Hadron spectroscopy at Jefferson Lab has entered a new era, driven by high-precision data from GlueX and CLAS12 and a growing interest in exotic hybrid states. At the same time, AI and machine learning are emerging as powerful tools to tackle the complexity of this data and deepen our understanding of QCD. This workshop brings together experimentalists, theorists, and data scientists working with JLab data to explore how AI can support hadron spectroscopy. The focus will be on identifying key challenges, sharing ideas, and building collaborations that can shape future research. Through a mix of talks and open discussions, we aim to connect communities and define practical steps toward integrating AI into spectroscopy efforts at Jefferson Lab.
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