This study examines the nexus between artificial intelligence (AI) and democratic governance, using Nigeria as a case study from 2013 to 2023. It employs a neo-institutional theory, integrating historical and sociological institutionalism to analyse how institutional structures, cultural norms, and path dependence shape policy outcomes. Adopting an ex post facto research design, the research utilises documentary data collection and content analysis to analyse the research questions. The findings reveal that Nigeria's engagement is constrained by limited R&D investment, institutional inertia, and a misalignment between global norms and local realities, despite a growing ecosystem of private-sector innovation. The study concludes that overcoming these structural and cultural barriers is essential for Nigeria to actively shape and benefit from global AI governance frameworks. This study adds to the body of work on digital governance in the Global South by showing how important institutional legitimacy and historical context are for adopting new technologies. This study recommends strengthening government investment in AI R&D to enhance participation in global AI governance forums and also to foster structured public-private partnerships to integrate AI startups and capacity-building outcomes into public sector governance.

Keywords: Artificial Intelligence, Global Governance, Nigeria, Government Investment, Public Sector Innovation

Introduction

Artificial Intelligence is rapidly reshaping global governance frameworks, and Nigeria stands at a critical juncture in aligning its political and administrative systems with emerging AI-driven technologies. The swift progress of Artificial Intelligence (AI) has emerged as a worldwide phenomenon, revolutionising several sectors and civilisations globally. While artificial intelligence presents a transformative potential for governance, enhancing efficiency, transparency, and accountability, it also poses substantial risks, including regulatory lapses, data privacy concerns, algorithmic biases, and deepening inequalities. Developed countries have made substantial progress in adopting artificial intelligence (AI), whereas poorer nations such as Nigeria are now starting to investigate how AI might be used to tackle important socio-economic issues (Chui et al., 2022). In Nigeria, where institutional weaknesses already challenge governance, the integration of artificial intelligence without robust oversight may exacerbate existing issues and compromise democratic consolidation.

Nigeria, the country with the highest population in Africa, over 200 million people, encounters several obstacles that hinder its progress. The difficulties encompass insufficiency in healthcare services, diminished agricultural output, educational deficiencies, and exclusion from financial opportunities (World Bank, 2021). Conventional approaches to tackling these problems have frequently been inadequate, necessitating the development of inventive and adaptable solutions. Artificial intelligence (AI), with its capacity to analyse vast information, produce accurate forecasts, and automate procedures, presents a hopeful approach to tackling these systemic issues (Ndukwe, 2023; Adebayo, 2022).

Artificial intelligence (AI) is a field within computer science that focuses on creating algorithms and systems that can carry out activities that usually need human intellect. According to Professor Freedom Onuoha, AI simply defined is the development, existence, use or deployment of computer systems that have the capacity to perform tasks that could or are ordinarily performed by human intelligence (personal communication, 2023). It has become a revolutionary technology worldwide (Russell & Norvig, 2020). In 2017 President Putin said that whoever controls artificial intelligence controls the world (Onuoha, F., Personal Communication, 2023).

The decade from 2013 to 2023 marked a pivotal era in which Artificial Intelligence (AI) evolved from a theoretical domain to a disruptive force reshaping global economic, social, and political structures. This period, often termed the "AI Spring", was fuelled by breakthroughs in machine learning, deep neural networks, and access to vast computational power and data (Brundage et al., 2018). Recognising AI's transformative potential and associated risks, a global race for supremacy ensued, characterised not only by technological innovation but also by the urgent development of governance frameworks to ensure ethical and safe deployment (Cath et al., 2018; Zwetsloot & Dafoe, 2019).

Historically, the discourse of artificial intelligence and governance emerged alongside the Global Digital Revolution in the early 2000s but gained serious traction in Nigeria during the last decade. The turning point came with the release of Nigeria's Draft National Artificial Intelligence Policy by the National Information Technology Development Agency (NITDA) in 2020, which attempted to frame artificial intelligence within national development goals. Nonetheless, as Ksheteri (2017) and Nemitz (2018) observe globally, and scholars like Akanbi and Adebayo (2021) and Olatunji (2020) show locally, the slow pace of technological regulation, limited digital literacy, and inadequate infrastructure have kept Nigeria lagging in both policy and practice.

International organisations like the OECD, UNESCO, the G20, and the Global Partnership on AI (GPAI) became central arenas for establishing norms and standards for AI development (Büthe et al., 2022). However, this global discourse has been notably asymmetrical. A significant governance divide has emerged, where agendas are predominantly set by technologically advanced nations and corporate giants from the Global North, often overlooking the specific developmental contexts, priorities, and vulnerabilities of countries in the Global South (Cogburn & Espinoza, 2021; Adams, 2023). These dynamics raise critical questions about inclusivity, digital colonialism, and the capacity of emerging economies to actively participate in and influence the rules governing a technology that will profoundly impact their futures.

Within this global context, Nigeria presents a critical and compelling case study. As Africa's largest economy and most populous nation, its approach to technological adoption carries significant weight across the continent (Akinwale & Ogundele, 2022; World Bank, 2023). The period 2013-2023 captures Nigeria's nascent but strategic engagement with AI, a journey defined by a stark duality of vibrant grassroots innovation and formidable systemic challenges.

On one hand, Nigeria has demonstrated remarkable organic growth in its AI ecosystem. A burgeoning startup landscape, particularly within the fintech sector, has leveraged AI for innovative solutions in areas like credit scoring, fraud detection, and personalised services (GSMA, 2022; Adesina, 2023). Concurrently, significant efforts in capacity building have emerged from academia, tech hubs (e.g., Co-Creation Hub, Data Science Nigeria), and private sector initiatives, aiming to cultivate a local pipeline of AI talent (Osiakwan, 2021). Furthermore, the federal government signalled its intent through policy instruments like the National Digital Economy Policy and Strategy (NDEPS) of 2019, which implicitly laid the groundwork for AI integration in the public sector, and the more explicit draft National Artificial Intelligence Policy (NAIP) in 2022 (Federal Republic of Nigeria, 2019; 2022).

