With the concept of privileged catalysts deeply rooted in organocatalysis, we expect a steady increase in studies aiming to bridge the gaps between different reactions that are mechanistically transferable via ML. Using this strategy, it is possible to both increase the available data (since more reactions are considered), as well as investigate more general mechanisms. However, careful consideration has to be paid towards combining different reactions, as mechanistic transferability has to be ensured. Furthermore, the usage of ML to identify general catalysts demonstrate that the application of modern ML tools is not limited to predicting selective catalysts.