Open innovation has emerged as an interesting topic to research in innovation management. Open innovation involves exchanging knowledge or ideas among stakeholders to improve the internal innovation process and create possibilities for external application of innovation. In this study, we are exploring the extant literature available in the domain of open innovation and machine learning to identify its relevance in the open innovation context. To attain this objective, we collected data from two databases (i.e. Scopus and Web of Science) by searching keywords related to open innovation and machine learning. After filtering and pre-processing, topic modeling is applied to discover applications of machine learning algorithms in the open innovation field. This study provides valuable inputs to researchers in the field to investigate various applications of machine learning algorithms in an open innovation context.