Abstract
Globalization has impacted every sphere of human existence without exception. Today, even the authority to control within demarcated territories is being contested due to the artificial intelligence (AI) revolution. Influential and wealthy countries in the global north, directly and indirectly, through big technology corporations, are continuously exploiting African countries, dictating their affairs through the export of tech-driven services in health, education, governance, and agriculture. The purpose of this study is to further interrogate the status of Africa’s sovereignty in the era of AI. The article is anchored on digital colonialism theory. It is a qualitative study and utilized in-depth interviews to aggregate expert views from 20 interviewees within the broad spectrum of the AI ecosystem using an interview guide suitable for the objectives of the study. The study established the fact that the US, China, and Europe dominate the global AI ecosystem in terms of investment and governance framework. It found that digital colonialism, a term that explains the exploitation of Africa through tech-driven services and products and is largely responsible for the level of poverty across the continent, is a reversible reality. It identified Nigeria, Kenya, South Africa, Rwanda, and Egypt as Africa’s leading lights in the AI ecosystem, even as achievements remain fragmented and unrealistic. The study recommended the declaration of a state of emergency on AI, acknowledging the technology as an infrastructure of sovereignty.
Keywords
Introduction
Globally, the notion of sovereignty is undergoing refinement due to the fluctuating dynamics of geopolitics and technological transformation. The basic understanding of this concept emphasizes the exercise of constituted authority within defined boundaries (Sassen, 2006; Schmitt, 2005; Zielonka, 2006). But emerging dynamics of geopolitics and technological revolution are changing initial assumptions and understanding of the concept, and particularly for Africa, the conversations are molded by the continent’s infrastructural and technological background and historical antecedence. In the context of this study, therefore, sovereignty is defined as an entity’s authority to control resource allocation and infrastructure across diverse fields, including digital assets.
Fundamentally, Africa’s independence, like that in other climes, transcends previously held conceptions of sovereignty and extends into the realm of technological control and authority over the digital space. This is manifested today in the control of critical services that significantly impact human existence but are controlled overseas (Okocha & Edafewotu, 2022; Ray, 2025). This has given rise to the term referred to as digital colonialism. It reflects system dominance, data control, and the erosion of technological sovereignty, highlighting how foreign AI tools reinforce economic dependency and the lopsidedness in knowledge production (Kwet, 2019). A key feature of this trend is the misrepresentation of Africa’s values and peculiarities in the AI ecosystem. As a result, a significant proportion of the African population is technologically excluded as imported AI systems do not reflect local flavor (Artificial Intelligence [AI] for Development [AI4D], 2024; Financial Times, 2024). This leaves huge scars of marginalization due to systemic defects, regardless of the potential that positions the continent as the new frontier, as observed by Benyera (2021). In fact, digital colonialism, which also entrenches huge dependence on the global north and reflects digital exploitation across different sectors, including education, health, agriculture, and energy, among others, is largely responsible for the state of backwardness in Africa.
Additionally, emerging investment directions reflect the lopsidedness in the global AI industry. This level of marginalization is another manifestation of digital colonialism in Africa. As McKinsey and Company (2021) assert, Africa received less than 2% of inflows in 2020, accentuating its vulnerabilities and background. Affirming this view, Birhane (2020) argues that the 4IR, driven largely by AI, has become the defining marker of modern power and socio-economic transformation. Yet, African states are engaging from a position of weakness, often deploying externally developed technologies while losing control of the innovation and production processes that matter the most. This digital marginalization is rooted in Africa’s historical experience and also accounts for its current socio-economic state (Okocha & Faloseyi, 2025). Having been excluded from the benefits of the first three industrial revolutions due to colonialism and its aftermath, the continent now faces the risk of repeating this pattern in the AI era.
Evidently, infrastructural deficit is among the most critical obstacles. Munyati (2025) highlights that as of 2024, Africa hosted less than 1% of global data center capacity despite representing 18% of the world’s population. Most of the 150 active data centers are concentrated in South Africa, Nigeria, Kenya, and Egypt (White & Case LLP, 2025). While initiatives such as Microsoft-G42’s geothermal-powered facility in Kenya and the International Finance Corporation’s (IFC) 100 million dollars investment in Raxio are promising, their geographic concentration means vast regions remain digitally excluded (Reuters, 2025, 2024). Aragba-Akpore (2025) further notes that only 43% of Africans have internet access, with fixed broadband subscriptions below 0.5%, far below global standards. Equally pressing is the human capital and innovation gap. Although 1.25 billion dollars in AI venture capital has flowed into Africa, most funding targets the same Tier-1 countries where skilled talent is clustered (Oloyede, 2025).
