Last week I participated in the Global Forum for AI and Social Sciences hosted by Florian Ostmann, The London School of Economics and Political Science (LSE) and the LSE Data Science Institute. The theme was AI and Labour. With a combination of keynotes from coal face leaders in the world, expert panels, lightning talks and provocation-led solution labs, the Forum was a hive of contentions and provocations for better work futures.
It’s clear that the global discourse on AI and the future of work is shifting from dramatic predictions of mass job loss toward a nuanced reality of structural reorganisation. While global evidence indicating that AI has not yet driven widespread net unemployment, AI is fundamentally altering task structures, entry-level recruitment, and the distribution of economic gains. For Africa, where labour markets are uniquely defined by high informality and systemic underemployment, navigating this transition requires moving beyond passive reskilling toward a proactive, policy-driven reshaping of the digital economy. Below is a cache of my notes and key takeaways:
1. The global landscape: Task restructuring and the aggregation paradox
Global analysis from the OECD – OCDE , International Labour Organization and International Monetary Fund demonstrates that while aggregate employment effects remain muted, workplace exposure to AI is widespread:
- Exposure operates primarily at the task level rather than replacing entire occupations. High-exposure roles include administrative, billing, data entry, and statistical support.
- Micro-level productivity gains from AI are substantial – particularly for lower-experienced workers – yet firm-level and macroeconomic productivity gains lag due to the “Productivity J-curve,” which requires complementary investments in organisational change, data infrastructure, and workforce capability.
- Career ladders are contracting at the bottom, with hiring for entry-level positions slowing globally due to shifting skill premiums, experience demands, and task automation.
2. The African imperative: Informality, structural demand, and the digital divide
On the African continent, the interaction between AI and labor diverges significantly from advanced economies due to structural market realities:
- Informal employment exceeds 90% across several African nations (informality in youth jobs is 4.8 times higher than in the rest of the world). While complex, multi-task informal roles (e.g., informal vendors managing physical procurement, logistics, and finance) are difficult to automate or code, informal workers remain exceptionally vulnerable to broader economic shocks.
- High data tariffs, internet poverty, and energy grid limitations delay rapid AI diffusion. While this infrastructure bottleneck temporarily cushions direct job displacement, it risks deepening the international digital and economic divide.
- Labour issues in Africa highlight a fundamental economic mismatch: capital-intensive growth sectors (e.g., extractives) fail to create sufficient formal (stable) jobs. Consequently, university and vocational graduates experience staggered transitions, underemployment, unwritten contracts, and job misalignment, demonstrating that skills supply alone cannot solve unemployment without structural labour demand.
3. Strategic policy levers for Africa
To prevent AI from exacerbating existing inequalities, African governments, trade unions, and civil society must deploy integrated policy frameworks spanning governance, fiscal policy, and worker empowerment:
A. Reframing the social contract and decent work
- Establish universal floors for labour rights and digital safeguards, enforcing transparency around algorithmic management, automated recruitment, and workplace surveillance.
- Expand social protection frameworks – including unemployment insurance, wage support, and universal benefits – to cover informal and non-standard workers transitioning across volatile labor markets.
B. Building worker power across the AI supply chain
- Recognise workers across the full AI lifecycle – from data annotators and supply chain workers to end-users – as critical agents in AI governance.
- Incorporate worker-led impact assessments, include public interest disclosure clauses in employment agreements, and independent (protected) dispute resolution mechanisms to protect workers economic integrity alongside whistleblowing protection measures.
- Broaden collectives of collective bargaining bodies to address political economy imbalances and negotiate equitable working conditions.
C. Fiscal mechanisms and value redistribution
- Explore tax base adaptations – such as windfall profit levies – to ensure that capital-intensive AI gains contribute to national revenues and social wealth funds.
- Develop bottom-up, AI-assisted public value remuneration models (e.g., rewarding community-led environmental, educational, care work or the broad base of transparency (data) work) to monetise verifiable social contributions.
D. Data infrastructure and regional autonomy
- Invest in national and regional data labs integrated into government data functions and scientific and industrial councils working with sector or skills councils to track occupational exposure, monitor real displacement trends, and inform higher education and sector skill planning.
- Foster public-private partnerships that focus on work-integrated learning and middle-skill GenAI applications tailored to local needs.
4. Actionable justice-centred policy pathways
Collective spaces such as the Global Forum for AI and Social Sciences are crucial for bridging the disconnect between abstract global AI principles and the realities of labour conditions. This timely convening provided a vital platform to interrogate how AI reshapes task structures, labour markets, and power dynamics across borders. It was a welcomed opportunity to share evidence from African labour markets – characterised by widespread informality, structural underemployment, and severe infrastructure and regulatory bottlenecks – in global arenas. Moreover, an opportunity to assess our Africa-focused public interest agenda focused on actionable, justice-centered labour policy pathways that uphold human rights, economic redistribution, and structural equity.
