We demonstrate the performance of the WTMetaD-IB AL approach using linear Atomic Cluster Expansion (ACE) potentials to model three organic reactions, namely the S N 2 reaction between fluoride and chloromethane in implicit water (R1), the methyl shift of 2,2-dimethylisoindene in the gas phase (R2), and the glycosylation reaction between glucosyl α-trichloroacetate and i -PrOH in explicit dichloromethane (DCM) solvent (R3). For the first two examples, we compare the accuracy and sampling efficiency against our previously reported AL + downhill dynamics strategy. We show that the integration of WTMetaD-IB and AL results in accurate and data-efficient MLIPs, without requiring a priori knowledge of the relevant TSs and/or reaction pathways. The accuracy and stability of the MLIP trained using WTMetaD-IB AL demonstrate the broad applicability of the proposed method, reducing computational cost and human intervention and facilitating the widespread use of MLIPs in modelling reactivity.