Abstract: This study investigates the readiness of research institutions to implement FAIR (Findable, Accessible, Interoperable, and Reusable) and Open Data frameworks. It specifically examines five key constructs: awareness, digital literacy, technical capacity, AI readiness, and FAIR readiness, with a particular focus on the mediating role of AI readiness. Academic and research experts were sent a structured questionnaire using a quantitative, cross-sectional approach. Partial Least Squares Structural Equation Modeling (PLS-SEM) data analysis was employed to investigate direct and mediated effects among the constructs of the research. The analysis indicated that AI readiness is pivotal in improving FAIR readiness and completely mediates the connection between technological capacity and FAIR outcomes. Technical capacity greatly affects AI readiness; however, it does not immediately forecast FAIR readiness. Awareness and digital literacy showed no direct impact on FAIR preparedness, indicating the primacy of system-level integration over individual knowledge alone. The study demonstrates the importance of using AI to establish FAIR principles and promote Open Data adoption. Moreover, it provides empirical evidence highlighting the need to strategically implement AI readiness into technological infrastructures to improve data management practices. In turn, the findings allow for practical recommendations to be made that will help academic leaders and policymakers create AI and FAIR-aligned research settings in Kuwait and other similar locations.

Keywords: FAIR Data Readiness, Artificial Intelligence, Open Data, Research Information Systems

Pages: 734-748