This article is intended as a companion document to the more focused report provided by the author at the 2017 American Education Research Association (AERA) Conference as part of the Technology, Instruction, Cognition & Learning Special Interest Group's Symposium on Intelligent Tutoring Systems (ITSs). Both the AERA talk and this article focus on adaptive instructional systems (AISs) which are comprised of learners, Intelligent Tutoring Systems (ITSs), and external (non-adaptive) instructional environments. AISs tailor instructional experiences for individual learners and teams of learners based on a model of their learning needs and preferences. An exemplar of an AIS is the Generalized Intelligent Framework for Tutoring (GIFT), an open source architecture for authoring, delivering, managing, and evaluating AIS technologies (tools and methods). This article reviews desired states for AISs in the context of enhancements to GIFT capabilities. This article covers a wide range of desired states for AISs and their affiliated design goals, challenges, and emerging solutions. While we consider the review presented in this paper comprehensive, we acknowledge that it is far from exhaustive. Our primary goal is to present the state of art, potential, and practice in ITS design in order to engage the education and training community in our quest to make AISs ubiquitous.