Striking a balance between automation and human interaction (Selwyn, 2019), this qualitative phenomenological study, utilizing keyword analysis--a corpus-based technique (Culpeper & Qian, 2020), explored six TESOL professors/teacher educators’ AI-assisted communicative styles and culturally sustaining pedagogy in asynchronous interactions in graduate TESOL courses with high student satisfaction ratings. The conceptual framework consists of Spencer-Oatey’s (2008) rapport management framework (2008) and Papp and Cottrell’s (2021) best teacher professional learning “directly connected to teachers' working contexts and problems of practice; so, actions are practical, relevant to teachers' needs, and contribute to achieving valued student outcomes” (p.121). The study analyzed 2190 discussion and grading posts from Canvas courses with 9 out of 10 ratings on faculty performance to examine how these communicative styles foster learning outcomes and engagement. Findings revealed the major styles-- expressiveness, restraint, directness, and engaging key phrase templates facilitate learner engagement and rapport among asynchronous online students. Utilizing research findings and practical ways to incorporate AI tools into effective online teaching and retrospective reflections on student learning outcomes for development with AI are thus recommended. Actionable human-centric integration of AI insights for instructors and instructional designers to optimize communicative strategies and boost online student learning and satisfaction will be shared.