Toward Intelligent X-ray Spectroscopy: An Agentic AI Platform for Automated and Multimodal Analysis

X-ray Absorption Spectroscopy (XAS) is a powerful, element-specific probe of electronic states and local atomic structure, particularly valuable for amorphous and disordered materials. Its ability to reveal chemical speciation and coordination environments has made it widely used across materials science, chemistry, and physics, and it is now among the most widely used techniques at synchrotron facilities. However, XAS interpretation remains challenging and expert-dependent, and recent synchrotron upgrades have transformed XAS into a high-throughput, multimodal technique that demands scalable, automated analysis rather than traditional manual workflows. This talk will present current progress toward an agentic AI system designed to accelerate and automate XAS analysis. The focus will be on the AI agent framework, its ability to extract richer materials information than conventional approaches, and its extension to multimodal spectroscopy datasets, along with a brief overview of broader AI developments for a modern X-ray spectroscopy beamline, including automated experimental control and the vision of an intelligent laboratory.