This review examines the current state of research on generative AI (GAI) chatbots in higher education (HE), focusing on empirical studies published between December 2022 and December 2023. The study analyzes 23 research articles, employing a three-pronged approach: (1) examining the state of the emerging field, (2) identifying learning theories used in the studies, and (3) scrutinizing discourses about AI in HE. The findings reveal a diverse range of study designs and methods, with a focus on GAI chatbots' performance, trust, reliability, and student motivation. Learning theories such as experiential learning, reflective learning, active learning, and self-regulated learning are used in some studies, though not consistently. The research also highlights the presence of both dystopian and utopian discourses about the future role of GAI chatbots in HE. While some studies suggest positive impacts on student learning and teacher practices, others express concerns about potential negative effects, such as academic integrity issues and the displacement of teacher roles. The review underscores the need for more theoretical and methodological rigor in future research on GAI chatbots in HE. It also emphasizes the importance of understanding the social and ethical implications of AI in education, as well as the need for more nuanced and balanced discourse around the role of GAI in HE. The study concludes that while GAI chatbots show promise, their impact on HE practices and student learning remains complex and requires further investigation.This review examines the current state of research on generative AI (GAI) chatbots in higher education (HE), focusing on empirical studies published between December 2022 and December 2023. The study analyzes 23 research articles, employing a three-pronged approach: (1) examining the state of the emerging field, (2) identifying learning theories used in the studies, and (3) scrutinizing discourses about AI in HE. The findings reveal a diverse range of study designs and methods, with a focus on GAI chatbots' performance, trust, reliability, and student motivation. Learning theories such as experiential learning, reflective learning, active learning, and self-regulated learning are used in some studies, though not consistently. The research also highlights the presence of both dystopian and utopian discourses about the future role of GAI chatbots in HE. While some studies suggest positive impacts on student learning and teacher practices, others express concerns about potential negative effects, such as academic integrity issues and the displacement of teacher roles. The review underscores the need for more theoretical and methodological rigor in future research on GAI chatbots in HE. It also emphasizes the importance of understanding the social and ethical implications of AI in education, as well as the need for more nuanced and balanced discourse around the role of GAI in HE. The study concludes that while GAI chatbots show promise, their impact on HE practices and student learning remains complex and requires further investigation.