Labour mobility in Africa is defined by a large informal sector and low-skilled workforce, alongside a growing youth population of 420 million whose aspirations are increasingly oriented toward high-paying, globally connected digital work. The aspirations‒capabilities framework demonstrates how the rise of artificial intelligence (AI) is redefining the continent’s labour mobility landscape. It identifies four primary ways in which AI is shaping mobility on the continent: the involuntary immobility faced by low-skilled informal workers; the reshaping of aspirations through digital exposure; the enabling of virtual mobility; and the entrenching of global inequality and data colonialism.
The current trajectory of AI adoption will only exacerbate current socio-economic gaps and broader divides in technological advancement and development between Africa and the Global North, as AI models are designed to function extractively, using Africa’s labour and data without benefitting the populace. The paper’s recommendations centre African agency and recognize the institutional dimension of technological capabilities needed for AI, alongside the technology. This includes increased regional economic integration, leveraging indigenous knowledge and expanding the spread of mobile technology. These efforts must prioritize reducing existing structural inequalities and ensuring social protection for vulnerable groups, such as low-skilled migrants, to build the positive liberties needed to maximize AI.
Introduction
Labour mobility in Africa is shaped by structural drivers such as education, infrastructure and technology,1 which raise standards of living and create economic incentives that pull working-age populations to move in search of better livelihoods.2 Technological change, in particular with the rapid rise of AI,3 is redefining this landscape and the future of labour mobility on the continent.
AI holds the promise of generating labour demands in the emerging AI industry, boosting job prospects, productivity and wages in higher-income occupations and introducing new possibilities for virtual mobility.4,5 While this presents complementary benefits to workers in non-routine cognitive tasks highly exposed to AI, such as engineers or actuaries, it may increase income inequality6 as AI threatens the displacement of low- to middle-skilled workers in routine cognitive tasks, such as basic office support or customer service.7 It will also impact vulnerable informal workers who are likely to struggle to adapt.8
With only 38 percent of Africans having internet access, the rise of AI compounds the digital divide. In addition to this domestic inequality, increasing technological dependency on the Global North risks digital colonization, reinforcing global inequalities.9
Furthermore, technological transformation in Africa has lagged, which points to insufficient infrastructural and institutional capacity.10 The rise of AI means that urgent collective action by African governments is needed to harness the opportunities and mitigate the challenges that AI poses for labour mobility and the development of human capital.11
This paper contributes to understanding these intersections. It begins with an introduction and overview of the issue from the aspirations‒capabilities framework perspective. It then explores four key ways in which AI is shaping labour mobility in Africa, before discussing the policy landscape and concluding with recommendations.
Purpose and Scope of the Paper
African Union statistics indicate that labour mobility is increasing rapidly, with nine in 10 workers in sub-Saharan Africa working in informal employment and in non-technological sectors such as agriculture, trade in goods, and construction, which tend to be highly mobile. Furthermore, labour migration is significantly driven by young people.12 While there are approximately 420 million young Africans, with 10 to 12 million entering the workforce each year, only three million jobs are created annually.13
For this demographic, there is an aspiration for high-paying digital and globally connected work augmented by AI.14 There is a gap, however, between this desire and the reality of informal and low-skilled work that is available to them.15 Closing this aspiration gap is dependent on industrial and structural transformation, including strong macroeconomic policies and significant investments in infrastructure and human capital.16 The aspirations‒capabilities framework guides this paper and helps to identify the social, economic and political factors that influence labour mobility.17 This framework posits that mobility depends on aspirations to migrate and the capability to do so. It moves beyond reducing migration and labour mobility to simply cost-benefit calculations and recognizes the agency migrants have within existing structures.18
Through the lens of this framework, this paper highlights four ways in which the rise of AI shapes labour mobility in Africa: the involuntary immobility faced by low-skilled informal workers;19 the reshaping of aspirations through digital exposure;20 the enabling of virtual mobility;21 and the entrenching of global inequality and data colonialism.22
The purpose of this paper is to explore how AI shapes people’s aspirations for better livelihoods and the capacity of governments to support these aspirations within the landscape of constraints, such as the AI divide and lack of skills and infrastructure.
