Learning as a Wage Benefit

Training has always been an economic choice. Firms invest in skills when they expect retention, productivity gains, and a stable operating environment. When those conditions hold, training behaves like capital expenditure: it upgrades the workforce and returns value over time. When those conditions do not hold, training is treated as leakage: the worker learns, then leaves; the firm pays, then loses.

That logic has sharp consequences in the Global South. Where labour is informal, contracts are short, and firm financing is expensive, employers are structurally discouraged from investing in worker capability. This is one reason many economies can sustain employment while failing to sustain wage growth. People are busy. Skills are not compounding.

Automation intensifies the problem because the half-life of skills shortens. What was stable for a decade can become obsolete in two years. In such an environment, training is no longer an occasional event. It is a continuous wage benefit. Those inside stable firms receive it as part of compensation. Those outside must self-fund. The skills gap becomes a cash-flow gap.

Why Businesses Under-Train

Small and mid-sized firms in emerging markets face a blunt constraint: survival first. When working capital is tight, when input prices swing, when power cuts interrupt production, and when tax and regulatory processes are uncertain, managers behave defensively. They prioritise continuity over upgrading. Even when leaders recognise the value of training, the immediate environment makes training feel like a luxury.

There is also an institutional problem. In many countries, training systems are fragmented across ministries, donor programmes, and short-lived initiatives. Firms do not see a predictable pipeline of credentials that map to real job performance. Workers do not see training as portable and recognised. In that confusion, the cheapest strategy is to hire someone already trained, usually from the small pool of candidates with elite schooling or exposure abroad.

As a result, the labour market becomes a tournament: credentials screen access, networks decide entry, and on-the-job learning becomes an informal privilege rather than a formal system. Automation does not correct this. It rewards it.

AI Makes Skill Visible

In the pre-AI economy, a large share of knowledge work relied on scarcity. Access to information, software, libraries, and institutional mentoring created barriers that protected wages. Generative tools, code assistants, and low-cost automation are eroding those barriers. That might appear democratising. In practice it creates a new hierarchy: those who can use tools well accelerate; those who cannot are exposed.

The decisive differentiator becomes operational literacy: the ability to structure problems, verify outputs, understand trade-offs, and integrate tools into repeatable workflows. This is not the same as being good with computers. It is closer to professional judgement. It is learned through guided practice, and guided practice is most available in organisations that already have systems.

This is why automation can widen inequality even while lowering the cost of information. The bottleneck shifts from access to content to access to apprenticeship. In much of the Global South, apprenticeship is under-supplied.

Informality as a Training Trap

The informal economy is often described as entrepreneurial. It is also educationally constrained. Informal work rarely offers structured progression, recognised credentials, or paid time for learning. Workers learn by doing, but they learn within narrow scopes: selling, driving, repairing, cooking, trading. These are real skills. Yet the pathways to higher productivity, digital tools, compliance capability, quality control systems, export standards, are often absent.

In parts of Africa, Asia and Latin America, this creates a paradox. The labour force is young and energetic, but training systems are thin. Migration then becomes a rational training strategy: people leave not only for higher wages, but for exposure to systems that teach. Remittances finance families; migration finances learning.

Countries that treat migration purely as a brain drain miss the deeper mechanism: learning is being outsourced because domestic institutions are not reliably providing it.

Portable Learning, Paid Time

Serious skills policy begins with an unglamorous insight: training requires time, and time has a payer. The question is not whether societies value learning. The question is who finances it. If individuals must self-fund continuous training while living under cost-of-living pressure, the system will reproduce privilege. If firms must finance training alone in high-risk environments, they will under-invest. If the state finances everything, it risks building training that is misaligned with real jobs.

The most practical models share three features. First, they make training portable: credentials and learning records follow the worker across firms. Second, they make training co-funded: the cost is shared among worker, firm, and state through mechanisms that scale with income and profitability. Third, they make training auditable: programmes are evaluated against wage outcomes and employment durability, not participation counts.

In the Global South context, the most powerful intervention is often the simplest: paid learning time tied to labour market transitions. When workers move from informal to formal jobs, from low-skill to mid-skill roles, from unemployment into apprenticeships, the system should buy time for learning as a public investment. Not forever. Just enough to create compounding capability.

Who Gets to Upgrade

In 2026, the question of who still gets paid to learn is becoming a proxy for who remains middle class. Automation is not a single shock. It is a continuous sorting process. The winners will not necessarily be those with the highest IQ or the longest CV. They will be those embedded in systems that sponsor learning, verify competence, and compound skill into higher wages.

Closing Insight: The Global South does not face a talent shortage. It faces a training finance shortage, an absence of reliable mechanisms that purchase time for upgrading at scale. Countries that solve this will turn automation into productivity. Those that do not will harden the skills divide into a durable class boundary, with learning as the new inheritance.