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Federal and state departments of transportation, the US Army Corps of Engineers, electric utility companies, and other decision-makers need accurate and timely information about the condition of infrastructure to prioritize investment decisions. Currently, there are no broadly applicable automated tools to provide timely information about structural health. Artificial intelligence (AI) provides a forward-looking perspective to conceptualize and implement a data-driven and physics-informed structural health monitoring (SHM) strategy to overcome some of the challenges in traditional approaches. In September 2020, the National Science Foundation funded a project to demonstrate the proof-of-concept of an AI-driven SHM platform. The project team interacted with potential end-users and decision-makers to identify important aspects to consider in an AI-driven SHM platform. This paper summarizes the feedback received from the stakeholders and presents the project's preliminary results that serve as proof of concept.