At the same time, Africa loses an estimated 70,000 skilled tech workers annually to emigration (Ray, 2025), depleting its talent pool and deepening reliance on foreign expertise. Benyera (2021) argues that this reflects a new form of coloniality rooted in data extraction and algorithmic dependency rather than physical resource exploitation. Birhane (2020) terms this “algorithmic colonization,” where foreign-designed AI systems are deployed without sensitivity to local contexts, reinforcing dependence and digital subservience. The consequences extend beyond technical limitations to political and democratic governance. As Bakare (2025) and Okocha, Onobe, and John (2022) argue, Africa’s democratic institutions are increasingly vulnerable to manipulation by foreign digital platforms that harvest user data with minimal regulation or accountability. For example, Cheeseman et al. (2018) argue that the overreliance of electoral processes such as voter registration, voter verification and result transmission on imported technology rather than indigenous platforms may create significant opportunities for corruption and external interference in deciding the outcome of elections. This was evident in the recent elections conducted across Africa, specifically in Nigeria, Democratic Republic of Congo, Senegal, Kenya, South Africa and Tunisia, where outcomes were heavily disputed due to alleged misuse of the technologies (including AI) deployed by the institutions of state in the handling of electoral processes such as voter education, e-voting, result verification and collation (Omondi et al., 2024).
Nevertheless, modest progress is ongoing; some African governments and institutions are actively pursuing strategies to reclaim digital sovereignty. Senegal’s Senix internet exchange has localized domestic traffic, reducing reliance on international backbones (Digital Africa, 2023). Morocco has introduced progressive data localization laws and hosts the continent’s most powerful supercomputer (Abiodun, 2025). Rwanda and Ethiopia are investing in Tier 3/4 data centers powered by renewable energy and anchored by sovereign data frameworks. Nigeria’s Center for AI Excellence and proposals for a continental Digital Infrastructure Investment Fund further illustrate emerging commitments to localized innovation (Abiodun, 2025).
At the community level, innovative models are also gaining ground. Shared infrastructure approaches that integrate cloud services, rural electrification, and fiber connectivity are already operational in areas such as Buheesi, Uganda (World Economic Forum [WEF], 2025). These examples reflect the possibility of Afrocentric models of AI development rooted in local ownership, inclusivity, and sustainability. Yet, major obstacles remain, because policy frameworks at national, regional, and continental levels are ineffective and fragmented, while financing instruments remain inadequate. The huge gap in technical talent, combined with an overreliance on foreign technologies, highlights Africa’s digital future.
As the technological revolution is impacting all facets of human endeavor, redefining politics, resource allocation, and overall human relations across borders, Africa, with its profound systemic and structural defects as asserted by Stahl et al. (2023) and Okocha et al. (n.d.), continues to lag behind every other world region. Africa’s history of colonization accentuates this trend; its current overreliance on external aid, as asserted by Ekanem and Okolisah (2018); an ineffective and fragmented policy framework; inadequate financing instruments and investments; a huge gap in technical talent; and brain drain (Abiodun, 2025). This position, Birhane (2020) frames as “coloniality of data” or “techno-colonialism,” where Western-controlled AI systems impose foreign values and entrench subjugation. According to Salami (2024), such practices reflect the deeply entrenched digital dominance by the global north.
Moreso, the digital infrastructure gap has deepened this marginalization. As African Business (2024) reports, Africa hosts only 1% of global data center capacity, forcing reliance on foreign-owned platforms for data storage and processing, with implications for sovereignty and security. This is compounded by situations where Western AI firms extract African data without fair negotiation, perpetuating exploitative patterns that reflect the trend in the Fourth Industrial Revolution (4IR) (Kwet, 2019). Another manifestation of digital colonialism is in investment directions which underscore this divide as affirmed by Lu (2025), stating that nearly half a trillion dollars has been raised for AI in the United States more than the rest of the world combined (471 billion dollars versus 289 billion dollars) in contrast to Africa’s 1.1% of global AI investments in 2020 (Mckinsey & Company, 2021). Ade-Ibijola and Okonkwo (2023) and Salami (2024) warn that this unequal distribution risks making Africa a passive consumer rather than an active co-creator of AI innovation; however, the loss of governance, surveillance, and several cases of the establishment of centers of excellence across the continent (Nigeria, Kenya, South Africa and Egypt) demonstrate that the situation is redeemable. No doubt, development in the AI industry offers pathways for sustainable growth for Africa, hence countries in the continent cannot afford to be isolated in the scheme of things, especially as AI becomes increasingly embedded in global geopolitics.
Based on the above, the main objective of this study is to critically appraise Africa’s independence or autonomy across social, political and economic fronts, especially in the era of advancement in technology occasioned by the AI revolution. Specifically, the article seeks to: (a) ascertain the current global status of investment in AI; (b) establish the causes of Africa’s low participation in the AI industry; and (c) identify ways by which Africa can harness AI as a lever of empowerment and self-determination.
Theoretical Framework
Based on the objective to critically appraise Africa’s independence across social, political, and economic fronts, especially in the era of AI revolution, the study is anchored on the digital colonialism theory. Digital colonialism theory, as developed by Michael Kwet, Shoshana Zuboff, and Nick Couldry in 2019, explains how AI functions as a mechanism for the domination of Africa’s socio-economic wellbeing by powerful nations and corporations. The framework highlights platform hegemony, data ownership, and the erosion of technological sovereignty, stressing how imported AI tools reinforce economic dependency and global asymmetries in knowledge production (Kwet, 2019). As such, colonialism is synonymous with techno-imperialism or surveillance capitalism. Key tenets of this concept include ownership and control of data and the dynamics of geopolitics in the digital era.
