Description
This project examines how community-based health care organizations can strengthen AI readiness by supporting confident and collaborative use of generative AI tools already available within the organization. At KidsAbility, a community-based non-profit children’s treatment centre, this area of inquiry is not new. Prior research has examined barriers to generative AI adoption and identified several critical challenges, including the diversity of clinical workflows, the systemic nature of documentation burden, the importance of flexibility and professional autonomy, and the need for mutual learning between clinicians and technology. Together, these findings highlight why there is no one-size-fits-all approach to generative AI use in community-based care. Building on this existing work, the proposed project adopts a service design and human-centred research approach to examine where barriers to engaging with generative AI, along with where breakdowns occur in clinicians’ everyday workflows. This project will examine how early frustration shapes whether generative AI is sustained or abandoned. Through interviews, service flow mapping, and co-design workshops, the project will explore optional opportunities for generative AI use across different parts of clinical practice, including documentation, family-facing communication, and creative therapeutic activities such as developing personalized exercises aligned with a child’s interests. In partnership with KidsAbility, the project will co-design and pilot a flexible, practice-based toolkit that supports clinicians through the early learning and calibration phase of generative AI use. The project will also develop an AI readiness framework that conceptualizes readiness as a process shaped by professional confidence and collaboration, generating transferable insights for other community-based health care organizations.