With artificial intelligence breakthroughs permeating the Earth Science domain, there is an immediate need to advance the data, tools, and resulting technologies to broader societal challenges. Different efforts are emerging with fragmented best practices for making Earth Observation (EO) data Artificial Intelligence (AI)-ready, availing computer vision and image analysis tools for broader reuse across the remote sensing community. This paper will revisit current best practices and outline a guideline for advancing EO data and derivative AI products for broader community use. We mainly discuss the Analysis Ready Data (ARD) essentials and aim to forge their evolution with Findable, Accessible, Interoperable, Reusable (FAIR) principles to support cross-modal/cross-sensor/cross-provider opportunities that appear to be central to solving complex EO challenges.