In increasingly remote and digitally mediated education, English Language Learners (ELLs) encounter new and heightened challenges related to language development, digital literacy, and affirmation of cultural identity. This study explores how integrating generative artificial intelligence (AI) with culturally responsive teaching practices can reshape language instruction to become more inclusive, adaptive, and student-centered.

Drawing upon phenomenological research, this investigation is grounded in interviews with experienced educators from urban schools across the United States. Three principal domains of innovation emerge: the development of inclusive virtual learning environments, the use of AI to enhance instructional scaffolding, and the adoption of authentic, multimodal assessment strategies. Together, these approaches support more equitable and engaging English learning experiences in both synchronous and asynchronous formats.

First, sustaining cultural practices that recognize and affirm learners’ identities is essential. Educators employ reflective digital tools such as Padlet and Flipgrid to facilitate translanguaging, peer collaboration, and storytelling, all of which contribute to heightened engagement and a sense of emotional safety. Conversational AI platforms - including Call Annie - are integrated to provide low-stakes opportunities for oral practice, context-specific feedback, and increased learner confidence through simulated interactions.

Second, adaptive AI-driven scaffolding addresses the diverse linguistic and technological needs of ELLs. Platforms such as NotebookLM for grammar assistance and Quizlet for vocabulary acquisition, complemented by strategic dialogues, enable tailored pacing and support. Explicit instructional modeling and guided exploration remain crucial, particularly for adult learners and individuals with limited digital literacy, ensuring effective adoption and meaningful use of these emerging technologies.

Third, the study advocates a shift in assessment practices. Moving away from traditional standardized measures, educators are implementing multimodal, project-based evaluations that incorporate AI-generated feedback, voice recordings, and self-assessment rubrics. These methods offer a more comprehensive reflection of language development, learner growth, and student agency.

A phased approach to implementation is proposed:
(1) professional development centered on digital pedagogy and AI tools;
(2) iterative piloting of AI-enhanced instructional activities; and
(3) expansion of technological infrastructure to ensure equitable access.

Findings highlight that, when intentionally embedded within culturally responsive and scaffolded frameworks, AI has the potential to become a highly motivating, personalized, and authentic pedagogical resource.

This research encourages educators, policymakers, and technology developers to recognize AI as a transformative partner in advancing equitable, multilingual education. It calls for moving beyond temporary trends toward systemic, sustainable change.

Keywords: English Language Learners, Generative AI, AI in Language Education, Culturally Responsive Pedagogy, Digital Scaffolding, Translanguaging, Multimodal Assessment, Remote Language Learning, Inclusive Education, Digital Literacy, Oral Language Development, Technology-Enhanced Language Learning.