Data Governance frequently feels overwhelming; governance frameworks outline a long list of things we feel we need to do, but aren’t, and the guilt we frequently feel stifles action. Data Governance should be simple and impactful - but how do we make it more approachable, and more importantly, make it sustained and focused on outcomes? The desire to use AI/ML compounds the challenges agencies face with their underfunded data governance initiatives - we need to do new and creative things with our data, but how do we do this safely, responsibly, and in ways that we can explain how the data was used and managed? Key questions we will address: • How do you pick an impactful starting place for data governance? • How do you make the case for doing something different? • Iterative Governance: how to cast a big vision and start small • Examples of quick wins and low-barrier initiatives • Tips for getting buy-in from leadership and other departments