The trajectories of educational technology and artificial intelligence, once parallel and largely independent, have now converged so completely that treating them as separate domains no longer makes sense. In the early 2000s, a master’s degree in educational technology concerned itself with multimedia authoring, learning-management systems, web-based resources and generic evaluation models. Meanwhile, AI labs were refining neural networks, speech recognition, computer vision and, eventually, the large language models that power today’s conversational agents. These two strands have now braided into a single rope that pulls the entire education sector toward an intelligent, data-saturated future. Adaptive tutoring engines adjust reading passages on the fly, chatbots scaffold metacognitive reflection, multimodal analytics transform clickstreams into personalised intervention plans, and extended-reality headsets gather psychomotor data in virtual laboratories. A postgraduate curriculum that still majors on yesterday’s toolkits risks preparing graduates for a world that no longer exists.