Furthermore, Kwet (2019) argues that digital colonialism reflects colonial legacies, with tech giants in the West controlling the global south through the entire technology value chain, warning that the trend accentuates the imbalance that has reduced Africa to a “captive market” (Dahiya, 2023; Kwet, 2019). The reflections of Zuboff (2019) cover the concept of surveillance capitalism, where personal data is harvested with a view to predicting and manipulating behavior. She explains how this trend exacerbates lopsidedness and undermines democracy and sovereignty in the global south. Also, Couldry and Mejías (2019) explain data colonialism as a new form of resource extraction where the raw material is data rather than physical resources. They argue that digital infrastructures impose systemic control over people’s lives, replicating colonial domination by redefining space, labor, and social interaction.
In the context of this study, digital colonialism theory explains how African digital assets are exploited by global superpowers, often through proxies. It underscores Africa’s dependence on the global north for infrastructure, education, healthcare, and governance, providing a critical lens for understanding how AI risks accentuating suppression through technological dependence and surveillance.
According to the World Bank, availability and use of digital technologies are strongly linked to economic growth, innovation, job creation, and inclusion, at all levels of governance, yet Africa faces significant challenges in digital development (Digital Transformation, 2024). The report indicates that big tech companies continue to extract African digital assets for AI training and commercial purposes by creating value-added services and products for different uses, without providing proportionate economic returns or investing in the local industry. Moreover, the lopsidedness in broadband capacity, with a significant proportion of broadband infrastructure in Africa owned by non-African entities, enabling foreign control over digital communication lines (a form of digital colonialism), further exacerbates underdevelopment and poverty across Africa (Digital Transformation, 2024). Also, the advancement of education, which is a driver of socio-economic transformation, is negatively impacted by digital colonialism. This is because restrained innovation in local tech solutions and dependence on foreign platforms and cloud providers by African governments and businesses has worsened the trend of technological subordination (Kwet, 2019).
Relatedly, the exploitation of Africa’s weak digital laws by big Western multinationals to evade domestic regulations creates uneven playing grounds in the international tech markets at the expense of African countries (Dahiya, 2023). Beyond creating the environment for unfair competition, digital colonialism raises questions about whether African states truly govern their cyberspace, data, and technological systems, leading to the ideas of data sovereignty, network sovereignty, and algorithmic governance (Pierucci, 2025). Centered around ideas of the Sovereignty theory by Carl Schmitt, Saskia Sassen, and Zielonka, sovereignty theory provides a framework to assess how AI—largely developed outside Africa—threatens state autonomy over cyberspace and data, creating new dependencies and exclusions (Sassen, 2006; Schmitt, 2005; Zielonka, 2006). African countries’ overdependence on foreign technological products across different fields, which in many cases are in violation of domestic laws, represents a major violation of the country’s sovereignty.
This is further exacerbated by the continent’s low representation and participation in the global AI governance system, where guidelines are developed for participation in the ecosystem. This is partly why Africa remains poor and underdeveloped despite its huge potential. Digital Colonialism, supported by the sovereignty theory, provides insights into how the bypass of local laws and guidelines by big tech corporations for commercial gains and industry control violates the sovereignty of digitally colonized countries in the global south, including Africa, where ownership of broadband infrastructure and participation in global AI governance is abysmally low. By and large, digital colonialism further erodes Africa’s sovereignty because, rather than disappearing with political independence, sovereignty in the digital era adjusts to new realities and frameworks (Sassen, 2006).
Literature Review
Trends of Global Investment in AI
AI is augmenting slowly, but steadily, in recent times, attracting an unprecedented flow of investment in the industry. Muthusamy and Negi (2018) opine that central to all of the growth trajectories is the huge capital investments in key components of the AI value chain. According to Kariuki (2025, para 4), “corporate AI investment reached 252.3 billion dollars in 2024, with private investment climbing 44.5% and mergers and acquisitions up 12.1% from the previous year.” Current data, as reflected in Kariuki (2025), indicate a steady and consistent rise in private ventures over the past 10 years despite global instability.
However, global AI investments are unevenly distributed, with only a few countries (in the global north) accounting for a significant proportion of activities. For example, in reviewing key findings of Stanford’s 2024 AI Index on the economic impacts of AI in 2024, “Global trends in AI investment and enterprise deployment” (2025, para 4–5) affirms the United States’ lead in total AI private investment, stating that “In 2024, the 109.1 billion dollars invested in the US was 11.7 times greater than the amount invested in the next highest country - China and 24.1 times the amount invested in the United Kingdom.” Similarly, the trend is the same in public investment in AI. According to Kariuki (2025), the US takes the lead and is closely followed by the United Kingdom. Germany, Spain, and the UK set the pace for Europe’s top investors, while historically lowly ranked countries such as Romania, Greece, Hungary, and Poland have broken into the top 10, reflecting a balanced distribution of AI-related financing across Europe (Kariuki, 2025). But recent findings indicate significant efforts by the Chinese government, which is intentional in promoting the AI industry and initiatives, targeting to develop an AI sector worth 150 billion dollars by 2030 (Mou, 2019).
