Artificial Intelligence–Driven Knowledge Management for Development in the Global South: Bridging Digital Divides Through Localized Innovation

Abstract This chapter explores the transformative potential of artificial intelligence (AI)-driven knowledge management (AIKM) systems in addressing development challenges in the Global South (GS), particularly in Africa. Traditional KM frameworks often fail to serve the GS due to infrastructural deficits, linguistic diversity and limited technical capacity. However, advances in mobile technology, edge computing and culturally aware AI present a unique opportunity for inclusive innovation. The chapter argues for context-specific AIKM solutions that leverage the GS’s demographic strengths – such as its youthful, mobile-savvy population – and proposes strategies to overcome systemic constraints like unreliable internet access, limited power infrastructure and scarce computational resources. Focusing on localization, the chapter advocates for the development of lightweight, offline-capable AI tools that process knowledge in local languages. It highlights the importance of integrating indigenous knowledge and supporting digital sovereignty through regionally trained AI models. Key application areas include education, financial inclusion, healthcare and entrepreneurship, where AIKM can streamline operations, enhance accessibility and support sustainable development. Emphasis is placed on avoiding reliance on First World AI paradigms, which are often ill-suited to GS realities, and instead adopting leapfrogging strategies to build nimble, community-driven systems. The chapter concludes by calling for ethical, transparent and decentralized governance of AIKM to balance empowerment with safeguards against misuse. Ultimately, it posits that with strategic adaptation, the GS can not only close the digital divide but also lead the next wave of knowledge-based innovation.