The Impacts of AI for Labour Mobility in Africa
Digital Involuntary Immobility and Low-Skilled Informal Workers
The aspirations‒capability framework emphasizes that human mobility is an expression of agency23 that is shaped by the interaction between positive liberties, such as education and digital skills,24 or negative liberties, such as migrant-exclusionary practices.25 Where there is deprivation of these liberties, the result is involuntary immobility. Labour mobility in Africa is often a response to labour demands in agriculture, the mining industry, and trade in goods as livelihood strategies for poor families.26 For these low-skilled workers, the rise of AI is a macro-structural change that disrupts their traditional livelihoods and, without the resources to transition, makes them immobile.27
AI is already being mobilized across the continent with AI-driven automation in low- and semi-skilled sectors such as textile and garment manufacturing, automotive roles such as welding and inspection, agriculture and broader entry-level and manual labour roles.28 While AI enables precision technologies, machine learning and satellite imagery, which help improve the efficiency of agricultural practices,29 it has the disadvantage of leading to the gradual displacement of workers, which may worsen economic exclusion if not managed properly. As labour migrants face a drop in employment prospects, a reduction in remittances follows, which affects the economic stability of their home countries.30
The African Union Continental AI Strategy highlights that, if leveraged, AI can improve people’s livelihoods, create jobs, foster innovation and advance the continent’s socio-economic transformation. It equally acknowledges that low-income individuals, as well as migrants, are more vulnerable to discrimination and exclusion in the digital economy.31 While designed to function as a capability-expanding intervention that provides positive liberties such as infrastructure development, workforce skilling and availability of African datasets,32 AI’s implementation has not helped create voluntary pathways of labour mobility.33
By 2030, 230 million jobs will require digital skills in sub-Saharan Africa.34 If the people needed for these jobs lack the positive liberties of education and skills training, the gap may breed secondary crises, including an increase in irregular migration,35 illegal survival strategies, human trafficking, exploitation and marginalization.36
AI Exposure and Reshaping Aspirations
The aspirations‒capability framework highlights that individuals’ migration aspirations are shaped by the perception of geographic opportunities available in both their home and desired countries. Technology is a key macro-structure that influences these perceptions,37 with a rapid flow of information on how AI-driven livelihoods can increase income and standards of living. Reflecting this trend, a report shows that 64 percent of workers in Africa use AI in their work, and there is a mix of curiosity, excitement and optimism about the future of AI in labour markets.38
While this digital exposure highlights the opportunities, it does not help to secure them. This structural gap is reflected by the same survey, which found that only 35 percent of those workers believe their current skills will remain relevant in the next three years.39 There is also concern about how technological advancements such as AI can subordinate indigenous knowledge systems,40 with modernization making those systems seem outdated or irrelevant, or simply data to be mined for AI.41
Historically, economic booms from certain industries have resulted in an overreliance on new technologies. There is therefore a need to ensure that the rise in the AI economy does not displace other vital aspects of economic development. For instance, expectations around AI may gradually erode younger generations’ aspirations, making lower-income livelihoods in fields such as agriculture seem less desirable than technological ones.42
Virtual Mobility
Another major way that AI is reshaping aspirations is by advancing voluntary immobility, where people are increasingly choosing to stay in their home countries due to opportunities provided by virtual mobility.43 Globalization is advancing virtual mobility with opportunities for remote work, digital outsourcing and broader transnational online employment. This democratizes opportunities where Africans can compete with peers from both the Global South and North, and it removes the socio-economic barriers that make traditional labour migration difficult.44
Some of these emerging dimensions of digital labour include data heteromation, where, due to low labour costs, African workers are employed for invisible tasks such as data entry, image annotation and SEO (search engine optimization) to power global AI systems.45 Furthermore, there are opportunities for micro-tasking, online freelancing and even professional remote work in fields such as accountancy and medical diagnosis.46 In addition, digital platforms such as YouTube and TikTok allow African filmmakers, musicians and content creators to monetize their work.47
These forms of labour are positively contributing to reducing unemployment on the continent, but due to a lack of bargaining power, workers may experience exploitation and job insecurity. Furthermore, they often face discrimination based on their national identity.48 As highlighted earlier, due to the AI divide, these opportunities are only available to a limited number of people. This friction is worsened by a lack of infrastructure, resulting in low internet access and erratic electricity supply.49
Global Inequalities and Data Colonialism
