Miscommunication and communication challenges between instructors and students represents one of the primary barriers to post-secondary learning. Students often avoid or miss opportunities to ask questions during office hours due to insecurities or scheduling conflicts. Moreover, students need to work at their own pace to have the freedom and time for the self-contemplation needed to build conceptual understanding and develop creative thinking skills. To eliminate barriers to student engagement, academic institutions need to redefine their fundamental approach to education by proposing flexible educational pathways that recognize continuous learning. To this end, we developed an AI-augmented intelligent educational assistance framework based on a power language model (i.e., GPT-3) that automatically generates course-specific intelligent assistants regardless of discipline or academic level. The virtual intelligent teaching assistant (TA) system will serve as a voice-enabled helper capable of answering course-specific questions concerning curriculum, logistics and course policies. It is envisioned to improve access to course-related information for the students and reduce logistical workload for the instructors and TAs. Its GPT-3-based knowledge discovery component as well as the generalized system architecture is presented accompanied by a methodical evaluation of the system accuracy and performance.