[Google AI Overview at the query, signed out and incognito (operator defaults of 2026-10-01 and 2026-10-14), 2026-10-29. The paste is the Overview expanded (the 'AI Mode Conversation' view, with the source cards that follow the answer); the 'You said' line carries the query twice, run together, and is given once here. Inline links are Google redirect URLs, kept as pasted. Supplied as an attached file.] [QUERENT] ILO Generative AI and Jobs index [SYSTEM] The International Labour Organization (ILO) published its updated assessment in the report "Generative AI and Jobs: A Refined Global Index of Occupational Exposure" (ILO Working Paper 140). Key Findings of the Index • Global Exposure Rate: About 24% (1 in 4) of global workers are in occupations with some level of exposure to generative AI (GenAI). • Highest Exposure Category (Gradient 4): Only 3.3% of global employment falls into the highest exposure category where a large majority of tasks can be heavily impacted. • Transformation vs. Replacement: The research emphasizes job transformation rather than widespread job elimination or mass redundancy, as very few occupations consist entirely of automatable tasks. • Income Disparities: High-income countries (HICs) show a 34% total GenAI exposure rate, compared to just 11% in low-income countries (LICs), reflecting differences in economic structures and digital adoption. • Gender Divide: Women are nearly twice as likely to hold jobs exposed to GenAI as men (roughly 29% vs. 16% across sampled countries), largely because women are more heavily represented in clerical, administrative, and routine information-processing roles. • Most Exposed Occupations: Clerical support workers, administrative staff, secretaries, receptionists, data entry operators, and translators face the highest exposure. • Least Exposed Occupations: Manual trades, construction, agriculture, and heavy manufacturing involve physical and non-routine tasks with very low GenAI exposure. Methodology • Task-Level Assessment: Evaluates nearly 30,000 to over 52,000 individual task data points across the International Standard Classification of Occupations (ISCO-08) framework. • Four-Gradient Framework: Combines worker surveys, expert Delphi panel inputs, and large-scale AI assessments to categorize jobs into four distinct exposure gradients based on mean exposure scores and task variability. Would you like to explore: • Specific exposure scores for a particular occupation or industry? • How GenAI impacts administrative versus technical roles? • Policy recommendations from the ILO for workforce upskilling? International Labour Organization