On the other hand, this progress is constrained by significant structural headwinds. Government investment in AI Research and Development (R&D) has been historically limited and fragmented, lacking the strategic focus and sustained funding seen in other nations (Eke et al., 2021). This raises questions about Nigeria's participation in global AI and technology governance forums and whether it is a passive observer or an active contributor shaping agendas. Key challenges such as inadequate infrastructure (e.g., unstable power, limited internet penetration), a protracted regulatory vacuum, and the late passage of a data protection law in 2023 have created a complex environment for AI startups to thrive and for the safe and effective integration of AI into public services (NITDA, 2020; Salami, 2021). It is in the light of these developments that this study explores Nigeria's participation in global artificial intelligence governance.

Government Investment in AI R&D and Nigeria’s Participation in Global AI and Technology Governance Forums

In analyzing the landscape of government investment in Artificial Intelligence Research and Development, a more critical school of thought, represented by scholars like Okonkwo (2021) and Jiboku (2022), argues that Nigeria’s issue is not just insufficient funding but a fundamental misalignment of AI R&D with national priorities. Okonkwo identifies that the Nigerian state approach to technology investment has been historically characterized by what he terms a “prestigious project syndrome” where visible, high-profile initiatives like the National Centre for Artificial Intelligence and Robotics (NCAIR) are launched with great fanfare but are subsequently starved of the sustained operational funding and strategic direction needed for meaningful impact.

This creates a façade of progress that masks underlying stagnation. Jiboku (2022) builds on this by applying dependency theory framework to argue that Nigeria’s Research and Development Strategy (or lack thereof) perpetuates its position on the periphery of the global knowledge economy. He contends that by failing to invest in core, fundamental research, Nigeria remains a consumer and adapter of technologies developed in the core nations (the US, China, and Europe), thereby continuing a cycle of technological dependence that hinders genuine industrial and economic sovereignty.

This perspective reframes the discussion from one of budgetary allocation to one of political economy and global power structures. This critique is supported by broader African political economy scholarship. For instance, Mensah (2020), in a study of technology adoption in Ghana and Nigeria, identifies a chronic “budget-implementation gap” where allocated funds for science and technology fail to be disbursed or efficiently utilized, echoing Okonkwo’s findings. Furthermore, the dependency framework is reinforced by Zingale (2022), who argues that the global AI supply chain is designed to keep African nations in a position of providing raw data and consuming finished AI products, a modern form of extractivism.

While this critique effectively diagnoses the problem of misalignment and dependency, the existing literature does not empirically investigate the direct causal link between specific government investment decisions (or the lack thereof) and the country’s concrete outcomes in global forums. This study will move beyond theoretical critique to systematically analyze how the “prestigious project” model and the absence of fundamental research funding directly impacted Nigeria’s negotiating power and participation quality in bodies like the OECD and GPAI.

Ndlovu (2023), in a pan-African analysis, argues on the terms of debate in forums and Adeyemi (2022) enrich the discussion by examining power dynamics. Ndlovu argues that global forums are hegemonically structured by the Global North, making Nigeria’s inconsistent participation a potential form of resistance. Adeyemi’s concept of “governance shopping” explains Nigeria’s peripheral role in global forums like the Organization for Economic Cooperation and Development (OECD) and Global Partnership on Artificial Intelligence (GPAI) that are set by the Global North, focusing on issues like “ethical AI” and “alignment” in ways that often overlook the more pressing concerns of the Global South, such as rectifying global data asymmetries and preventing digital colonialism.

From this viewpoint, Nigeria’s inconsistent participation is not just a function of capacity but also a form of subconscious resistance to engaging on terms that are not its own. Similarly, Adeyemi explores the concept of “governance shopping,” where weaker states, lacking the capacity to shape dominant frameworks, engage in a form of forum-shifting to arenas where they have more relative influence, such as the African Union (A.U.). This explains Nigeria’s more assertive role within the AU while it remains a peripheral actor in other global theatres.

This body of literature suggests that mere participation is not enough; the critical question is whether Nigeria can coalesce with other southern nations to collectively challenge and redefine the normative foundations of global AI governance. Cogburn (2018) details the concept of “multistakeholderism” in internet governance, arguing that it often masks the disproportionate influence of corporate and state actors from the Global North. Similarly, Abdulla (2019) explores how the “Brussels Effect” (the unilateral regulatory power of the EU) is now being replicated in the AI domain, forcing adopting countries to comply with external norms.

This broader context validates the observations of Ndlovu (2023), and Adeyemi (2022), regarding Nigeria’s constrained agency. This literature excellently frames the structural constraints but treats the Nigerian state as a monolithic entity reacting to external forces. A gap exists in understanding the internal bureaucratic processes: how did the specific lack of funding and technical capacity within relevant MDAs (e.g., Foreign Affairs, Communications) directly constrain diplomats’ ability to engage, beyond subconscious resistance? This study will investigate the micro-level capacity gaps within the state apparatus that led to passive participation.

Examining the landscape of government investment in Artificial Intelligence Research and Development and Nigeria’s participation in global AI technology and governance forums between 2013–2023, scholars largely converge on a narrative of nascent awareness hampered by systemic constraints, yet punctuated by isolated initiatives and growing rhetorical commitment. The literature positions Nigerian direct financial investment in AI-specific R&D as markedly limited, especially when compared to global benchmarks and even to regional peers like Rwanda, which launched a national Artificial Intelligence policy in recent years (Okechukwu, 2022).

According to Eke, Wakawa, and Onyema (2021), Federal budgetary allocation to science and technology, historically meagre and often underutilized, were not distinctly apportioned for AI, forcing research efforts to be subsumed under broader, and often underfunded, ICT or computer science envelopes. This financial constraint is identified as the primary bottleneck stifling ambitious AI research projects within public universities and federal research institutes, which suffer from inadequate computing infrastructure, poor Internet connectivity, and a lack of access to large curated datasets necessary for training sophisticated AI models (Adewusi, 2020).