In the governance space, key countries and regions (particularly in the global north) in the AI ecosystem are at the forefront of pursuing solutions that align with their cultural, industrial and social aspirations (The State of AI in Africa Report, 2025). For example, the US, China, and Europe have separately hosted global AI forums to advance their interests and make valuable inputs in the global AI governance framework (Masood, 2025). In 2024, the European Union (EU) launched the EU AI Act, the first-ever act of this kind, to lead global AI governance (AI Act enters into force, 2024).
Evidently, the trend across Africa reeks of a reinvention of colonialism in the global south through the domination and control of digital technology by countries in the global north, also referred to as digital colonialism (Kwet, 2019). And some of the manifestations (of digital colonialism) include financing and participation in the tech industry, which Africa ranks very low in investment flow and strong governance processes, despite its huge potential. According to projections by the UN Economic Commission for Africa, cited in Osuagwu (2024, para 3), “if African businesses could capture 10% of the rapidly expanding global AI market estimated to contribute 15.7 trillion dollars to the global economy by 2030, the continent’s economy could grow by an impressive 1.5 trillion dollars.” But this remains an audacious vision as statistics show very low funding in the sector, with the continent accounting for just 1.1% of the global average as of 2020 (McKinsey & Company, 2021). Also, major investments, such as Microsoft-G42’s 1 billion-dollar geothermal-powered facility in Kenya and IFC’s 100-million-dollar partnership with Raxio across six countries, remain limited in geographic scope and benefit only select regions in the continent (Reuters, 2025).
Africa’s Participation in the AI Industry
Hardcore empirical evidence is not required to substantiate the imbalance in AI investment and governance. Indeed, Africa’s share of the global AI industry is relatively insignificant compared with its population. For instance, with about 18% of the world’s population as of 2024, Africa hosted less than 1% of global data center capacity (Munyati, 2025), and it received only 2% of inflows in global AI investments in 2020 (McKinsey & Company, 2021). But as Africa continues to take the back seat in the current setting, scholars and tech utopians on the continent have identified key causative factors as well as drivers for the emancipation of Africa (Majesty & Yinka-Banjo, 2025). It is, however, important to properly situate Africa’s position in the global AI industry in terms of governance, having established the investment flows in the sector across the continent. In further driving this conversation, it is pertinent to note that the major factors responsible for Africa’s low participation in the AI industry include inadequate representation of the continent in the global AI governance framework; funding structure in the AI ecosystem; weak governance framework; and unclear policy direction, which hinders adoption and innovation of AI (State of AI in Africa Report, 2025). In fact, Whyte (2020) opines that the global south, including Africa, faces significant power imbalances when engaging with multinational corporations and global governance platforms.
Strategically, Africa is largely excluded and unfairly represented in the global AI governance framework, which is important in guiding policy formation, investment direction, wealth creation and general infrastructure distribution in the ecosystem. An overview of documents on global AI governance in recent years, focusing on AI ethics, principles, roadmap, management systems, models development and adoption, among others, supports the view about the exclusion of Africa in the scheme of things (The Research Report on Global AI Governance, 2025). For example, Musoni (2024) and Majesty and Yinka-Banjo (2025), assert that Africa’s low participation in 26 Global AI Governance Fora between 2019 and 2024, including the G7 summit of AI in 2023; The Global AI Security Summit in 2024; World Internet Conference in 2023 and the World Artificial Intelligence Conference in 2024, among others, account for its backwardness in AI adoption and integration.
Also, the funding in the AI ecosystem, which follows a rigorous process of planning and execution, does not prioritize African peculiarities and context. This is one of the manifestations of digital colonialism in Africa because not prioritizing the African context in planning means the continent will perpetually depend on outsiders for tech products and services while being controlled by the West and its proxies. The State of AI in Africa Report (2025) and the Geopolitical Risk Index (2025) reflect this reality, indicating an investment from global tech companies that are based outside of the continent and primarily focus on infrastructure development rather than engendering local innovation and adoption (Whyte, 2020). Additionally, beyond the endemic problems of poor internet penetration, energy and legacy issues, Ade-Ibijola and Okonkwo (2023) argue that the skilled manpower behind the technological revolution is concentrated in wealthy and developed countries. According to Khattab (2024, para 4), “Israel has over 140 scientists and technicians per 10,000 employees, which is one of the highest ratios in the world.” Relatedly, Emaojo (2025, para 12) states that “US dominates in AI research output, creating 61 significant AI models in 2023, leaving the EU and China with 21 and 15, respectively. Meanwhile, just 5% of Africa’s AI talent has access to the relevant computing resources.” However, situations across the continent affirm a position among economists on the impact of AI and the possibility of increasing inequality (Ade-Ibijola & Okonkwo, 2023; Okocha, Onobe, & Alike, 2022).
