Can synthetic avatars replace lecturers? An exploratory international study of higher education stakeholder perceptions

Abstract Advances in technologies which use Generative Artificial Intelligence (GenAI) to mimic a person’s likeness or voice have led to growing interest in their use in educational contexts. However, little is known about how key stakeholders (teaching faculty and professional staff) perceive and intend to use these tools. This study investigates higher education employees’ perceptions and intentions regarding the use of synthetic avatars (alternatively known as deepfakes) through the lens of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Using a mixed-methods approach that combined quantitative survey data ( n = 173) with qualitative text response, we found that academic stakeholders demonstrated a relatively low intention to adopt these technologies ( M = 41.55, SD = 34.14) and held complex, often contradictory views about their implementation. Stakeholders identified potential benefits, including enhanced student engagement through interactions with historical figures, improved accessibility through voice synthesis, and reduced workload in content creation. However, they expressed significant concerns about the exploitation of academic labour, institutional cost-cutting leading to automation, degradation of human relationships in education, and broader societal impacts, such as environmental costs and information validity. Quantitative analysis revealed that adoption intentions were most strongly associated with hedonic motivation, with a gender-specific interaction in the evaluation of price value. Qualitative findings highlighted significant concerns regarding ethical implications, resource inequities, and the impact on professional identity. These results suggest that traditional technology acceptance models should be expanded to consider broader ethical and structural factors. Based on these findings, we propose a three-pillar framework for implementing synthetic avatar technologies in higher education that emphasises establishing robust institutional policies and governance structures, developing comprehensive professional development and support systems, and ensuring equitable resource allocation guided by evidence-based implementation strategies. This study enhances our understanding of how emerging AI technologies can be thoughtfully integrated into higher education while maintaining academic integrity and professional autonomy of educators.