Scholarly works further elucidate that the government’s approach during this period was less characterized by direct R&D investment and more by a facilitative, and at times symbolic, role. According to Musa and Bello (2022), the establishment of the National Centre for Artificial Intelligence and Robotics (NCAIR) in 2020 under the National Information Technology Development Agency (NITDA) represents the most concrete institutional manifestation of the government’s intent. However, scholars like Chukwunonso and Adeyemi (2023) are quick to critique that the Centre’s mandate, while laudable on paper, has been crippled by funding inconsistencies and a lack of clear, measurable output targets, making its overall impact on the national AI R&D landscape difficult to quantify.

The literature suggests that much of the substantive R&D during this decade was actually driven by the private sector, particularly by multinational tech companies like Google and Microsoft operating in Nigeria, and by academia through international grants and partnerships rather than through sustained government funding (Okolo, 2021). This created a fragmented ecosystem where critical research was often aligned with corporate interests or foreign academic agendas rather than being strategically directed towards solving Nigeria’s most pressing domestic challenges, such as food security, healthcare delivery, and infrastructure management (Talabi, 2019).

The challenge of funding science in Nigeria is part of a historical pattern. Jega (2020), provides a longitudinal study showing that Nigeria’s national R&D expenditure has never surpassed 0.5% of GDP since the 1980s, well below the AU target. Furthermore, the critique of a fragmented ecosystem is echoed by Bosun-Fakande (2022), who specifically maps the overlapping mandates of National Information Technology Development Agency (NITDA), National Office for Technology Acquisition and Promotion (NOTAP), Nigerian Communications Commission (NCC), concluding that this institutional turf war creates policy inertia and stifles innovation.

The discourse on Nigeria’s participation in global AI technology and governance forums between 2013–2023 paints a picture of an emerging actor struggling to find its voice and assert its interest on a crowded and highly competitive international stage. Scholars note that Nigeria’s presence in seminal global AI discussions, such as those hosted by the OECD, UNESCO, and GPAI, has been consistent and often represented by mid-level officials rather than high-powered delegations capable of shaping agendas (Bello & Smith, 2023).

This limited engagement is attributed by Nwankwo (2022) to a combination of factors, including a lack of a coherent national AI strategy for much of the decade, which meant the country often attended these forums without a firm, negotiated domestic position to advocate for. Furthermore, the technical complexity of AI governance issues , spanning ethics, data sovereignty, intellectual property, and military applications, requires deep expertise that was in short supply within the relevant government ministries, departments, and agencies (MDAs), leading to a passive rather than proactive participation style (Eze, 2020).

A comparative study by the Centre for International Governance Innovation (CIGI, 2021) on AI preparedness in the Global South found that most nations lack dedicated AI expertise within their foreign ministries, relying instead on generalists who are often outmatched by specialized delegations from wealthier nations. However, Singh (2022) offers a counterpoint, showing how India leveraged its vast domestic IT talent pool to quickly build capacity and assert itself in digital trade forums, a strategy Nigeria has yet to emulate effectively.

According to Adebayo (2021), Nigeria’s most significant foray into global AI governance during this period was its role within the African Union (AU) context. As a major regional power, Nigeria contributed to continental dialogues on African Union’s Digital Transformation Strategy and the ongoing efforts to develop a pan-African AI policy. Scholars argue that this regional platform offered Nigeria a more accessible and immediately relevant arena to influence norms and standards that align with African socio-economic realities and data cultures, as opposed to simply adopting frameworks designed in the Global North (Obioma & Chike, 2022). However, the literature also highlights a critical gap: the near-total absence of Nigeria from discussions surrounding the development and governance of frontier AI technologies such as large-scale foundation models and generative AI.

As noted by Ismaila (2023), the global race in foundational models is being set by a handful of corporations and state actors in the US and China, and Nigeria’s lack of investment in core R&D means it is relegated to being a consumer and a policy-taker in this specific domain, with profound long-term implications for its technological sovereignty and economic competitiveness.

The collective scholarly view suggests that while Nigeria began to show up at the global AI table towards the end of the decade, its participation was more symbolic than substantive, highlighting a critical need for capacity building within foreign policy and technology governance circles to effectively represent the nation’s interests in the years to come.

The review notes that countries with substantial investments in Artificial Intelligence Research and Development, such as the United States and China, are able to set the pace in standard-setting, ethical guidelines, and innovation policy. For example, these countries have made multi-billion-dollar investments through national plans like the U.S. National Artificial Intelligence Initiative Act (2021) and China’s Next Generation AI Development Plan (2017), which enable them to dominate forums like the OECD, ISO/IEC, and the Global Partnership on Artificial Intelligence (Cave & Dignum, 2019; OECD, 2021).

Nigeria’s Research and Development expenditure remains below 0.2% of its Gross Domestic Product (GDP), a figure far below the African Union’s recommendation of 1% and UNESCO’s global standard of 2% (UNESCO, 2023).

The Stanford AI Index (2023) indicates that Nigeria does not appear among the top 50 countries investing in AI R&D or producing peer-reviewed AI research. This gap is exacerbated by the absence of a clearly implemented national AI strategy. While countries like Kenya, Rwanda, and Tunisia have rolled out AI policies and roadmaps, Nigeria’s National Artificial Intelligence Policy remains in draft form as of 2023, awaiting cabinet approval (UNECA, 2023; NITDA, 2023).

According to Zhou et al. (2023), countries in North America, Europe, and Asia collectively produce over 90% of AI-related peer-reviewed publications, while sub-Saharan Africa contributes less than 1%. Nigeria’s academic institutions face structural barriers such as underfunding, outdated curricula, limited laboratory infrastructure, and a lack of access to global AI datasets and computing power.

Consequently, when Nigerian scholars do engage in AI research, it often lacks visibility in high-impact journals or conferences. Moreover, much of the AI research in Nigeria is either basic-level or focuses on applications without engaging with the broader ethical, legal, and policy debates that define global AI governance. This limits Nigeria’s ability to shape AI principles from an Afrocentric perspective, particularly concerning issues of fairness, inclusivity, and historical marginalization.