But there are success stories that indicate a not-too-gloomy future for the continent. Several countries, Bakare (2025) asserts, are reforming the ecosystem for improved innovation and adoption of technology. For example, Kenya is evolving as a regional hub for agriculture and climate adaptation. The State of AI in Africa Report (2025) shows notable growing momentum across the continent, with Kenya and South Africa taking strategic national approaches. The same trajectory is reported in West and Central Africa, where Nigeria, Ghana, and Senegal are making progress (Majesty & Yinka-Banjo, 2025; The State of AI in Africa Report, 2025).
In conclusion, Nigeria’s position on the continent is clearly articulated, given the quantum of reforms in the country. The State of AI in Africa Report (2025, p. 13) shows that “with over 400 AI-related startups, Nigeria stands out as the largest and most active AI ecosystem in West Africa.” It further listed some of the country’s leading data centers in the public and private sectors.
Developing an AI Governance and Investment Framework for Africa
Evidently, Africa’s peculiar socio-economic and cultural heritage has significantly influenced its development journey, specifically, its AI path. For example, the continent’s colonial legacies of economic inequality, poor infrastructure, and restricted educational opportunities are issues impeding its technological growth (Asongu & Nwachukwu, 2018; Okocha, Onobe, & Alike, 2022). In fact, Faluyi et al. (2025) opine that the global AI boom has been characterized predominantly by the narrative that “America invents, China scales, and Europe regulates.” In this context, Okocha et al. (n.d.) assert, however overlooks Africa’s potential for AI innovation, adaptation, and inclusive growth. Moreover, the current trend reveals a scenario of mixed fortunes with encouraging determination, ingenious adjustment, and underlying bottlenecks (Whyte, 2020). The continent’s youthful population that offers significant opportunities for AI development consolidates Africa’s position. Additionally, the increasing mobile phone penetration and internet access have created a fertile ground for AI innovation (Global System for Mobile Technology Association [GSMA], 2022). This affirms the assertion that the region is the new frontier for global digital control and governance.
In addition, Faluyi et al. (2025) argue that global AI research and development can be enriched by the continent’s rich linguistic and cultural diversity. Relatedly, the governance landscape in Africa is adapting to the technological shifts, as opined by Njoroge (2024), specifically on the adoption of the regional framework and the emergence of local policies. As observed by Orucho (2025), African countries are developing the necessary frameworks, indicating the growing government commitments to regulate and control the ecosystem. Clearly, these frameworks hold the key to a genuine AI revolution as they aim to emphasize African values, close the skills gap, and ensure ethical adoption of the technology. However, Bakare (2025) and Okocha and Edafewotu (2022) argue that there are serious concerns around the political will by leaders to translate policies into actions that reflect Africa’s diverse social and economic contexts.
Moreso, African countries are building the required policy environment to protect digital assets across the continent. Whyte (2020) reports that African countries are utilizing relevant regulations to address immediate challenges in adopting the technology. Majesty and Yinka-Banjo (2025) assert that Nigeria’s laws on data protection have provided the basis for managing AI’s impact. Enforcements of the laws have been recorded at different times as part of efforts to sanitize the operational environment. For instance, in July 2024, the Competition and Consumer Protection Tribunal upheld the $220 million fine on Meta by the Federal Competition and Consumer Protection Commission, for violating local data-protection laws (Violations, 2025). In the same vein, according to Faluyi et al. (2025, para 4), “in September 2024, a Kenyan court allowed a $1.6 billion lawsuit by former Facebook moderators who alleged unfair treatment under the country’s labor laws.” Scholars, Bor and Koech (2023) note, have proposed a tripartite strategy for achieving digital sovereignty: owning the computing infrastructure, governing and refining African data locally, and reversing brain drain through strategic talent investment. This model prioritizes culturally contextualized innovation and positions Africa not merely as a consumer but as a co-creator in the AI future.
From the foregoing, the increased attention on policy and investment shows that the continent’s AI ecosystem is evolving and undergoing a gradual transformation. However, progress remains uneven, as cited in the State of AI in Africa Report (2025) and affirmed by Marivate (2020). But as Africa strategizes for the international stage, Faluyi et al. (2025) and Okocha and Edafewotu (2022) believe that in adopting innovative technology for transformational development, entrenching social and cultural nuances remains vital. Clearly, the way forward lies in collaboration and synergy of resources and ideas.
