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AI systems already perform or assist with tasks in clerical, financial, programming, and other occupations—but that does not mean they have replaced those jobs. The International Labour Organization’s 2025 global index estimates that one in four workers worldwide are in occupations with some degree of generative AI exposure. It concludes that most jobs are more likely to be transformed than made redundant because they still require human input.
What “AI is doing a job” actually means
AI exposure describes the potential for technology to affect tasks within an occupation. It is not proof that employers have adopted AI for those tasks, that workers have been displaced, or that a whole occupation can be automated. As ILO Senior Researcher Paweł Gmyrek puts it, “Such exposure does not imply the immediate automation of an entire occupation, but rather the potential for a large share of its current tasks to be performed using this technology.” Read the ILO’s 2025 global index.
The examples below identify ten occupations the ILO describes as exposed to generative AI, and the kinds of work within them that could be assisted or automated. They are task examples, not claims that AI systems have taken over ten occupations or that every employer uses them.
10 occupations with tasks AI can assist with or automate
1. Data entry clerks
Entering information from digital documents into structured systems is a clerical task the ILO identifies among the most exposed. AI may help extract and organize information, while people can still be needed to resolve unclear records and check accuracy.
2. Typists
Producing or reformatting text is exposed when the work is digital and follows a repeatable pattern. The ILO includes typists among the roles most exposed to generative AI; that does not establish that all typing work is automated.
3. Accounting clerks
Some routine accounting work involves processing digital records and applying consistent rules. The ILO identifies accounting clerks among highly exposed roles, but exposure does not show that AI independently handles every transaction or exception.
4. Bookkeeping clerks
Bookkeeping tasks that involve organizing and recording information may be affected by AI. The ILO groups bookkeeping clerks with the most exposed occupations; reconciliation, unusual entries, and responsibility for accurate records can still involve human work.
5. Administrative secretaries
Some administrative work consists of handling digital information and producing routine text. The ILO names administrative secretaries among the most exposed occupations, while the occupation may also include tasks that depend on context, coordination, and interaction.
6. Financial analysts
Financial analysis is among the digitized professional roles for which the ILO reports increased exposure. AI may affect information-processing and analytical tasks, but the index does not say that AI replaces analysts or makes consequential financial decisions on its own.
7. Web and multimedia developers
The ILO identifies web and multimedia development as a professional area with increased exposure. Some work can be described digitally and may be affected by generative AI; the source does not establish which employers have automated particular development tasks.
8. Application programmers
Application programming is another role in which the ILO reports increased exposure. Some programming work is digital and sufficiently specified to be affected by AI, but a task-exposure score is not evidence that a programmer’s full job can be automated.
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9. Investment advisers
The ILO also names investment advisers among roles with increased exposure. Information and analysis tasks may be affected, while advice can involve individual circumstances and consequential judgment. The index does not claim AI has replaced advisers.
10. Other clerical workers
The ILO says clerical occupations remain the most exposed overall. This category is not a claim about one specific job title: it reflects a broader pattern in which many clerical tasks are digital and repeatable. Exposure varies between occupations and between tasks within the same role.
Five kinds of work AI cannot be shown to replace permanently
No occupation can responsibly be called permanently safe from AI on the evidence available here. The ILO finds that most jobs still include tasks requiring human input, but that is not a guarantee about every job or future technology. The more useful distinction is between tasks that may be exposed and work whose variability, human interaction, physical setting, or accountability makes whole-job replacement a much stronger claim.
1. Work that requires judgment across varied cases
AI exposure is not the same as handling every exception. When cases differ and require judgment, a system’s ability to assist with routine portions does not establish that it can take over the entire occupation.
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An occupation may include communication and coordination alongside digital tasks. The ILO’s finding that most jobs retain a need for human input is a reason not to equate exposed tasks with a fully replaceable job.
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3. Work that depends on physical context
A task performed in a real-world setting may involve physical presence or circumstances that are not captured by an estimate of generative AI exposure. Such exposure alone cannot demonstrate that AI can perform that work in context.
4. Work with responsibility for consequential decisions
AI may contribute information or analysis without establishing who is responsible for a decision and its consequences. The ILO index measures task exposure, not the transfer of professional or organizational accountability to a system.
5. Jobs combining exposed and human-led tasks
Many occupations are mixtures: some tasks may be affected by AI while others continue to require human input. The ILO’s central conclusion is that transformation is more likely than redundancy for most jobs, not that any particular occupation will remain unchanged forever.
How to judge whether an occupation is exposed—or likely to change
- Digitization and repeatability: Is the work performed digitally, and does it follow a consistent pattern?
- Variation: How much do cases differ, and how often does the work require handling exceptions?
- Human interaction and judgment: Does the task depend on communication, individual context, or decisions that cannot be reduced to routine processing?
- Physical presence and accountability: Does the work require action in a physical setting or responsibility for a consequential outcome?
These are practical lenses for interpreting exposure, not a separate ILO ranking. A high potential for AI to affect some tasks does not answer whether the technology is deployed in a particular workplace or whether the occupation will shrink.
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What the latest figures do—and do not—show
The ILO’s 2025 index estimates that one in four workers worldwide are in occupations with some degree of generative AI exposure. Its highest exposure category covers 3.3% of global employment. Those figures describe exposure gradients, not workers already displaced or jobs fully automated. The index’s mean automation score was 0.29 in 2025, compared with 0.30 in 2023; these are index scores, not percentages of jobs automated. ILO, 2025.
Exposure is also uneven. In high-income countries, 9.6% of women’s employment and 3.5% of men’s employment falls in the index’s highest exposure gradient. This is a comparison of employment shares in that category, not a measure of job losses. ILO, 2025.
Adoption is a separate question. The OECD reports that around 7% to 20% of firms in OECD countries adopted AI between 2021 and 2025. That is a firm-level adoption figure—not the share of workers or jobs affected—and it does not establish adoption of generative AI for any one occupation. OECD, 2026.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchThe ILO’s 2025 assessment says clerical work remains the most exposed, with increased exposure in some digitized professional and technical roles as well. The index therefore points to changing task mixes, not a verified list of occupations already handed over to AI. ILO, 2025.
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