Following President Trump’s Executive Order on Advancing Artificial Intelligence Education for American Youth in April 2025, a new national vision of AI emerged in classrooms meant to meet job market demands and keep up with international competition. The new AI-powered classroom is envisioned as a world where AI becomes an educator. AI provides instructional material, analyzes student performance in real time, and adapts to student needs at unprecedented speeds. While many AI enthusiasts may call this an opportunity to bridge the achievement gap, I propose that AI instruction is likely to exacerbate current structural inequalities pertaining to unequal funding, infrastructure, and support. In this paper, I will utilize California as a case study due to its proximity to Silicon Valley and its elevated levels of income inequality to investigate the implications AI has on students, teachers, and equity. Through an integrated study of (1) interviews with professors at the University of Chicago and primary school teachers in California and (2) a quantitative exploratory data analysis of student outcomes, I outline current barriers to equity and the effects of AI on education.