The focus on application-oriented research in the Global South is explored by Chan (2021), who terms it “AI for development” pragmatism. While this has immediate local benefits, it comes at the cost of ceding influence in foundational and ethical debates. Furthermore, the draft Nigerian AI policy can be compared to successful models elsewhere. The Rwandan strategy, as analyzed by Gathigi (2022), succeeded due to strong political will, clear ownership by the Rwanda Utilities Regulatory Authority (RURA), and focused pilots in healthcare and agriculture, avoiding the fragmentation seen in Nigeria.

While the comparative context is useful, the literature does not explore the two-way relationship between R&D and governance. The gap is in investigating how participation in global forums itself could (or should) inform and reshape domestic R&D priorities. This study will explore whether insights and networks gained from even limited forum participation have been fed back into Nigeria’s AI policy development process.

Theoretical framework

The study uses Neo-institutionalism as its theoretical framework, The theory, through historical and sociological lenses, helps explain Nigeria’s evolving engagement with Artificial Intelligence (AI) and global governance. Historically, Nigeria’s AI policies and R&D investments are shaped by institutional legacies of technological dependence, policy continuity, and path dependence within state bureaucracy. Past policy choices, limited research funding, and weak coordination among agencies constrain innovation, while participation in global AI governance forums reflects an effort to reorient these inherited structures toward international norms and cooperative standards that promote technological sovereignty and inclusion.

Sociological institutionalism highlights how shared beliefs, global norms, and cultural legitimacy drive Nigeria’s integration of AI into governance and capacity-building programs. Nigeria’s participation in organizations like UNESCO, AU, and OECD-based initiatives promotes policy diffusion and social learning, influencing domestic institutions to adopt globally accepted AI ethics and standards. This has encouraged the development of AI start-ups and skill-based programs aligned with international models. However, institutional inertia, weak enforcement mechanisms, and limited alignment between global expectations and local realities slow Nigeria’s progress toward a robust and accountable AI governance framework.

Methodology

Research Design and Methods of Data Collection

The study is the ex post facto research design. According to Kerlinger (1973), ex post facto research involves the study of "causal relationships between independent and dependent variables when manipulation of the independent variable is not possible." Furthermore, the study adopted a documentary method of data collection. The documentary approach is classified as an indirect methodology, relying solely on secondary sources for information.

Methods of Data Analysis

The study relied on content analysis for its method of data analysis. Content analysis is a method of data analysis widely used in various research fields, including sociology, psychology, media studies, marketing, and political science. It involves systematically examining qualitative data to identify patterns, themes, or trends within the content. The process typically begins with clearly defining research objectives, which serve as the foundation for subsequent steps. Researchers then select the type of content they want to analyze, which can range from text and audio to video and images.

Government Investment in AI R&D and Nigeria's Participation in Global AI Technology Governance Forums

Government investment in Artificial Intelligence Research and Development (AI R&D) is a critical determinant of a country’s capacity to participate meaningfully in global technology and governance forums. In Nigeria, evidence shows that between 2015 and 2023, national investment in R&D remained consistently low, severely limiting the country’s ability to produce research-driven contributions to AI platforms. According to World Bank data, Nigeria’s Gross Expenditure on Research and Development (GERD) remained around 0.2% to 0.3% of GDP throughout this period, far below the global average of approximately 2%. This disparity illustrates the persistent underfunding of Nigeria’s research and innovation infrastructure, which includes laboratories, university-based AI research centers, and public sector AI laboratories (World Bank, n.d.; UNESCO, 2021).

Table 1: Nigeria's GERD and Global Average GERD

Year	Nigeria GERD (% GDP)	Global Average GERD (% of GDP)
2015	0.22	2.0
2016	0.23	2.1
2017	0.25	2.0
2018	0.24	2.1
2019	0.26	2.2
2020	0.28	2.1
2021	0.29	2.3
2022	0.30	2.2
2023	0.30	2.3

Source: World Bank (n.d.); UNESCO (2021); WIPO & Global Innovation Index (2023)

As shown in table 1, Nigeria’s GERD has remained stagnant at under 0.3%, illustrating minimal growth over nearly a decade. This level of investment is insufficient to support high-quality AI research, train skilled AI engineers, or fund experimental AI projects. By contrast, the global average of 2% indicates that many countries are investing at least 6–10 times more in R&D, allowing them to produce competitive AI research outputs, host laboratories with advanced computing infrastructure, and actively shape AI governance discussions with technical evidence.

The persistent stagnation of Nigeria’s Gross Expenditure on Research and Development (GERD) below 0.3% of GDP reflects a structural underinvestment in knowledge production that has deep historical roots. Scholars argue that R&D investment is strongly correlated with national innovation systems, institutional maturity, and the capacity to produce frontier technologies (Lundvall, 2007; Edquist, 2011). Countries such as South Korea, China, and Singapore, which now play dominant roles in global AI technology and governance, systematically increased their GERD from the 1980s onward, allowing them to develop strong scientific communities, attract global talent, and build internationally competitive AI research hubs (OECD, 2020). In contrast, Nigeria’s R&D landscape remained weakly coordinated, poorly funded, and highly dependent on international donors, limiting its ability to generate sustained research output or maintain cutting-edge AI laboratories (UNECA, 2019).

A deeper examination reveals that Nigeria’s R&D expenditure has not only been low but also unstable, with limited multiyear budgetary commitments. According to UNESCO’s 2021 Science Report, countries with GERD above 1% of GDP typically demonstrate strong nationally coordinated research frameworks, strategic research agendas, and structured funding mechanisms for emerging technologies, including AI. Nigeria, however, lacked a long-term national AI research plan between 2013 and 2023, leaving universities and research institutes to pursue fragmented and donor-driven AI projects (UNESCO, 2021). This fragmented ecosystem reduces the international visibility of Nigerian AI scholars and limits the country’s capacity to contribute meaningfully to global technical working groups, expert panels, and governance forums.

The consequences of low GERD for AI-specific research are profound. AI research requires sophisticated computing infrastructure, high-performance processors, stable electricity supply, and continuous funding for data acquisition, algorithm development, and peer-reviewed publication. Yet, Nigerian universities and research institutes face chronic underfunding, dilapidated laboratories, inadequate broadband capacity, and unstable electricity, the very conditions that undermine AI experimentation (NITDA, 2020; AUC/OECD, 2021). While private-sector actors such as fintech companies and telecommunications firms have made incremental investments in AI-enabled services, these efforts remain commercially focused and do not substitute for state-led R&D investment required for national-level scientific advancements (GSMA, 2022).

