This presentation shows how to use artificial intelligence technologies to inspect batteries with 3D X-ray microscopy (XRM) and computed tomography (CT). More specifically, it illustrates how deep learning-based algorithms for CT reconstruction can be integrated into 3D X-ray inspection workflows for batteries. In addition, artificial intelligence (AI) provides a wide range of tools for automated defect recognition (ADR) of complex components that are difficult to analyze using traditional measurement methods. Machine learning (ML) platforms can train ADR models to assess battery overhang and inclusions.