Based on the proposed theoretical framework of Makransky and Petersen (2021) called CAMIL (Cognitive Affective Model of Immersive Learning) and on an embodied view of cognition for Second Language Acquisition (Atkinson, 2011), this chapter examines the research on how generative artificial intelligence (GAI) can be integrated with high-immersion virtual reality (HiVR) technologies that use head-mounted displays for the purpose of language learning. A review of studies conducted with both commercial and non-commercial HiVR apps revealed that although these immersive environments offer learners new spaces for interaction, most AI-enabled apps do not allow for genuine conversation. Instead, the automatic speech recognition (ASR) capabilities typically only offer users to choose from a set of pre-programmed options, without allowing for spontaneous conversations, leading to a call for expanded AI capabilities (Chun et al., 2022). One promising avenue involves employing GAI chatbots (Huang et al., 2022) that have been found to be helpful for language learning. These so-called “social bots” are designed to be proactive and not just reactive to users (Godwin-Jones, 2023, p. 12). However, the challenge remains as to how to best integrate GAI or large language models (LLM), such as Chat GPT, with HiVR. Generative AI could play the role of a partner, rather than a traditional tutor, and could promote active social learning involving interactions using both the brain and the body (Hwang & Chen, 2023). Furthermore, research and development are needed to take full advantage of the unique affordances of HiVR, specifically its fully immersive quality that enhances presence and its multisensory features that allow for holistic embodied participation.