Research Method
This article adopted the qualitative research method, using in-depth interviews as the instrument of primary data collection to critically appraise Africa’s sovereignty across social, political, and economic fronts, especially in the era of the AI revolution. The choice of in-depth interviews for this study was premised on its significant advantage in providing diverse and enriched perspectives to the discourse based on the interviewees’ knowledge and experience in the area of study. Hence, using a purposive sampling technique, the researchers selected 20 experts (interviewees) representing target interests within the broad spectrum of the AI ecosystem across Africa and beyond. They include agencies of the Nigerian government (three from National Information Technology Development Agency [NITDA]; two from the ECOWAS and one from the African Union Commission (Division on Science and Technology); line ministries (two from Ministry of Communication, Innovation and Digital Economy and one from Ministry of Foreign Affairs); eight academics in geopolitics, computer science and cybersecurity; four AI experts and developers. These experts/interviewees were coded (labeled) P1 to P20. The sample size is suitable for a study of this nature, as noted by scholars, including Okocha et al. (2025), who affirm that a sample size of between 15 and 20 participants in any study can validate the results, particularly in qualitative research. They also assert that in qualitative research, in-depth interviews are not concerned with the population but with the sample size.
For the study, the researchers developed an interview guide that was distributed both digitally and physically among the interviewees, after which the interviews were conducted over a period of 9 days from Tuesday, August 26, to Thursday, September 5, 2025. A revalidation session for 8 interviewees (15 minutes per interviewee) was conducted using a Samsung S24 ultra mobile phone to confirm the responses of the interviewees.
Data Analysis
Table 1 shows the demographic attributes of the interviewees, indicating a representation across the broad spectrum of the AI ecosystem, comprising academia and industry experts, and policy experts in the technology, international relations, and geopolitics fields. Out of the 20 interviewees, 9 had less than 5 years of experience in the subject matter area, while 11 had more than 5 years of experience. Also, 14 interviewees had postgraduate educational qualifications, while 13 were between 31 and 50 years old.
RO1: Ascertain the current global status of investment in AI.
Demographic Attributes of Interviewees.
In achieving the first objective of this study, the researchers sought to: (a) ascertain what AI means and its importance to nations in the 21st century; (b) identify the various components of AI; (c) establish the global trend in AI investment and Africa’s position in these projections; and (d) identify the major players in the industry.
Consequently, all 20 interviewees (P1 to P20) demonstrated vast knowledge of AI, its applications, and national importance. For example, P7 emphasized that “control and expertise over AI are increasingly becoming sources of geopolitical power, making AI investment and strategy a national imperative.” P8 described AI as “the new oil,” not only for its economic value but also because it structures global power, shaping military intelligence, financial markets, surveillance, and cultural narratives. AI is viewed as an infrastructure of sovereignty critical to competitiveness, security, and labor markets, framing the 21st-century digital era as a battleground for neo-colonialism and autonomy.
Regarding global investment, all interviewees affirmed the dominance of the United States and China in the AI race, creating a bifurcated global order (P8). They supported this with projections: P13 noted global AI investment exceeding trillions by 2030, estimating a 1.8 trillion-dollar market or 3–4 trillion dollars in infrastructure spending. P4 cited forecasts of 1.3 trillion dollars by 2030, while P15 projected the market growing from 244 billion dollars in 2025 to 1.81 trillion dollars by 2030, reaching 4.8 trillion dollars by 2033. P3 remarked, “The buzz and interest around AI has reached a crescendo.”
All agreed on major industry players, with seven interviewees (P1, P4, P6, P8, P9, P15) naming Google, Microsoft, Amazon, OpenAI, Alibaba, Baidu, Tencent, Huawei, DeepMind, and SAP. Influential AI leaders like Geoffrey Hinton and Elon Musk also shape the field. Most interviewees identified Kenya, Nigeria, South Africa, Egypt, and Rwanda as leading African adopters, though P3 expressed doubt about any African country standing out.
The findings indicate a lopsided investment trend, heavily favoring the global north, highlighting significant disparities in AI governance and investment between Africa and dominant global players.
RO2: Establish the causes of Africa’s low participation in the AI industry.
In the bid to achieve research objective 2, the researchers sought to know the following: (a) Establish what advantage(s) AI is giving to Western countries over African nations; (b) Determine the pattern of Africa’s participation in shaping or influencing AI governance processes; (c) Determine the consequences of lack of deliberate participation in global AI governance on Africa’s sovereignty; (d) Identify ways by which African countries are exploited by the Western nations using AI as a tool (e) and what the key obstacles to Africa’s comparatively low participation in the global AI industry are.
Consequently, 18 of the 20 interviewees clearly outlined the strategic advantages AI offers Western nations. P13 noted that “AI gives Western countries advantages in economic growth, military capability, healthcare, and education through advanced infrastructure, skilled talent, and massive investment.” P4 added that AI brings significant productivity gains (e.g., 0.5%–0.9% US labor boost through 2030), contributes 14.8% to North American GDP by 2030, and drives innovation in finance and manufacturing. The consensus links Africa’s lag to colonial legacies, low digital capacity, and inadequate investments in AI infrastructure.
Furthermore, all interviewees agreed that Africa has limited participation in global AI governance. 10 (P1–P9, P13) emphasized that this exclusion leaves Africa vulnerable to data commodification and profiling. P7 observed, “African participation is still a little above infancy … If they don’t invest, they will be left behind.” P3 bluntly stated, “I have not seen the footprint of Africa in AI governance.” According to P8, African representation is largely symbolic: “African voices are tokenized … not invited for agenda-setting.”
