Speaking with AI: the impact of microsoft 365 copilot voice chat on EFL learners’ fluency, interactional competence, and autonomy

Abbas Hussein Abdelrady, Abdelhamid A. Khalil, Abdul Aziz Mohamed Mohamed Ali El Deen, Abdulaziz Ibrahim S. Alnofal, Amr M. Mohamed

Introduction The growing availability of generative artificial intelligence (AI) tools has created new opportunities to enhance language learning, particularly speaking practice. However, studies on the effectiveness of AI voice-chat applications in enhancing English as a Foreign Language (EFL) learners’ speaking skills and autonomy remain limited. Methods This mixed-methods quasi-experimental study investigated the effects of Microsoft 365 Copilot voice chat on speaking fluency, interactional competence, and learner autonomy of 52 university English as a Foreign Language (EFL) learners over eight weeks. The experimental group ( n = 26) engaged in voice-based speaking tasks with Copilot, while the control group ( n = 26) completed parallel peer-to-peer speaking activities. Results Quantitative analyses revealed that the experimental group demonstrated greater improvements in speech rate, mean length of run, and pause reduction, as well as larger improvements in turn-taking, repair strategies, and topic management. Learner autonomy scores increased significantly only for the experimental group [ t (25) = 4.12, p < .001, d = 0.82, mean difference = 0.90, 95% CI [0.45, 1.35]], with 71% of participants voluntarily exceeding the required practice time. Qualitative reflective responses with eight experimental participants indicated reduced speaking anxiety, perceived usefulness of immediate feedback, and increased motivation. Discussion These findings suggest that AI voice chat, when integrated into learners’ existing academic tools, may support multidimensional speaking development and autonomous practice in EFL contexts.