Thus, the low GERD figures do not merely indicate underfunding; they also reflect the structural weakness of Nigeria’s broader innovation system. Without a supportive research environment, characterized by competitive grants, stable funding cycles, and world-class research infrastructure, Nigeria cannot produce high-impact AI outputs, participate in global AI benchmarking exercises, or shape norm-setting processes at multilateral levels (World Bank, 2018; WIPO, 2023). This is why Nigeria’s role in global AI technology governance forums often gravitates toward political, ethical, and regulatory discussions rather than technical contributions grounded in empirical AI research.

Hosting the UNESCO Regional AI Forum in Abuja in 2023 symbolized Nigeria’s diplomatic visibility but simultaneously underscored the paradox between the country’s political ambition and its technological limitations. Reports from the UNESCO Regional Office indicated that although Nigeria successfully facilitated deliberations on AI ethics, regulatory alignment, and Africa-specific AI challenges, it did not present significant technical research contributions during the forum (UNESCO Regional Office, Abuja 2022). Many technical demonstrations at the event were led by delegates from South Africa, Kenya, Rwanda, and Egypt, countries with comparatively stronger AI research ecosystems and higher R&D investment levels (AUC/OECD, 2021).

Nigeria’s contributions remained largely normative, emphasizing the ethical dimensions of AI, concerns about digital divides, and the need for inclusive AI governance in Africa. While these themes are essential, their predominance also reveals Nigeria’s limited capacity to influence technology-intensive aspects of global debates, such as algorithmic auditing, data governance standards, AI safety frameworks, and the design of machine-learning systems for public-sector use (Cave & Dignum, 2019; Future of Humanity Institute, 2020). According to scholars of science diplomacy, countries with limited technical capacity often compensate through active policy engagement; however, this rarely translates into long-term influence within technical governance bodies (Gluckman et al., 2017).

Furthermore, Nigeria’s role as host did not transform into long-term institution-building. Unlike Rwanda which used international events to establish AI centres of excellence and long-term research funding pipelines Nigeria did not announce any new AI research initiatives, national AI funds, or strategic partnerships that would elevate its research capacity post-forum (Smart Africa, 2023). As a result, the forum served more as a diplomatic achievement than a scientific milestone. This reinforces the argument that Nigeria’s participation in global AI governance is heavily skewed toward visibility rather than substantive technical engagement.

Global innovation assessments such as the Global Innovation Index (GII) consistently place Nigeria among countries with low knowledge production, weak infrastructure, and limited high-technology exports (WIPO & GII, 2023). These indicators are directly linked to GERD levels. Countries that dominate global AI governance such as the United States, China, Germany, and Japan, are also those with the highest GERD spending, enabling them to set standards, fund global research collaborations, and shape multilateral AI frameworks through scientific evidence (OECD, 2020).

Nigeria’s limited R&D investment thus systematically constrains its ability to influence technical agenda-setting within organizations such as the OECD AI Policy Observatory, the Global Partnership on Artificial Intelligence (GPAI), and the International Telecommunication Union (ITU). While Nigeria occasionally participates in these bodies, its contributions largely reflect policy perspectives rather than technical reports, empirical studies, or AI prototypes that carry significant weight in global discussions (ITU, 2022; GPAI, 2023). Consequently, Nigeria remains at the margins of global AI governance hierarchies, occupying a position more akin to a policy taker rather than a policy maker.

The lack of strong domestic research output also prevents Nigeria from forming effective coalitions with other technologically advanced African states. South Africa and Rwanda, for example, have leveraged stronger GERD investments to attract global AI partners, develop AI institutes, and publish peer-reviewed AI research thereby strengthening their bargaining power in global negotiations (AUC/OECD, 2021). Nigeria’s weaker research foundation leaves it unable to align with these states on an equal footing, reducing its influence on continental AI strategies such as the African Union's Continental AI Strategy launched in 2022.

Despite this low domestic R&D capacity, Nigeria maintained a visible presence in regional and global AI forums. For example, UNESCO’s 2023 report highlighted that Nigeria hosted the Regional AI Forum in Abuja, attended by delegates from over 30 African countries. However, analyses of the forum’s outcomes indicate that Nigeria’s contributions were largely policy-oriented, focusing on AI governance frameworks, ethical considerations, and regulatory discussions, rather than technical presentations or research-driven insights (UNESCO Regional Office, Abuja, 2022). This pattern is consistent with the observation that low national R&D investment limits the country’s ability to generate peer-reviewed research, prototype AI solutions, or deliver high-level technical presentations at international forums (RAND Corporation, 2005; OECD, 2007; WHO/ESSENCE, 2020).

Further evidence comes from global innovation assessments, such as the Global Innovation Index, which consistently ranks Nigeria low in knowledge production, high-technology exports, and research output. These limitations directly affect Nigeria’s technical influence in AI governance, leaving the country largely confined to normative and policy discussions, rather than contributing research-backed technical leadership (WIPO & Global Innovation Index, 2023).

Taken together, Nigeria’s low GERD levels, weak institutional support, and reliance on foreign partners reveal that domestic investment in AI R&D remained insufficient throughout 2013–2023. This underinvestment forms the foundation of the argument that Nigeria cannot substantially influence, nor fully participate in, global AI governance processes because it lacks the research capacity, technological outputs, and institutional strength required to engage as an equal actor.

Overall, the data and qualitative evidence strongly support the hypotheses that government investment in AI Research and Development has not influenced Nigeria’s participation in global AI technology and governance forums. Nigeria’s underinvestment in R&D has restricted the production of AI knowledge, constrained research collaborations, and limited the technical quality of its contributions, resulting in a presence that is diplomatically visible but scientifically marginal.

