As artificial intelligence permeates the educational landscape, a critical paradox has emerged: while AI promises to democratize personalized learning, it threatens to solidify a new ‘algorithmic inequality.’ For students in well-resourced districts, AI-driven tutors and predictive analytics act as powerful force multipliers, accelerating mastery and freeing up teacher time for high-level mentorship. Conversely, schools in underfunded regions—already struggling with aging hardware and intermittent connectivity—face a perilous lag. When the digital divide evolves into an ‘intelligence divide,’ the gap is no longer just about access to the internet; it is about access to a cognitive partner that can explain, adapt, and iterate in real-time. If we allow the deployment of AI to mirror existing socioeconomic disparities, we risk creating a tiered system where premium AI literacy is a luxury for the few, rather than a foundational right for all. To ensure that the next generation of learners doesn’t inherit a broken paradigm, policymakers must prioritize ‘AI equity’—investing in localized infrastructure and open-source models that treat high-quality, adaptive tutoring as a public utility rather than a commercial privilege. Closing the chasm isn’t just about handing out devices; it’s about ensuring every child, regardless of zip code, has the agency to leverage machine intelligence as a catalyst for their own intellectual mobility.