Additionally, 12 interviewees (P1, P2, P4, P7, P8, P9, P11, P12, P14, P16, P18, P20) discussed how Africa is exploited due to its limited role in AI development. P8 described multiple layers of digital exploitation, including data colonialism where African languages, health data, and biometrics are harvested without compensation, and surveillance outsourcing, where Western firms supply tools that empower authoritarianism while extracting citizen data. Also, Key barriers identified include lack of funding, weak policy frameworks, poor digital infrastructure, low STEM education quality, and corruption. P3 pointed to low tech penetration; P7 emphasized finance, policy gaps, and corruption.
From the foregoing, it is evident that Africa’s low AI participation stems from structural and systemic barriers. Without investment in infrastructure, skills, and inclusive governance, Africa risks deepening technological dependence and reinforcing digital colonialism.
RO3: Identify ways by which Africa can harness AI as a lever of empowerment and self-determination.
In this section, the researchers aimed to achieve objective 3 by seeking answers to the following questions: (a) Identify the enabling conditions required for reversing Africa’s current position in the AI industry; (b) Identify existing AI policies/ strategies for adoption at national, sub-regional and regional levels; (c) Propose priorities for Africa in addressing the continent’s challenges in AI adoption; (d) Propose ways by which AI can serve as a tool for advancing Africa’s sovereignty.
Fundamentally, all 20 interviewees (P1 to P20) agreed that Africa’s current position in the AI landscape is reversible through deliberate policies, strategic investments, and education reform. They believe that AI can be a transformative tool for the continent. P4 emphasized that “Africa’s position is reversible through strategic interventions,” citing its youthful population and natural resources as assets. P3 highlighted the need to scale investment in STEM education, while P7 noted that with intentional programs, AI can revolutionize healthcare, education, and agriculture without relying on GMOs.
Accordingly, several interviewees (P4, P15, P8, P9, P7, P19, P16) confirmed the existence of AI-related policies at various levels. However, P20 argued that “most of these policies are moribund and ineffective,” a sentiment echoed by P8, who said the African Union’s AI recognition within its digital transformation agenda lacks meaningful implementation. Sub-regional blocs like ECOWAS and SADC have not developed coherent AI strategies, and existing frameworks are often fragmented, underfunded, and reactive rather than visionary.
In addressing Africa’s AI adoption challenges, interviewees proposed phased, actionable priorities. For the short term (1–2 years), P4 suggested developing national AI strategies, investing in digital skills, and launching pilot AI projects in key sectors like agriculture. For the medium term (3–5 years), he proposed building infrastructure, supporting startups, and integrating AI into education and healthcare. For the long term (5+years), the focus should shift to establishing innovation ecosystems, ensuring ethical governance, and taking active roles in global AI discourse.
All interviewees agreed on the potential of AI to empower Africa and enhance its sovereignty. However, they emphasized prioritizing AI skill development, investing in infrastructure, creating contextual regulatory frameworks, and encouraging local innovation. P8 captured the vision by stating, “A Pan-African AI infrastructure could replace reliance on Western platforms. Local AI solutions tailored to African realities could reduce dependence on imported technologies and enable Africa to negotiate from a position of strength in global trade, diplomacy, and security.”
In conclusion, submissions by interviewees show significant improvement in investments in the global AI value chain, as the trend in the industry will continue to dictate every aspect of human endeavor. This presupposes that AI holds so much promise for Africa. It can advance the continent’s sovereignty, enable local innovation, strengthen data ownership, and foster self-reliant digital infrastructure. It can empower governments to improve services independently, support home-grown solutions tailored to local needs, and reduce reliance on foreign technology. However, Africa must make the right choices as it is currently not engaging global players on a level playing field.
Discussion of Findings
Arising from this study, key findings have drawn attention to Africa’s sovereignty in the era of AI, particularly current trends in the industry in terms of investment, governance framework and Africa’s low participation in the industry. The low participation and investment, lack of representation and contribution in the governance framework all reflect various aspects of digital colonialism in the continent. Findings align with the first objective, which showed the level of competition in the global AI industry, with the US and China dictating the pace in overall public and private sector investments, while Europe maintains leadership in policy formulation and regulation, and Africa conserves its status as a consumption-driven region, affirming the prevalence of digital colonialism.
Also, findings reveal the importance of AI to nations and show that modest efforts at scaling AI adoption across Africa are insignificant and that the continent may never catch up with the rest of the world, as standout performers or remarkable success stories do not exist. These findings align with the first objective of the study and are supported by “Global trends in AI investment and enterprise deployment” (2025) who reviewed Stanford’s 2024 AI Index on the economic impacts of AI in 2024, affirming United States’ lead in total AI private investment, and the assertion by Kariuki (2025), of the US lead with 831.0 million dollars during the period. Also, the findings of this study align with the content of the State of AI in Africa Report, 2025. The findings are further asserted by Michael Kwet, Shoshana Zuboff and Nick Couldry’s digital colonialism theory, which provides a useful interrogation of platform hegemony, data ownership, and lack of African technological sovereignty.