Another major barrier to Nigeria’s effective participation in global AI forums is its extremely low density of researchers. The World Bank (2021) reports that Nigeria sustained fewer than 150 researchers per million people between 2013 and 2023 a figure far below global innovation leaders such as South Korea (8,100), the United States (4,500), and China (1,300). This structural shortage severely constrains Nigeria’s ability to produce AI innovations, contribute to global standards-setting processes, or meaningfully influence international AI policies. The small number of researchers also means that Nigeria lacks the critical mass necessary to create a self-sustaining AI research ecosystem.

Low researcher density and reliance on external technical assistance have clear implications for Nigeria’s influence in global AI governance. With fewer than 150 researchers per million, the country cannot generate substantial AI research outputs or prototype innovations independently (World Bank, 2021; Synthesis Report, n.d.). Consequently, Nigeria’s contributions to international AI discussions tend to focus on normative and policy matters, leaving technical agenda-setting and research-driven leadership largely to countries with more robust domestic R&D systems.

Beyond financial underinvestment, Nigeria’s R&D landscape is characterised by systemic institutional weaknesses. Oyewole (2022) found that most Nigerian universities lack structured AI research clusters, interdisciplinary laboratories, or sustained funding streams dedicated specifically to machine learning or natural language processing. This infrastructural deficit undermines Nigeria’s capacity to domesticate global AI innovations or meaningfully contribute to international AI governance debates. Talabi (2021) further argues that the underfunding contributes directly to brain drain, as talented Nigerian scientists and engineers migrate to Europe, North America, and Asia in search of better financing and research environments. Such talent losses exacerbate Nigeria’s domestic capacity gap, further weakening its presence in global AI discussions.

Nigeria’s ability to participate effectively in global AI technology and governance forums is heavily influenced by domestic research and technical capacity. The country’s low scientific manpower and underfunded research environment have significantly constrained its ability to make independent, technically grounded contributions.

Table 2 shows Nigeria’s researcher density for selected years between 2013 and 2023:

Year	Researchers per million people	Global bench mark per million
2013	120	1,050
2015	130	1,080
2017	135	1,100
2019	142	1,150
2021	145	1,180
2023	148	1,200

Source: Synthesis Report (n.d.); World Bank (2021)

The table illustrates that despite small incremental growth, Nigeria’s researcher density remained critically low, limiting the country’s ability to generate AI expertise domestically. National policy documents, such as the Federal Ministry of Communications, Innovation & Digital Economy Strategic Blueprint, acknowledge the need for expanding technical talent, but as of the early 2020s, the domestic researcher base was insufficient to support high-level AI R&D (FMCIDE, 2023).

Across the 2013–2023 period, Nigeria’s R&D funding was not only low but also unstable. According to the World Bank (2021), annual budget allocations for science and technology were often revised downward due to competing priorities, particularly debt servicing and recurrent expenditures. As a result, research institutions lacked the consistent financing needed to sustain long-term projects or purchase modern equipment. Adedeji (2021) notes that even Nigeria’s top universities operate with obsolete laboratories, limited access to high-performance computing, and unreliable internet infrastructure all of which constrain AI research. Consequently, Nigerian researchers largely depend on personal funds, foreign scholarships, or donor-supported programmes to conduct research (Nwankwo, 2022). This reliance on external sources creates an uneven environment where local research priorities often yield to donor agendas.

The scarcity of domestic AI research capacity has affected Nigeria’s contributions in international AI policy workshops. Reports indicate that between 2021 and 2023, Nigerian delegations frequently relied on external technical assistance to engage in technical discussions and policy recommendations (United Nations, 2023). This reliance stems from underfunded research institutions and a small pool of trained AI researchers, which limited Nigeria’s ability to independently provide expert technical positions in global governance debates (FMCIDE, 2023).

This pattern of dependence also affects Nigeria’s credibility in global governance discussions. Cath et al. (2018) emphasise that global AI governance forums require not only political representation but also advanced scientific expertise capable of shaping norms, standards, and technical protocols. Without these competencies, countries risk being relegated to passive recipients of global AI standards rather than active co-creators. Nigeria’s repeated reliance on external experts illustrates this challenge. Furthermore, the absence of domestic AI research laboratories with global recognition unlike institutions such as DeepMind (UK), OpenAI (US), or CASIA (China) means Nigeria does not possess the scientific authority needed to shape global AI discussions.

Nigeria’s human-capital limitations also produce long-term structural consequences. The scarcity of researchers per capita slows down innovation cycles, reduces opportunities for technological experimentation, and makes it difficult for the country to generate high-quality evidence needed for policymaking. As a result, Nigeria tends to adopt global AI norms rather than negotiate or influence them. This situation demonstrates that even if the Nigerian government increases participation in diplomatic forums, without strong R&D investment and researcher capacity, such participation remains symbolic rather than substantive.

The National Artificial Intelligence Strategy also emphasizes international collaboration to complement domestic capacity-building efforts, indicating that Nigeria’s research infrastructure alone cannot currently support fully autonomous technical contributions (FMCIDE, 2023). These patterns demonstrate that while Nigeria participates actively in AI governance forums, its role is often policy-oriented, rather than driven by empirical research or technical innovation.

Nigeria’s low researcher density is further compounded by the limited number of specialised AI programmes across universities and research institutions. During the period from 2013 to 2023, only a small subset of Nigerian tertiary institutions offered structured machine learning or data science courses, and even fewer maintained graduate-level AI laboratories capable of conducting cutting-edge research (Adeleye, 2020). As a result, the national pipeline for AI researchers remains weak. This stands in stark contrast to global AI leaders, where national strategies explicitly prioritise talent development. For example, China’s New Generation AI Development Plan (2017) invests heavily in training tens of thousands of AI specialists annually, while the United States maintains a strong ecosystem linking universities, federal agencies, and private sector R&D (Zhang, 2020). Nigeria’s inability to replicate such structures reflects both financial limitations and institutional fragmentation, leaving the country dependent on sporadic short-term training initiatives rather than sustained capacity-building.

