Data management plans (DMP) are an intrinsic part of planning for and implementing openness in scientific research. DMPs contain integral information on research projects: IT requirements, legal and ethical considerations and strategies for opening data. However, all too often, the DMP is seen as a chore drawn up at the request of external funders rather than a tool adopted for the benefit of project members. Similarly, the information gathered into DMPs is rarely utilised by other stakeholders such as institutional research services, nor linked to external parties such as data repositories. Machine-actionable DMPs aim to change this landscape by offering better guidance and support for researchers preparing their plans, and facilitating a research data management system that allows data and information to be shared across institutions and repositories. In fact, one of the recommendations of the EOSC Nordic project, which studied FAIR incentives and expected impact in the Nordics, Baltics and EOSC, was the implementation of machine-actionable DMPs for seamless information workflow and supporting FAIR adoption in everyday research work. Tools such as Data Stewardship Wizard and Argos do this by taking researchers through a set of simple structural questions on research data management from which answers are exported into funder templates resulting in downloadable DMP documents. These machine-actionable online tools transform tick-the-box answers that are easy to fill in into full-text DMPs that comply with funder requirements. This poster introduces a pilot project testing the Data Stewardship Wizard and localising its Knowledge Template to the needs of Aalto University. It presents the project’s findings and stages, including the process of creating a template for the Research Council of Finland DMPs and testing the tool with researchers. In doing so, it examines machine-actionable DMPs from a practice-based perspective and comments on the process of institutional implementation.