Artificial Intelligence for Personalized, Adaptive, and Inclusive Learning: A Systematic Literature Review (2022–2026) - Farah Nur Dianita; Dannia Dwi Agustina; Septi Rakhmah Insani; Ayyula Az Zuhroh; Fatimah Azzahrah; Ernita Vika Aulia; Siti Nurul Hidayati (Universitas Negeri Surabaya, 2026)
Artificial Intelligence (AI) has been advancing rapidly and accelerating the transformation of education toward more personalized, adaptive, and inclusive learning environments. Despite the growing body of research, few studies have examined these three learning approaches in an integrated and holistic manner. This study analyzes the development and application of AI in education and its contribution to personalized, adaptive, and inclusive learning between 2022–2026. A Systematic Literature Review (SLR) based on the PRISMA framework was employed. Data were collected from Scopus, Google Scholar, ERIC, and ScienceDirect. Following screening and eligibility procedures, 312 records were identified, and 25 peer-reviewed articles were selected for analysis. In SLR studies, representativeness depends on the relevance and methodological quality of the selected studies rather than the number of publications. The selected articles covered the review period and captured dominant themes and emerging trends in AI-supported learning. Thematic saturation was achieved, indicating that additional studies did not provide new insights and confirming the adequacy of the sample for synthesizing developments over the five-year period. Data were analyzed using narrative synthesis, research trend analysis, article classification, and thematic analysis. The findings reveal increasing interest in AI-powered chatbots, adaptive learning platforms, Intelligent Tutoring Systems, and learning analytics. AI enhances learning effectiveness, student engagement, academic achievement, accessibility, and personalized instruction. However, challenges remain regarding infrastructure, teacher readiness, data privacy, ethical concerns, and algorithmic bias. The review proposes a holistic framework integrating personalized, adaptive, and inclusive learning and offers theoretical and practical implications for effective, equitable, and responsible AI-supported education.