Concern 692 · Working draft · editorial review in progress
National-income effects
National-income exposure arises when AI changes international demand for services that a country's workers and businesses rely on selling abroad.
Understanding the concern
Some economies earn substantial income from customer support, software services and other outsourced work. AI may reduce demand for certain tasks while making local firms more productive or enabling new services. The effect depends on which activities change and whether firms and workers can move into higher-value work.
Research on the Philippines highlights exposure in the business-process sector alongside choices about skills and adoption. A country's exposure score is not a prediction of lost national income. Think of a trading partner changing what it buys: the impact depends on how suppliers adapt, who can afford the transition and whether new demand appears.
An example
Overseas clients request fewer routine service hours but more specialized oversight that local workers have not yet been trained to provide.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
Evidence and its limits
The cited country analysis concerns the Philippines. It should not be generalized as measured income loss or automatically applied to India or other economies.
International Labour Organization 2026 · Country policy research
Generative AI and jobs in the Philippines: Labour market exposure and policy implications ↗ (opens in a new tab)Occupational exposure and policy choices in the Philippines, including IT-BPM. Not a forecast of national income losses or findings for India.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
How can a service-exporting economy prepare workers for changing demand without treating exposure as inevitable decline?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Seeing potential
Seeing potential means recognizing people's capacity to learn, contribute, and grow. It resists reducing someone to a score or to the tasks a machine can perform faster.
Use tools to support people's development. Give learners time, feedback, and real opportunities to practice. A prediction about someone's performance should not close off their future.
Ask together: How could this help people develop abilities they value?
Solidarity
Solidarity means standing with people whose lives are affected, especially when they have less power to protect their interests. It turns concern into a willingness to share responsibility.
Include affected people in decisions and support practical remedies when something goes wrong. Do not leave the cost of learning or repair entirely with those who were harmed.
Ask together: What would it mean to stand with the people carrying the greatest burden?
Dignity
Dignity means recognizing each person's worth regardless of usefulness, status, or a system's score. People deserve respect and a voice in matters that affect them.
Explain important decisions, avoid humiliating treatment, and keep room for a person's story. Do not treat a prediction as a complete account of who someone is.
Ask together: Does this use treat each person as someone whose experience matters?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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