In this interview, Julie Forman-Kay discusses the future role of NMR (Nuclear Magnetic Resonance) in structural biology, especially in the context of AI advancements. She emphasizes that while AI tools like AlphaFold have made significant strides in predicting static protein structures, they fall short in understanding protein dynamics and disordered regions. NMR is crucial for capturing these dynamic properties and excited states of proteins, which are essential for their function. Forman-Kay argues that integrating NMR data with machine learning algorithms is the next step for advancing structural biology.