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Abstract Carbon dioxide capture technologies are set to play a vital role in mitigating the current climate crisis. Solid‐state¹⁷O NMR spectroscopy can provide key mechanistic insights that are crucial to effective sorbent development. In this work, we present the fundamental aspects and complexities for the study of hydroxide‐based CO₂capture systems by¹⁷O NMR. We perform static density functional theory (DFT) NMR calculations to assign peaks for general hydroxide CO₂capture products, finding that¹⁷O NMR can readily distinguish bicarbonate, carbonate and water species. However, in application to CO₂binding in two test case hydroxide‐functionalised metal‐organic frameworks (MOFs) – MFU‐4l and KHCO₃‐cyclodextrin‐MOF, we find that a dynamic treatment is necessary to obtain agreement between computational and experimental spectra. We therefore introduce a workflow that leverages machine‐learning force fields to capture dynamics across multiple chemical exchange regimes, providing a significant improvement on static DFT predictions. In MFU‐4l, we parameterise a two‐component dynamic motion of the bicarbonate motif involving a rapid carbonyl seesaw motion and intermediate hydroxyl proton hopping. For KHCO₃‐CD‐MOF, we combined experimental and modelling approaches to propose a new mixed carbonate‐bicarbonate binding mechanism and thus, we open new avenues for the study and modelling of hydroxide‐based CO₂capture materials by¹⁷O NMR.