This study analyses global facets of educational inequity, examines urban-rural divides and attempts to analyse the potential of Artificial Intelligence (AI) in bridging this gap. Urban regions are comparatively better equipped with the modern technology and income resources, while rural institutions are mostly equipped with obsolete materials, suffer from teacher shortages and have minimal digital access leading to low student outcomes and high dropout rates. The case studies in India, Kenya, USA and Brazil were carried out through mixed methods and secondary data was taken mostly from global organisations. The study analysis of AI involves thematic and content analysis, statistical modelling and predictive analytics for the improvement of rural education. The study findings reveal that the AI intervention improved student engagement by 30 percent, STEM subject performance by 25 percent, and reduced overall dropouts by 40 percent for AI-integrated rural schools. Teachers were also empowered to personalise learning to students through AI-developed adaptive learning, virtual tutoring, automated grading and predictive analytics. Conversely, infrastructural shortage, digital illiteracy, financial strain and teacher reluctance remain obstacles for AI penetration in these rural areas. Further recommendations suggested by the research include massive investment in digital infrastructure, AI training programs, public-private partnerships and policy reforms geared towards inclusive and equitable education. The empowerment of such reforms would indirectly set the pathway towards a democratic approach for students and children inhabiting the rural hinterland to attain a feeling of quality personalised learning. This can be a bridge over the long-entrenched urban-rural educational divide.