Furthermore, the second objective, which established factors for Africa’s low participation in the AI industry, aligned with findings of the study associated with poor funding, poor appreciation of the industry and colonial legacies as major factors responsible for Africa’s position. The findings also indicated the different ways in which Africa is being exploited by Western nations using AI. It also acknowledged why Africa’s sovereignty remains shaky despite the abundance of resources and potential across the continent. Most importantly, the findings of the research corroborate the assessments in the Research Report on Global AI Governance (2025); Musoni (2024), and Majesty and Yinka-Banjo (2025), on Africa’s position in the global AI governance system. The findings also align with the position of Bakare (2025) on the adoption of AI across Africa and its impact on democracy, the economy, and the general well-being of the people. The submissions of Faluyi et al. (2025) and Whyte (2020) on what Africa must do align with the findings of the study. Furthermore, the sovereignty theory as postulated by Schmitt, Sassen, and Zielonka lends credence to the findings of this study on Africa’s perpetual technological dependence on the West, undermining its sovereignty (autonomy and control of both physical and cyberspace).
Additionally, this article’s third objective aligns with findings of this study that showed differing opinion on Africa’s current position in the AI industry with majority opining that the current trend against Africa is reversible with intentional policies and targeted interventions, while one interviewee (P3) remaking that the continent’s current position is almost irreversible and that there are no standout examples of success stories when benchmarked against global standards. The findings of this research revealed that prioritizing AI skills, investing massively in infrastructure, building contextualized regulatory frameworks, and scaling investment in STEM education can revolutionize Africa’s AI industry. In the same vein, Faluyi et al. (2025), State of AI in Africa Report (2025) and Marivate (2020) perspectives on Africa’s AI landscape as an evolving field and undergoing gradual transformation align with the findings of this study.
Moreover, the digital colonialism theory and sovereignty theory affirm major findings captured under the third objective of this study, which highlighted how Africa can leverage AI for its socio-economic and political sovereignty. How Local AI solutions tailored to African realities could reduce dependence on imported healthcare, educational, and agricultural technologies. These findings are accentuated by the sovereignty theory, which provides a lens for viewing authority in a globalized world, and the digital colonialism theory, which highlights how digital technologies are defining sovereignty and power, and the possibility of building sustainable, effective and independent digital futures.
Basically, the findings of this study have highlighted gaps in policy, talent pool and infrastructure in the AI industry across the continent. For example, findings show that most African states lack effective national AI strategies, and regional blocs like the African Union have only begun preliminary consultations. It also revealed inadequate representation of the continent’s interests at global forums on AI. This requires a move away from colonial mentality and the adoption of long-term, synchronized investments across the continent. Africa must begin to seek indigenous solutions to its technological backwardness, adopting strategies that align with peculiarities across the continent. However, the findings did not show the estimated quantum of investment required to transform the AI landscape across Africa.
Conclusion
This study critically appraised Africa’s sovereignty (autonomy) across social, political and economic fronts, and at individual, national, regional and continental levels, especially in the era of rapid advancements in technology occasioned by the AI revolution. Specifically, the study sought to, among other targets, ascertain the current global status of investment in AI; establish the causes of Africa’s low participation in the AI industry, and identify ways by which Africa can harness AI as a lever of empowerment and self-determination.
Consequently, findings from 20 interviewees representing target interests within the broad spectrum of the AI ecosystem across Africa revealed worrying statistics about Africa’s future in the global AI industry, with some interviewees submitting that Africa may never attain full digital and economic autonomy (sovereignty) in an increasingly globalized, crisis-prone, and multipolar world. This viewpoint, supported by the position of other scholars on the subject matter, indicates that Africa may not attain the same status as some countries in the global north, but it can harness AI to improve governance, healthcare delivery, agriculture and education in African countries.
Nevertheless, findings of the study indicate that data colonialism is a reality and that the digital lopsidedness between Africa and the global north will persist, but Africa can negotiate a path that guarantees mutual benefits for its people and institutions, given the fact that the landscape across the continent is evolving and undergoing gradual transformation. This study also established a nexus between AI and sovereignty across multiple fronts. The findings also identify Nigeria, Egypt, Rwanda, Kenya, and South Africa as leading lights in Africa’s quest for digital autonomy. Modest efforts at national, regional and continental levels in framing effective strategies for AI adoption in Africa were also highlighted as key findings of the study.
Recommendations
From the foregoing, this study recommends the following:
Africa should declare a state of emergency in AI, acknowledging it as an infrastructure of sovereignty. National, regional and continental authorities such as ECOWAS, AU, SADC and national governments must harmonize resources and efforts in ensuring adequate representation/participation in the global AI governance system. African leaders adopt strategies and policies that will scale investments in indigenous AI models and frameworks.
Footnotes
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.