Artificial intelligence hub establishment in emerging economies: a comparative study of best practices and contextualization for Nigeria

Dada, Oluwaseun Alexander

Artificial intelligence hub establishment in emerging economies: a comparative study of best practices and contextualization for Nigeria

Thesis / Dissertation

2026

Publisher

University of Cape Town

Department

Department of Information Systems

Faculty

Faculty of Commerce

Abstract

This thesis examines the viability of establishing sustainable and inclusive Artificial Intelligence (AI) hubs in Nigeria that are grounded in local socio-economic and institutional realities while drawing selectively from international best practices. While established AI hubs in advanced economies benefit from stable governance, deep capital markets, robust digital infrastructure, and highly networked innovation systems, Nigeria operates within a landscape marked by infrastructural deficits, limited financing pathways, volatile governance and persistent brain drain. However, the country also possesses distinctive strengths, including a rapidly growing youth population, an energetic fintech sector, emerging innovation clusters, and an influential diaspora. This study adopts a qualitative, exploratory research design grounded in an interpretivist philosophical stance to examine how Artificial Intelligence (AI) hubs can be established in Nigeria. A hybrid evidence strategy was employed, combining a structured and systematic literature review with in-depth semi-structured interviews. The literature review synthesises global evidence on AI hubs, clusters, and innovation ecosystems across developed and emerging economies using a rigorous search protocol, inclusion - exclusion criteria, and thematic coding. Primary data were collected through semi-structured interviews with multi-stakeholder participants drawn from the government, academia, industry, civil society, and technology ecosystems. Interview data were analysed using thematic analysis, with initial coding aligned to the conceptual framework and subsequently consolidated into higher-order thematic groups. Triangulation was used to integrate insights from the literature and interviews, enhancing validity and contextual sensitivity. The analysis culminated in synthesising the findings into a contextualized framework for AI hub development in Nigeria. his framework reconceptualises AI hub development in emerging economies as an adaptive civic innovation infrastructure, where long-term viability depends on the alignment of governance legitimacy, human capital mobilisation, infrastructural readiness and ecosystem coordination. In addition, the findings suggest that in fragile and infrastructure-constrained contexts such as Nigeria, AI hubs are unlikely to emerge as a single Silicon Valley-style cluster in one city; instead, they are more likely to evolve as interconnected ecosystems distributed across multiple urban, institutional, and digital centres. Therefore, the study's core theoretical contribution lies in extending existing AI hub and innovation ecosystem models beyond advanced-economy assumptions by demonstrating how hubs can emerge and stabilise within resource constrained, institutionally volatile contexts such as Nigeria. The findings generate three overarching insights. First, governance and legitimacy emerge as foundational: transparency, accountability, and community trust are as important as digital infrastructure or financial capital in determining hub viability. Second, human capital constitutes Nigeria's decisive resource base, encompassing technical capability, entrepreneurial capacity, ethical leadership, and mobilisation of diaspora knowledge networks. Third, inclusivity and sustainability are functional imperatives: hubs that marginalise women, rural communities, or underrepresented groups risk limited adoption and weak societal embeddedness, while long-term resilience depends on diversified financing, adaptive governance, and sustainable energy sources. Practically, this study provides a contextually grounded roadmap for developing AI hubs in Nigeria. The government should prioritise policy coherence, early stage public investment, and anti-corruption safeguards; academia must strengthen interdisciplinary AI curricula and industry linkages; industry actors should pursue problem-driven innovation in high-impact sectors such as finance, agriculture, and health; and donors and the diaspora can serve as catalytic partners in capacity building and early investment. Overall, this thesis argues that Nigeria cannot-and should not-replicate Silicon Valley or Singaporean models in their entirety. Instead, it must pioneer a distinctive Global South pathway that integrates technological innovation, social legitimacy, ethical governance and contextual adaptation. If implemented effectively, such hubs could position Nigeria as a continental leader in AI while contributing to a broader Global South paradigm in which technological advancement and social transformation evolve together.