<![CDATA[The integration of artificial intelligence (AI) in education has introduced innovative tools such as AI-driven educational avatars, offering new opportunities to enhance teaching and learning processes. However, their implementation in resource-constrained environments remains limited due to infrastructural, technological, and contextual challenges. This study aims to develop a context-sensitive framework for the adoption and adaptation of AI-based educational avatars in low-resource educational settings. Using a qualitative research design, this study employs a combination of literature review, case analysis, and expert consultation to identify key barriers and enabling factors influencing the effective use of AI avatars. The findings reveal that successful implementation depends on three critical dimensions: technological adaptability, socio-cultural relevance, and institutional support. Additionally, the study highlights issues such as limited internet access, lack of digital literacy among educators, and insufficient policy integration as major constraints. Based on these findings, the study proposes a contextualized framework that emphasizes scalable technology design, localized content development, and continuous capacity building for educators. The framework also underscores the importance of collaborative efforts among policymakers, educational institutions, and technology developers to ensure sustainable implementation. In conclusion, AI-driven educational avatars hold significant potential to improve educational access and quality in underserved contexts. However, their effectiveness largely depends on the ability to align technological innovation with local needs and systemic conditions.]]>
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