University of Toronto Libraries Scoping Decision Tree for Paid AI-Powered Research Tools

This decision tree is designed for collections librarians and information professionals at the University of Toronto who are considering submitting requests for AI-powered research tools related to library collections that have an associated cost. As libraries navigate the rapidly evolving landscape of AI technologies, this framework provides a structured guide to help determine which tools might align with our licensing capabilities and institutional priorities. These considerations are not intended to provide definitive acceptance or rejection decisions, but rather to guide your preliminary assessment process. These questions may help you identify if a respective AI-powered research tool warrants further investigation, the possibility that tools unsuitable for library licensing may be appropriate for other university units to consider, or which present challenges may need to be addressed before licensing can be considered. The decision tree encourages thoughtful evaluation of factors including licensing models, target audience alignment, the capability for users to opt-out, and cost considerations. Remember that these questions represent initial scoping criteria only - tools that appear within scope will still require further evaluation regarding privacy implications, data security, integration capabilities, and alignment with library values before final licensing decisions are made. If your initial assessment suggests that an AI-powered research tool may be within scope for licensing by the library, please contact your collections specialist or coordinator to discuss further. A text-only version follows the provided graphic. Created: March 2025