I was compelled to write this after reading the Generative AI Outlook Report 2025 by the European Commission. It’s a dense, policy-rich document—but one section lingered with me long after I closed the tab: how generative AI is quietly reshaping Europe’s labour market, not just through job loss, but through a profound realignment of what “work” even means.
It made me wonder—what if the real disruption isn’t happening in Europe, but in the silence of the Global South?
Unlike Europe, where AI displaces white-collar efficiency jobs and triggers regulatory debates, the Global South is navigating a slower, more invisible erosion. We are not losing jobs to AI. We are losing opportunities to create better ones. While Europe fears the disappearance of professions, we risk missing the train entirely—relegated to being passive users of models built elsewhere, with values we did not shape, in languages we don’t speak.
Europe, for all its structural advantages, is still struggling to meet its digital skills targets. Only 55.6% of its adults possess basic digital skills (European Commission, 2024); women remain underrepresented in AI fields, comprising just 19.4% of ICT specialists (Eurostat, 2023). To address this, the EU has committed to ensuring that 80% of adults attain at least basic digital skills by 2030, doubling its current ICT workforce to 20 million, and integrating AI literacy into formal education through initiatives like the European Digital Education Hub and the draft AI Literacy Framework under consultation (European Commission, 2025). Even so, the continent has an AI Act, a literacy framework in development, and a clear vision: ensure AI does not deepen inequalities. That clarity, however flawed in execution, matters.
In contrast, the Global South faces a triple challenge:
- Infrastructure poverty—unreliable electricity, limited connectivity, and minimal compute capacity. For instance, only 43% of Africa’s population has access to reliable electricity, and internet penetration in Sub-Saharan Africa was just 37% in 2023 (ITU, 2023).
- Talent drain—our best minds migrate, while our youth use AI tools informally with no safeguards or training. In many Latin American countries, digital gender gaps persist, with up to 40% of women lacking access to the internet (UNESCO, 2024).
- Policy inertia—where digital literacy is still seen as a bonus, not a right. As of early 2024, only seven African nations have drafted national AI strategies (UNESCO, 2024).
Yet this isn’t just a lament. It’s also a unique window of possibility.
The World Bank has noted that AI’s disruption in the Global South will be slower and more limited—because of the prevalence of manual and informal labour (World Bank, 2024). That’s often seen as a disadvantage. But what if that’s our strategic leverage? This labour structure is heavily reliant on interpersonal interactions and community-based economies—factors that are more resistant to automation and harder to replicate with AI. In many regions, these social dynamics are not just economic features, but cultural backbones.
However, this also means that resistance to AI adoption can be high, driven by legitimate fears of job displacement and the devaluation of human-centric work. Without a clear and inclusive strategy to show how AI can augment rather than replace these roles, trust will be difficult to build. That’s why it’s essential to communicate AI’s role not as a substitute, but as a support for livelihoods grounded in relational and informal labour systems.
Instead of chasing automation, we could champion augmentation—designing AI to amplify, not erase, human contribution.
Instead of importing AI models, we could co-create them: small, cost-effective local language models (LLMs) that don’t require massive compute infrastructure, but are trained on local needs, dialects, and cultural nuance.
Instead of fearing AI, we could prepare our youth to shape it—by embedding it into the systems that already matter most: education, health, agriculture, and finance.
AI can help bridge long-standing development gaps if aligned with public needs. In agriculture, AI can predict planting seasons, optimize crop rotations, and anticipate livestock feed needs—improving food security while empowering farmers rather than replacing them. In education, it can personalize learning for students with limited teacher access. In healthcare, it can assist with early diagnosis in remote areas. And in financial services, AI can expand credit scoring models to reach informal workers and first-time entrepreneurs.
These are not utopian dreams—they’re practical augmentations, when guided by policy and driven by purpose. And this can only materialize if policymakers recognize their catalytic role—by designing the right incentives for local industry and investors, and by demystifying AI for the public. Consistent public education campaigns, media engagement, and inclusive messaging about AI as a tool for augmenting livelihoods—not replacing them—are essential. When AI is framed as a pathway to reduce poverty, boost productivity, and empower local actors, it reshapes public trust. Over time, this can shift the dominant narrative from suspicion and anxiety to confidence and co-ownership.
But before all that, what’s urgently missing is a strategic blueprint. Countries in the Global South must craft and communicate clear, measurable roadmaps for AI adoption—plans that are not just aspirational but rooted in their specific challenges and opportunities. Such frameworks are not only necessary for good governance; they’re crucial signals for businesses and investors seeking to understand where the value lies. Without a guiding strategy, even the most well-meaning actors will be flying blind.
Moreover, Global South stakeholders must remain highly attuned to the deeper social risks posed by AI adoption in their contexts—risks that may, in fact, outweigh those in the EU. The region faces a dangerous convergence of limited digital literacy, widening economic gaps, gender-based digital exclusion, and poor infrastructure. Women, for instance, are overrepresented in roles most vulnerable to AI automation and already face systemic barriers to digital access. Indigenous and Afro-descendant women, particularly in Latin America, suffer a “double disadvantage” due to structural poverty and cultural marginalization (UNESCO, 2024).
AI could also amplify misinformation and manipulation in contexts with low literacy and high social media penetration. Disinformation campaigns, deepfakes, and microtargeted political messaging may flourish in regions where ethical AI understanding is still embryonic. The absence of strong guardrails could lead to the disenfranchisement of entire populations—especially youth and the elderly—through invisible algorithmic bias or predatory data practices. Without robust education, ethical frameworks, and inclusive policies, the Global South risks deepening its digital divide.
This is why mitigation must begin now: with public education, with targeted AI literacy, with regulation that reflects context, and with long-term investments that prioritize inclusive access over flashy pilot projects.
- Invest in AI fundamentals—data centres, affordable internet, and offline-compatible models.
- Build human-AI hybrid skills—from farmers using AI for crop cycles, to artisans creating digital avatars.
- Design ethical governance not as Western mimicry, but as a development strategy rooted in our own values.
Let Europe debate guardrails. We need a bridge.
We don’t need to catch up to the North. We need to leap differently—using our constraints as creative fuel, our informality as a design opportunity, and our diversity as a blueprint for AI that actually serves.
If we act with intention now, by 2030 we won’t just be reacting to AI’s global tide. We’ll be steering our own current. And this isn’t just about us. It’s about everyone.
When social inequality deepens and trust in digital systems erodes in the Global South, the ripple effects are global. From forced migration caused by economic displacement or social unrest, to the cross-border spread of misinformation and AI misuse, the Global North will not be shielded from these impacts. Moreover, the vast majority of capital for AI development still originates from the Global North—yet the Global South remains its most open, untapped market. Investors hesitate not because of lack of potential, but because of instability and uncertainty.
That’s why closing the AI readiness gap isn’t charity—it’s global insurance. It’s about creating the conditions for shared growth, for mutual resilience, and for building a future where AI becomes a bridge, not a fracture line, between regions.
