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AI exposure does not mean your job is destined to disappear. The International Labour Organization (ILO) estimates that one in four workers worldwide is in an occupation with some degree of generative AI exposure, but says job transformation is more likely overall than job redundancy. That distinction is central: exposure describes the potential for AI to affect tasks, not a count of workers who will lose their jobs.
What does it mean for a job to be exposed to AI?
An occupation is considered exposed when some of its tasks could be affected by generative AI. That can mean automating parts of a task, assisting a worker, or changing how work is organized. It does not, on its own, predict whether an employer will adopt AI, eliminate a position, or create a different role.
The ILO’s 2025 estimate covers occupations with any degree of exposure. Its refined index places 3.3% of global employment in the highest exposure category—a much narrower group than the one-in-four figure. Both figures measure potential task impact, not job losses. ILO, “Generative AI and Jobs: A Refined Global Index of Occupational Exposure”.
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Clerical work remains the broad occupational group with the greatest exposure in the ILO index. Exposure has also expanded into some highly digitized professional and technical work. This is a task-level picture, not a ranking that identifies which individual workers will be replaced.
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Exposure varies by occupation, task, gender, and country income level. A global average therefore cannot tell a worker what will happen in a particular workplace or economy. The ILO’s index draws on task-level data, worker input, expert validation, and AI-assisted task scoring. ILO, May 20, 2025.
Why exposure is not the same as replacement
Most jobs combine tasks that may be affected by AI with tasks that still require human input. AI could change how a task is performed without eliminating the wider job. Whether that becomes assistance, a redesigned role, or a reduction in positions depends on how employers implement the technology and how work is organized.
Gene Marks makes a related argument in his opinion article: technological change can displace some work while changing other work and opening new roles, and workers adapt rather than simply accept change. That is an argument about how people respond to technological shifts, not a quantified forecast of AI-related job losses. The article also recognizes risks such as workplace privacy and security concerns. Gene Marks, “AI may come for your job. It’s not the end of the world — it’s the start of a new one.”
What workers can do as tasks change
Because exposure is measured at the task level, a useful first step is to look at the work itself rather than assume an entire occupation will vanish. Identify which tasks are changing, which still require judgment or human interaction, and how AI is being used in your workplace. Ask your employer how responsibilities, expectations, and training may change as new systems are introduced.
- Find out which tasks AI is intended to assist or automate, and how the output will be checked.
- Clarify whether responsibilities, performance measures, or staffing plans are changing alongside the technology.
- Raise privacy and security questions about the information entered into workplace AI systems.
- Look for opportunities to build skills relevant to the tasks your role is gaining or retaining.
These steps do not guarantee that a job will remain unchanged. They can help make a transition more visible and give workers a chance to participate in decisions affecting their work.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why employers and workers need to shape the transition
The ILO calls for social dialogue among governments, employers, and workers to manage AI-related change and improve both working conditions and productivity. For workplaces, that means discussing not only whether a tool can perform a task, but how adoption affects the people doing the work and who benefits when productivity changes.
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Exposure figures are useful for understanding where work may change at a broad level. They are not individual predictions. The more immediate questions are what tasks are changing in a particular role, how the technology is being introduced, and whether workers have a voice in that process.
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