1、 Disclaimer:The findings,interpretations,and conclusions expressed in this material represent the views of the author(s)and are not necessarily those of the ASEAN+3 Macroeconomic Research Office(AMRO)or its member authorities.Neither AMRO nor its member authorities shall be held responsible for any

2、consequence from the use of the information contained therein.Working Paper(WP/25-12)Labor Market Exposure to AI:From GenAI to Future AGI Xianguo Huang November 2025 This page is intentionally left blank Labor Market Exposure to AI:From GenAI to Future AGIPrepared by Xianguo(Jerry)Huang*Authorized f

3、or distribution by Abdurohman(Deputy Director)November 2025AbstractThis paper adopts and extends a task-based framework leveraging Large Language Models(LLM)to assess occupational exposure to Generative Artificial Intelligence(GenAI).It revealscross-country variation by income level,with higher-inco

4、me economies experiencing greatertask-level exposure.At present,the potential for GenAI to augment human work outweighsits automation risks,though this balance may shift with the advent of more advanced AI sys-tems and their integration with other emerging technologies.The paper further conducts ane

5、xercise to assess occupational exposure under a scenario where artificial general intelligence(AGI)is realized.Using a combination of LLM-based task evaluations and detailed labor forceemployment data,the study also presents a country case study.While overall exposure remainsmoderate,occupations in

6、clerical,administrative,and financial services are particularly vulnera-ble to GenAI-driven transformation in Brunei.Exposure is notably higher,among individuals withmid-level educational attainment,as well as among women.JEL codes:J23,J24,J68,O30,O33Keywords:GenAI,AGI,Labor Market,ISCO-08,Brunei*Em