Abstract
This paper, drawing primarily upon recent and ongoing research at the ILO, suggests a landscape where AI is more likely to augment human capabilities and enhance productivity in many roles rather than leading to widespread automation, although certain occupations and demographic groups exhibit higher exposure to transformative effects. Using an innovative and refined methodology, the paper begins by examining potential occupational exposure to GenAI in the G20, refining previous estimates to identify varying gradients of impact and highlighting significant disparities based on gender and national/regional income levels. The analysis then contextualizes these AI-specific potentials by exploring the current digital intensity of employment and the realized employment effects of a wider array of emerging digital technologies, underscoring the heterogeneous nature of digital transformation across different economic contexts. Furthermore, the paper touches on important aspects of AI's influence on job quality, including the rise of algorithmic management and the often-overlooked role of the "data labourers" who underpin AI systems.
