The FAIR Digital Object (FDO) concept takes a further step, by requiring that much of the core metadata information is both accessible directly at the point of resolving an object's PID, and unambiguously formatted and presented in a way that computer processes – including AI – can easily act upon. In this way FDOs promises greater discoverability and machine actionability of research objects, allowing us to use the world’s research data more efficiently. However, FDOs are seen by many as overly complex and difficult to implement. Our session aims to demystify the concepts involved, and build a bridge between producers and users of "FAIR data" and "FAIR DO" proponents through examples illustrating what is required to upgrade digital objects from basic “FAIR for humans” to fully-fledged FDOs.