Beyond the AI Conversation Partner: A Critical Integrative Review of Generative AI-Supported L2 Speaking and the SPEAK Implementation Framework

Abstract

Generative artificial intelligence (GenAI) has rapidly expanded from text-based assistance to voice-enabled dialogue, automated oral feedback, and multimodal speaking assessment. These developments appear to address a persistent problem in second-language (L2) education: learners need frequent, low-risk opportunities to speak, but teachers cannot always provide individual interaction and feedback at scale. However, the availability of an apparently fluent conversation partner does not establish that durable speaking development, fair assessment, or transfer to human communication will follow. This critical integrative review examines three questions: what learning and affective outcomes are associated with GenAI-supported L2 speaking practice; what limitations weaken its pedagogical value; and what implementation conditions support responsible use. Targeted searches of Google Scholar, publisher platforms, open research repositories, and citation chains produced an analytical corpus of 11 core publications, supported by 14 theoretical, methodological, assessment, feedback-literacy, and ethics sources published or retained for interpretation through July 2026. Evidence was appraised for contextual clarity, task alignment, outcome validity, feedback transparency, and the strength of claims. The synthesis indicates that GenAI can increase practice volume, support rehearsal, provide scenario-based interaction, and reduce fear of immediate human judgement. Adaptive prompts and rapid feedback may also support vocabulary retrieval, discourse organisation, pronunciation awareness, and willingness to communicate. Yet the evidence remains dominated by small samples, short interventions, self-report measures, prototype studies, and technical benchmarks. Recurring risks include inaccurate or overconfident feedback, accent and speech-recognition bias, unnatural interaction, dependency, privacy concerns, unequal access, and weak transfer evidence. The review proposes the SPEAK framework: Structured tasks, Progressive intelligibility-focused feedback, Equity and ethics, Agency and anxiety-sensitive practice, and Knowledgeable teacher oversight. GenAI should therefore be used as a structured rehearsal and feedback resource within teacher-designed speaking pedagogy, not as an autonomous replacement for human interaction or professional judgement.