”
- Relevant U of T Teaching Examples across disciplines.
- Name Teaching and Learning Fellows focused on AI work with specific expectations and deliverables like Western did
- Create or repurpose existing teaching and learning grants to focus on generative AI, as UBC did – describing it as “providing means and infrastructure to experiment with GenAI in teaching and learning.” Grant recipients receive funding for the project, access to an institutional sandbox, technology support from an incubator team and student support.
- This Critical AI Literacy Workshop-in-a-Box is a ready-to-use resource designed to help educators and facilitators guide participants through an engaging, interactive exploration of Generative Artificial Intelligence (GenAI) and its societal impact. This workshop moves beyond technical skills, encouraging critical thinking about AI’s capabilities, limitations, biases, and ethical considerations.
- To help teachers integrate and explore AI in their learning design easily and effectively, there are several templates available that can help with structuring a learning activity or journey. Instructors can implement these without any specific tools, just following the principles of the learning design.
