This work explores how artificial intelligence (AI) principles can be applied in low-resource classrooms to improve student engagement and learning outcomes, even without advanced digital tools. Drawing from my teaching experience in underserved Nigerian schools, the study examines adaptive learning strategies, feedback loops, and personalized instruction inspired by AI methodologies. The abstract outlines a proposed action research framework for implementing low-tech, AI-inspired pedagogical techniques and measuring their impact on student participation and comprehension. This contribution aims to support educators, researchers, and policymakers seeking scalable and inclusive approaches to AI in education, especially within low-income and resource-constrained environments.