Moreover, Nigeria’s research ecosystem lacks strong university–industry linkages, which are essential for translating research into AI applications. In many countries, such collaborations serve as the backbone of national innovation systems, connecting academic expertise with private-sector funding and technological resources. However, in Nigeria, industries often rely on imported technologies and foreign technical partners because domestic institutions cannot meet their needs (Onwudiwe, 2021). This limited interaction reduces opportunities for researchers to engage in industry-driven AI projects, which are crucial for building expertise and generating innovation outputs that could, in turn, enhance Nigeria’s standing in global governance forums. The absence of such collaboration perpetuates a cycle where under-resourced universities produce under-prepared graduates, who then lack the capacity to engage in international AI debates at a technical level.

Another critical dimension is the persistent inadequacy in Nigeria’s digital research infrastructure. High-performance computing (HPC), cloud servers, and large-scale datasets are essential components of modern AI research. Yet several studies highlight that Nigerian research institutions struggle with basic infrastructure, including stable electricity and high-speed internet connectivity (Adedeji, 2021; Nwankwo, 2022). Without such infrastructure, researchers cannot run advanced experiments, model large datasets, or participate in cross-border collaborative research, which increasingly relies on shared digital platforms. By comparison, global leaders such as the European Union fund large-scale computing networks like EuroHPC to support AI innovation and ensure that researchers can contribute effectively to international dialogues on AI safety, regulation, and standards (European Commission, 2020). Nigeria’s infrastructural limitations therefore restrict not only research outputs but also opportunities for scientists to contribute empirical evidence in global forums.

The country’s reliance on donor-driven research frameworks also carries deeper structural implications. While external funding from institutions such as UNESCO, the United Nation's Development Programme (UNDP), and the World Bank has supported capacity-building programmes, these initiatives often shape national research priorities more than domestic policy does (Akinboade, 2020). This misalignment can weaken Nigeria’s long-term strategic autonomy in AI, as national agendas become dependent on the objectives of external partners. In global governance settings, countries with strong domestic evidence bases and autonomous research trajectories tend to exert greater influence (Cath et al., 2018). Nigeria, however, struggles to assert such influence because many of its research activities are responsive to donor programmes rather than driven by national AI priorities. This further reinforces Nigeria’s role as a recipient of global norms rather than an active co-designer.

Nigeria’s limited research capacity also affects the quality of its representation in multilateral AI forums. Delegates often include policymakers, diplomats, and administrators rather than technical experts capable of evaluating algorithmic standards, auditing frameworks, or data governance protocols (United Nations, 2023). While policymakers are essential for diplomacy, the absence of scientists and engineers means Nigeria’s contributions frequently remain general or political rather than technical. In contrast, countries like the United States, Singapore, Japan, and Canada routinely send delegations composed of both policymakers and AI specialists, thereby shaping discussions on technical standards, risk frameworks, and regulatory architecture (GPAI, 2022). Nigeria’s delegations, lacking similar technical depth, find it difficult to influence these discussions, leading to minimal impact on the direction of global AI governance.

Brain drain further intensifies Nigeria’s research capacity deficit. Talented Nigerian AI professionals often migrate to the United States, Canada, the United Kingdom, and Europe due to access to better research funding, well-equipped laboratories, and competitive salaries (Talabi, 2021). This migration deprives Nigeria of the highly skilled experts needed to lead national AI strategies or represent the country effectively in global governance settings. The African Union’s Digital Transformation Strategy (2020) notes that African states lose thousands of highly trained ICT professionals annually, undermining continental innovation. For Nigeria, which already has one of the continent’s lowest researcher densities, such losses weaken domestic AI ecosystems and reduce the pool of experts available for international engagement. The cumulative effect is a narrowed scientific base that cannot sustain the expertise needed to lead or significantly contribute to global AI policy discussions.

Furthermore, Nigeria’s weak domestic publication output in AI, evidenced by low citation impact and limited presence in high-ranking journals, constrains its global visibility. Countries that shape global AI governance often do so partly through scientific authority, demonstrated by strong publication records and internationally recognised research institutions (Zhang & Dafoe, 2019). Nigeria, however, contributes minimally to global AI literature, weakening its ability to project epistemic authority. This limitation reinforces the perception that Nigeria is not yet positioned to provide leadership in technical debates concerning AI governance, such as algorithmic transparency, evaluation benchmarks, or risk mitigation strategies.

Finally, the cumulative effect of these structural challenges is that Nigeria’s participation in global AI governance forums remains largely symbolic. The country attends conferences, signs declarations, and engages in diplomatic activities, but lacks the domestic technical capacity to shape discussions substantively. As evidenced throughout 2013–2023, Nigeria’s underinvestment in AI R&D, low researcher density, weak research infrastructure, and dependence on external technical assistance prevent it from translating political participation into scientific influence. As a result, Nigeria remains a policy consumer rather than a policy producer in the global AI governance landscape (FMCIDE, 2023; World Bank, 2021). This aligns with the overall hypotheses that government investment in AI R&D has not significantly influenced Nigeria’s ability to play a strategic or technically informed role in global AI technology and governance forums.

In conclusion, the evidence from 2013 to 2023 supports the hypotheses that government investment in AI R&D has not significantly influenced Nigeria’s participation in global AI technology and governance forums. Low domestic research capacity constrains technical contributions, resulting in engagement that is visible diplomatically but limited scientifically (FMCIDE, 2023; United Nations, 2023; World Bank, 2021; Synthesis Report, n.d.).

Effective participation in global AI technology and governance forums requires not only policy engagement but also demonstrable domestic innovation capacity. In Nigeria, the translation of public R&D investment into technology outputs has remained extremely limited, as reflected in patent activity data, which in turn has influenced the country’s technical contributions to international AI and digital governance dialogues.

Data from the World Intellectual Property Organization (WIPO) show that Nigeria recorded single-digit annual patent applications in advanced technologies, including AI-related inventions, throughout the period 2013–2023 (WIPO, 2022; WIPO, 2023). These low patent volumes indicate that public R&D investment has not effectively translated into tangible technological outputs. Nigeria’s limited patenting activity suggests weak domestic research commercialization, inadequate incentives for innovation, and a shortage of research-intensive institutions capable of producing high-tech solutions.