Labour mobility and building individual and national capabilities in Africa are closely linked to the private sector, which accounts for 80 percent of production and two-thirds of investment, and which employs 90 percent of the working population.50 The sector’s strategic interests in AI determine the adoption and investment in the countries in which they operate. In many developing countries, multinational corporations often pay lower wages, suppress labour unions and stifle local businesses.51 With the rise of AI, there are therefore concerns about the potential of AI to weaken the bargaining power of labour,52 along with concerns that it may further concentrate economic and political power in the hands of Global North corporations.53
This concentration of power is reinforced through data colonialism, a status quo where participation in the digital economy is inherently extractive and non-negotiable. This process commodifies human life into raw data to train AI models and generate profit.54 In Africa, this often occurs under the guise of altruism, where in the name of public benefit and convenience big corporations build digital connectivity infrastructure that harvests citizens’ data without consent, often with monopolistic control over users’ internet access and use of data. Thus, AI may perpetuate the reproduction of global inequalities, with Danielle Coleman, a scholar of AI governance, characterizing this as the “new scramble for Africa.”55
This monopolistic control limits the capability of African governments to build independent digital systems, which stifles local agency. The approach of multinational corporations is also prone to failure, as these corporations frequently ignore local African contexts and cultural norms. Furthermore, where AI tools are trained with poor and underrepresented datasets, they automate bias and perpetuate historical injustices.56 This exploitation also manifests as Africa is being used as a testing ground for harmful software due to weaker safeguards and regulations.57
Conclusion and Recommendations
The impact of AI on labour mobility in Africa is not technologically predetermined, but rather shaped by the political choices of stakeholders and their competing vested interests58 in the global market, which is driven by technological change, geoeconomic fragmentation, economic uncertainty, demographic shifts and the green transition.59 While the rise of AI promises unprecedented opportunities for labour mobility on the continent, it also risks creating new challenges and entrenching inequalities for vulnerable people60 such as women, children and irregular labour migrants.61 Ultimately, its success depends on the political will of national governments62 to build strong institutions63 and localize AU frameworks such as the African Continental Free Trade Area agreement,64 the Free Movement Protocol65 and the African Union Continental AI Strategy.66
The current trajectory, however, highlights a mismatch between the digital aspirations of labour and the structural capabilities on the continent.67 Current AI models are designed in the West to be capital and skill intensive, in contrast with African markets, where there is scarce capital and abundant low-skilled labour. Consequently, AI functions as an extractive industry that exports automation and inequality.68
To change this direction of technology and maximize the opportunities AI presents, it requires transitioning the continent from being a testing ground to centring African agency. This requires rejecting the blind techno-optimism that views all innovation as progress;69 instead, African stakeholders must actively redirect the tools of machine intelligence toward machine usefulness, translating them to solve local African problems and build the positive liberties of the citizenry. To maximize the benefits of AI for labour mobility in Africa, these underlying structural conditions must be addressed.70 This paper’s recommendations, therefore, include the following:
- Focus on structural inequalities and on building digital infrastructure: Inequality manifests across Africa through infrastructural disparities in access to necessities such as electricity, internet, mobile technology, and education, which leads to critical skills shortages.71 There is a need to tackle these gaps in rural connectivity first, as they restrict the capabilities of citizens and, ultimately, the government to benefit from the rise of AI. National governments should prioritize rural broadband expansion, working with telecommunications operators to subsidize cost, with the African Union acting as an oversight body to hold states accountable.
- Strengthen regional economic integration and indigenous knowledge flows: A significant amount of labour migration occurs informally within countries in the same region.72 Regional Economic Communities should effectively lead the implementation of the African Union’s Free Movement Protocol. Additionally, cooperation within Regional Economic Communities should include the co-creation of traditional knowledge datasets from shared indigenous practices. These can serve as the foundation for AI technology in their regions and reduce structural inequalities caused by the exclusion of African knowledge systems.
- Prioritize social protection for vulnerable groups: There is evidence that involuntary labour mobility in Africa disproportionately affects women and young people. Therefore, national and regional governments must pay special attention to ensuring social protection and safety nets such as AI training and literacy programs for skills development.73 These must be complemented by updated and strengthened regulatory frameworks for AI technologies and for employers to enforce basic fair-work standards,74 ensure that African labour is treated as a valuable asset, and to prevent data colonialism.
- Leverage mobile technology for digital inclusion: Although the continent has for many decades played catch-up in technological advancements, there is a strategic opportunity for leapfrogging with the rise of AI using mobile technology.75 While digital penetration remains low, around 66 percent of the African population owns a mobile phone.76 Governments should build on this existing system in the short term, using mobile-enabled AI applications for AI vocational training.
