Abstract
With more than 1.2 billion young people, the Global South faces an urgent need to move beyond traditional education systems. Furthermore, this urgent transformation mainly focuses on reimagining education as a tool for comprehensive human development, which is founded in the region’s unique cultural values, moral traditions and communal cohesion, rather than the means of dispensing information. Therefore, this study explores the role of Artificial Intelligence (AI) in addressing structural issues in education in low- and middle-income countries. We developed an integrated educational challenge score focusing on the out of school rates, completion rates and proficiency levels using a multi-indicator dataset from 124 countries. AI was adopted to rank the countries. Our results for the developed composite score showed Niger, South Sudan, and Djibouti as the most affected third world nations having the urgent need for educational upgrade. In the regression result, the Random Forest Regressor most accurately predicted unemployment based on education variables (R² = 0.17), indicating a modest but relevant relationship between disparities in education and labor outcomes. The results guide a strategic roadmap for the development of AI in education in the global south.