Generative AI and jobs: A 2025 update
This research brief by the International Labour Organization provides a 2025 update on the potential occupational exposure to generative AI, incorporating a refined methodology that combines human and AI insights across nearly 30,000 tasks. The study finds that about one in four workers globally are in an occupation with some degree of GenAI exposure, though most jobs will be transformed rather than automated away. It also highlights notable disparities in exposure based on gender, region, and national income levels.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Policymakers, researchers, and social partners should read this to understand the potential impacts of generative AI on jobs and how to proactively design labor policies.
What the document contains
The document covers global estimates and methodologies for assessing potential occupational exposure to generative AI, categorized into four progressive gradients of exposure. It analyzes differences in exposure across ISCO-08 occupational groups, country income levels, and sex, while discussing the implications of GenAI for job transformation and labor market policies.
The report does not provide binding regulatory requirements, legal definitions of AI, or enforcement mechanisms, as it is a research brief analyzing labor market statistics and trends.
- About one in four workers across the world are in an occupation with some degree of GenAI exposure.
- Most jobs will be transformed by generative AI rather than made redundant due to the continued need for human input.
- Global employment exposure to GenAI varies significantly by sex and national income levels, with higher exposure concentrated in high-income countries and among female workers.
- The highest risk category (Gradient 4) comprises 3.3% of global employment, showing a slight buffer against full job displacement.
- Managing the technological transition through social dialogue is critical to enhancing both working conditions and productivity.
· Introduction · Methodology · Occupational Exposure · Comparison with 2023 exposure scores · Exposed occupations as a share of employment and comparison with 2023 estimates · Conclusions
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
0/5Clear responsibility for AI outcomes
N/A
screening score · 2026-10-23
Fairness
1/5Non-discrimination and equitable treatment
Our aim is to encourage governments and social partners to proactively design policies that support orderly, fair, and consultative transitions
Introduction
screening score · 2026-10-23
Human Dignity
0/5Respect for the inherent worth of persons
N/A
screening score · 2026-10-23
Human Oversight
2/5Humans remain in control of consequential decisions
Will workers have more time to do creative work or will the automation lead to greater standardization of their roles and reduced autonomy?
ILO Brief 6
screening score · 2026-10-23
Privacy
0/5Protection of personal data and private life
N/A
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
N/A
screening score · 2026-10-23