The future potentials of AI as a mobile educational assessment technology are vast, offering a transformative approach to personalized learning. As AI continues to develop, it has the capacity to revolutionize educational assessment by providing individualized learning systems. The integration of "AI technologies can help address, in conceiving individualized, adaptive learning systems for reading proficiency across the developmental spectrum, . . . implications for practice and/or policy" (Sabatini, et al., 2023. p. 1175). AI has the potential to tailor educational experiences based on the unique needs and progress of each learner. Particularly, the use of AI and computational linguistics in educational assessments holds promise in bridging gaps in understanding and enacting a longer vision of reading development. This process allows educators to implement targeted interventions and support strategies. The implications for practice and policy are lifechanging, paving the way for a more responsive and effective educational system that caters to the diverse and dynamic needs of learners. 

In terms of forecasting it is probable that AI technology in the future will become incredibly easy to integrate into almost any technology, website, or system. "We can imagine a hypothetical AI that perfectly [understands] all the language in the content and assessment material” (Phillips et al., 2023, p. 649). Theoretically, assessment systems that already exist in tools like Magicschool.ai may be directly implemented into an LMS. Students with access to AI assessment can gain feedback for a variety of outcomes instantaneously. Style, form, function, complexity, detail, content, and argument can all be assessed with AI in a way that only grammar and spelling is currently done. In this way formative assessment becomes truly mobile. Even with current technology, we can communicate between student and teacher at any time in any place, but that feedback is still dependent on the teacher having the time and inclination to read and assess student work.  Once students have access to AI feedback on writing and reading, then assessment is truly mobile, because it does not rely on an external source outside your control.