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AI is changing work, but exposure to automation does not mean an entire job will disappear. Its effects can include automating some tasks, helping people do others more productively, and creating new tasks or occupations. The balance depends on the work, the technology, and how employers manage the transition.
How does AI change work?
AI changes work through several channels that can operate at the same time. A system may take over a task, assist a worker with another, or make new work possible. The result for employment depends on how these effects balance out; the OECD does not establish one universal net outcome across sectors and time horizons. OECD analysis of skills in the AI age describes these interacting effects and the differences across sectors, regions, cities, and skill levels.
| Channel | What it means at work | What it does not establish by itself |
|---|---|---|
| Task automation | A system performs some work previously done by a person. | That every task in the job, or the whole job, will be eliminated. |
| Assistance and productivity | A worker uses AI to help complete work or improve productivity. | That the time saved will necessarily lead to fewer employees; employers may use it in different ways. |
| New tasks and occupations | AI may create work associated with using, managing, or responding to the technology. | That new work will appear at the same pace, in the same places, or for the same workers as tasks change. |
Adoption is rising, but adoption is not a head count of jobs automated. OECD data show that the share of firms using AI in OECD countries rose from around 7% in 2021 to 20% in 2025. Those figures describe firm uptake, not the percentage of workers or jobs replaced. OECD executive summary and firm-adoption figures
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No single exposure statistic can answer that for an individual worker. A job is a bundle of tasks, and a technology may affect some of them without making the rest unnecessary. Work that depends on non-routine thinking, social interaction, judgment, or responsibility may be changed by AI without being straightforward to automate. Conversely, tasks that are more routine may face different substitution risks. Exposure to AI and the likelihood that a whole job will be automated are not the same measure.
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The OECD topic overview estimates that occupations at the highest risk of automation account for about 28% of jobs on average across OECD countries. This is an estimate of jobs in occupations classified as highest risk—not a forecast that 28% of jobs will be lost. It applies to OECD countries, not the world as a whole. OECD Future of Work overview
For a specific role, a more useful question is which activities are changing. Consider the tasks you do repeatedly, the parts that require context or human judgment, and the responsibilities that remain with a person even when software contributes to the work. That task-level view is more informative than treating a job title as either “safe” or “doomed.”
What skills will workers need as AI changes work?
The International Labour Organization (ILO) describes changing demand across cognitive, socioemotional, digital, and AI skills. Its analysis emphasizes adaptability and human agency as AI becomes part of workplace tasks. ILO report on the changing skills landscape in the age of AI
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- Socioemotional skills: Communicate, collaborate, and handle the human aspects of work that technology does not remove.
- Digital skills: Work confidently with digital systems and understand how they fit into a job’s workflow.
- AI skills: Know how to use AI appropriately, check its output, and recognize when a task needs human review.
- Adaptability: Update how you work as tasks, tools, and expectations change.
These categories point to a practical learning approach: build on the expertise you already use in your role, then learn how AI affects specific tasks within it. Tool familiarity matters, but it is not a substitute for the knowledge needed to spot an error, judge whether an output is fit for purpose, or decide when not to use it.
How can workers and employers make the transition useful?
AI’s effects are not determined by the technology alone. Employers choose which tasks to automate or assist, what workers are expected to do with the time or capacity that results, and how much discretion people retain. A careful rollout treats AI as a change to a workflow—not simply a software installation.
For workers
- Map your tasks. Separate routine, repeatable activities from work that depends on context, judgment, relationships, or accountability.
- Identify where assistance could help. Look for tasks where AI might support drafting, analysis, or other work, while keeping responsibility for checking results clear.
- Strengthen review skills. Practice verifying outputs against domain knowledge and the requirements of the task, rather than accepting them because they appear polished.
- Ask how the role will change. Seek clarity about new responsibilities, required training, decision rights, and who is accountable for AI-supported work.
For employers
- Define the work problem first. Specify which task the system is intended to automate or assist and what outcome would count as an improvement.
- Assess the workflow, not just the tool. Check quality and reliability in the relevant work, the effect on worker discretion and job quality, privacy and data governance, accessibility and bias, and the training and support workers will need.
- Keep human responsibility explicit. Set out who reviews consequential outputs, resolves errors, and can override or challenge the system.
- Evaluate outcomes over time. Look for evidence of productivity or safety outcomes in the actual workflow, and account for the cost of review, correction, and training—not just the speed of generating an output.
- Involve affected workers. Workers can identify practical failure points and explain how a change affects the rest of the job, helping employers make deployment more useful and manageable.
Who may be affected differently?
AI’s effects are uneven across occupations and groups. The ILO reported in March 2026 that female-dominated occupations are almost twice as likely to be exposed to generative AI as other occupations. That is a relative exposure finding, not an estimate that women are almost twice as likely to lose their jobs. The ILO points to occupational concentration, underrepresentation in AI and STEM fields, and bias reflected in AI systems as factors behind unequal exposure. ILO announcement on women’s exposure to workplace generative AI
As ILO senior economist and report co-author Janine Berg put it: “The impact of generative AI on women’s jobs is not predetermined.” How employers deploy systems, address bias, and support workers through changing tasks can shape the outcome.
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