A research paper, "AI Research in Developing Nations" by Bright Etornam Sunu, examines the significant imbalance in global AI development, highlighting how progress is concentrated in wealthy nations while developing countries remain on the periphery. It details the multifaceted challenges these nations face, including inadequate infrastructure, funding gaps, and a scarcity of localized data, which exacerbate existing inequalities. Despite these hurdles, the source showcases inspiring problem-driven innovations and vibrant local AI ecosystems emerging from the Global South. Finally, it proposes strategic pathways to foster a more equitable AI future, advocating for democratized access to compute resources, localized data ecosystems, increased investment, talent retention, and culturally relevant AI governance. The overall argument emphasizes that bridging this AI divide is crucial for a more robust and just global AI landscape, benefiting all of humanity.