The single-digit patent pattern also highlights Nigeria’s structural weaknesses. Bello (2022) notes that Nigeria lacks effective technology transfer mechanisms within universities, meaning discoveries rarely progress from academic research to commercialisation. Similarly, Adebayo (2023) argues that Nigerian startups excel in software deployment but do not invest heavily in fundamental AI research that leads to patentable inventions. As a result, Nigeria remains primarily a consumer of foreign technologies rather than a producer of indigenous AI innovations.

Salami (2020) further contends that Africa’s technological dependence reinforces “algorithmic colonisation,” where foreign AI systems dominate local markets, shape data flows, and impose external design logics. This dynamic is reinforced by Nigeria’s weak patent production: with no strong domestic AI innovations to export, Nigeria plays no significant role in determining global ethical, technical, or regulatory standards.

Table 3: Patent Application Annually and Observation

Year	Total Patent application (residents + non residents)	Observation
2013	12	Low innovation output; mainly generic technologies
2016	9	Limited translation of R&D investment into patents
2019	11	Advanced technology patenting remains minimal
2022	8	AI-related inventions included but still marginal
2023	10	Slight improvement, but still negligible globally

Source: WIPO, 2022; WIPO, 2023

The consistently low number of patent applications highlights that domestic AI R&D remains under-supported, limiting Nigeria’s ability to generate research-driven technology outputs and competitive innovation.

The limited technological outputs have had a direct impact on Nigeria’s participation in global AI governance. During the UN Global Digital Compact (GDC) consultations in 2022, Nigeria delivered policy statements and regulatory recommendations on AI and digital technologies (United Nations, 2022). However, the country was unable to present national AI datasets, models, or research evidence due to the scarcity of domestically generated technology and insufficient R&D investment. This contrasts sharply with research-intensive countries, which contribute empirically grounded technical evidence, prototypes, and policy recommendations backed by robust data (United Nations, 2022).

Patent filings are important because they demonstrate not only creativity but also the ability of a research system to produce original and commercially valuable inventions. Countries such as China, South Korea, the United States, and Japan leverage patent activity to strengthen their positions in global AI governance. Their high patent volumes allow them to shape international intellectual property regimes, influence global standard-setting bodies, and negotiate regulatory frameworks to protect domestic industries (Zhang et al., 2021). Nigeria’s absence in patent-driven innovation therefore limits its bargaining power and visibility in global AI governance.

The combination of low patent activity and underfunded R&D means that Nigeria’s participation in global digital governance is primarily policy-oriented. While the country actively engages in normative discussions about AI ethics, regulation, and governance frameworks, its technical influence remains limited, as it cannot substantiate its policy positions with strong research outputs or national AI models. This situation reinforces the Hypotheses that government investment in AI R&D has not significantly enhanced Nigeria’s capacity to participate technically in global AI forums.

The evidence demonstrates a clear linkage between domestic innovation outputs and global influence in AI governance. Without increased government investment in AI research, support for patentable innovation, and incentives for technology commercialization, Nigeria is likely to remain dependent on international expertise for technical input, while its engagement in global AI governance will remain largely policy-driven. Strengthening patenting activity and AI-related R&D outputs is therefore critical to shifting Nigeria from a passive policy participant to an active, research-driven contributor in the international AI governance space (WIPO, 2022; United Nations, 2022).

Conclusion and Recommendations

The study concludes that between 2013 and 2023, Nigeria's engagement with artificial intelligence has been characterised by a significant disconnect between grassroots technological innovation and top-down governance integration. While the period saw notable advancements in Nigeria’s digital economy and AI startup ecosystem, the country has yet to develop a robust, ethical, and inclusive framework for AI governance that aligns with its national development goals and democratic values. Overall, the study underscores that Nigeria’s AI journey from 2013 to 2023 reflects broader patterns of digital inequality and governance challenges in the Global South. The absence of a coherent national AI strategy, coupled with weak regulatory enforcement and low digital literacy among policymakers, has left the country vulnerable to ethical risks, algorithmic biases, and foreign technological dominance. These factors collectively hinder Nigeria’s ability to harness AI for sustainable development and equitable governance. On this note, it recommends that the government strengthen its investment in AI research and development to enhance participation in global AI governance forums.

To transition from a passive observer to an active contributor in global AI governance, the Nigerian government must prioritise and significantly increase strategic investment in AI research and development. This investment should be channelled through a dedicated national AI research fund, administered by a revitalised and adequately resourced National Information Technology Development Agency (NITDA) in collaboration with the Ministry of Science, Technology, and Innovation. Specific actions should include establishing a National AI Research Institute: Create a flagship AI research institute with mandates to conduct cutting-edge research on AI ethics, safety, and applications tailored to Nigeria’s developmental context. This institute should partner with universities, tech hubs, and international research bodies and allocate sustainable funding: Earmark at least 0.5% of the national budget for AI R&D, with clear deliverables and accountability mechanisms. Funding should support long-term projects, PhD scholarships, and innovation grants focused on governance applications and develop a strategic AI diplomacy agenda: The Federal Ministry of Foreign Affairs, in conjunction with NITDA, should formulate a clear strategy for engaging in forums such as the Global Partnership on AI (GPAI), UNESCO, and the African Union’s AI initiatives. Nigeria should aim to co-chair working groups, contribute position papers, and advocate for inclusive governance models that address Global South concerns and build technical capacity within government. Train a cadre of AI-savvy diplomats, policymakers, and regulators who can effectively represent Nigeria’s interests in international negotiations and standard-setting processes.

By boosting domestic AI R&D capabilities, Nigeria will not only generate homegrown solutions to local problems but also gain the technical credibility and strategic leverage needed to influence global AI governance agendas.

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CONFERENCE PAPER

Raji, I. D., & Buolamwini, J. (2019). Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society (pp. 429–435).

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Exploring the Place of AI Administration and Democratic Governance in Nigeria

Introduction

BOOK CHAPTERS

CONFERENCE PAPER

OTHER ARTICLES

About The Author

Editor

Latest Posts

Search for More

EduPub Channel

📢 Follow EduPub on WhatsApp

Ads

Categories

Most Popular

Top Ten Books on Research Methodology

What is a Monograph?

A Silent Voice: A Journey of Redemption, Empathy, and Healing

Recent Posts

Categories

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📘 Publish with EduPub