About skaills

The developing-world dual effect

AI hits developing economies on two clocks running in opposite directions. Heavy reliance on manual, low-skill, low-wage labor — and the cost, infrastructure gaps, political constraints, union pressure, and regulatory friction that slow AI deployment — will keep human labor cheaper than AI for many tasks for years. At the same time, outsourcing-dependent sectors (call centers, BPO, manufacturing in free zones, IT outsourcing) get hit faster than the same roles in developed economies because the demand-side decisions are made elsewhere. Which clock your role, your organization, your sector, or your country sits on is the question that shapes every planning horizon below.

Humans are the pivotal agents — if we play our cards right

AI does not transform economies on its own. Humans transform economies with AI. The transition to the next economic system is a deliberate act of building — not a passive event. That requires carefully planned compensating measures to get through with limited casualties, and conscious cultural choices: which values, traditions, and practices we drop without regret, which we preserve and carry over, and which we nurture and double down on. This values-triage is the cultural counterpart of the economic transition, and it has to happen at every layer — individual, organization, and society.

Productivity — and who captures its gains — cannot be left out of the labor conversation

In the AI era it is no longer honest to discuss work, wages, employment, or employability without addressing productivity and the distribution of productivity gains. The structural tension underneath is rarely named out loud: businesses do not exist to create jobs — they exist to create value for consumers, in the form of goods and services. From the firm's perspective, employment is a resource used to produce and distribute that value. From the perspective of workers, society, and governments, employment is also a distribution mechanism — historically the primary way the gains of economic activity get allocated across the population. For most of industrial history those two views coincided because productivity gains required more labor. AI breaks the coincidence. The political-economy question that follows — who captures the gain: the worker (through higher wages and shorter hours), the employer (through margin), the customer (through lower prices), or the platform layer (through rents) — is no longer optional reading. Every serious transformation plan takes a position on it; the honest plans make the position explicit.

AI changes the worker's relationship to the production process

Because AI is a productivity-enhancing technology, it does more than redistribute the gains — it changes where the worker stands in the value chain. The worker moves from being the producer of the output to being the operator of a productivity multiplier that produces the output. What counts as skill shifts from execution to orchestration, judgment, and supervision of AI output. The marginal product becomes increasingly attributable to the tool rather than to the labor, which weakens individual wage-bargaining power and reshapes what collective bargaining is even bargaining over. Some workers move up the chain — designing, supervising, judging — and capture more of the new value. Others get squeezed because their old position has disappeared and they have no obvious next position in the chain. Transition policies that work address this structural relocation directly: real paths up the chain for the people whose old position is going away, not retraining for an adjacent role at the same level.