The creation of uOttawa’s AI strategy and roadmap, started as a draft based on Infotech’s Research Group blueprint and work accomplished by other Canadian universities. The draft was then shared for consultation with all IT leaders across campus. Through this process, a shared AI vision was created.
The Information Technology AI strategy guides the integration of AI initiatives at the University through five key focus areas for continuous improvement, efficiency, and innovation through the transformative power of AI.
“An effective AI strategy is not focused on how to leverage AI in our organization, but how AI can help our organization realize its business vision and strategy.” – Office of the CIO
Five focus areas
Area 1: Alignment with Strategic Objectives
We want to ensure the use of AI is aligned to the uOttawa mission, vision and strategic objectives. AI can help us towards ‘Building the University of tomorrow’. Whether it’s revolutionizing research, facilitating tasks for our community, or improving day-to-day operations, AI is a strong asset. See how the University is leveraging AI:
- Office of the Vice-President, Research and Innovation (OVPRI)
- Teaching and Learning Support Service (TLSS)
- Library Generative AI guide
Area 2: Security and Privacy in Mind
The security, safety and privacy of our networks, systems and community is non-negotiable. Strong security and privacy controls, and the responsible use of data are key in AI decisions. The University has already began developing guidelines:
- Guidelines for Security and Privacy for the Usage, Procurement and Deployment of AI
- Guide on reasonable use of AI while protecting personal information (only available with VirtuO access)
- Generative Artificial Intelligence copyright considerations from the uOttawa Library
Area 3: Integrate With Existing Governance and Processes
Governance plays a strong role at the University, and AI governance will be no different. AI implementations must align with both the University goals and Information Technology goals. Through this process, we enhanced our existing Enterprise Architecture guidelines with the responsible AI principles. In this way we lower risk, stick to policies, and resolve AI-related issues as we navigate this new landscape.
A new University AI advisory committee is being created with different representatives across campus, so that we have a consolidation of viewpoints through expert voices. This committee coordinates AI efforts across the institution. It also shares best practices and ensures consistency. The AI committee supports the University’s commitment to apply responsible AI principles to all related projects.
Area 4: Buy Over Build
Our approach is realistic. As we learn about AI, we will prioritize existing, off-the-shelf AI solutions over re-inventing the wheel. But we’re not afraid to learn and will build custom solutions and models when needed.
We have leveraged our Microsoft licences to introduce Copilot on the web to the University community. By logging in with an uoAccess account, users benefit from faster processing, some data protection, and a new AI companion.
Area 5: Ensure Robust Data
Our use of AI will rely heavily on data. We will collect and use quality data for this reason. We will protect and use it responsibly through clear and strong governance and practices.
To achieve this, we will evolve to be a more data-centric culture. First, by defining our Data governance roadmaps and formalizing a Data Governance committee. This committee and other stakeholders can build data policies, and help us align the University to look at data in new and more structured ways.
The implementation of Artificial Intelligence is a new frontier for the University. There will be testing, evaluation and iteration as we integrate AI. Our strategy ensures we embrace AI in a strategic way, with our vision and mission guiding us. To follow Information Technology’s AI journey, visit our Artificial Intelligence webpage.