In this chapter, I examine whether generative artificial intelligence (GAI) is truly a transformative force in education or simply the latest in a long line of overhyped technologies. Following Mayer (Psychology of learning and motivation. Academic Press, 2002), I situate GAI within a century of educational technology promises (e.g., film, radio, television, computers, massive open online courses (MOOCs), and learning analytics) that would revolutionize education, only to disappoint when adopted in technology-centered rather than learner-centered ways. GAI, like earlier tools, excels at management: automating routine academic tasks, streamlining editorial workflows, and easing instructional logistics. These affordances can free time for higher-level work, but they also risk diminishing engagement and the intrinsic cognitive effort essential for deep learning. There are also serious concerns associated with GAI, including misinformation, deepfakes, academic dishonesty, and the potential erosion of critical thinking and human interaction. I argue that, to move beyond “flavor-of-the-month” status, GAI must be pedagogically aligned—supporting individualized, optimally challenging, feedback-rich learning experiences—and its use must be evaluated with rigorous intervention research that measures actual learning, not just satisfaction. Without such evidence, GAI is unlikely to escape the fate of prior educational technology fads.