Measuring the Impact of AI and Large Language Models on Singapore’s Labor Market: Constructing a Task-Level Exposure Index

Artificial intelligence (AI), particularly large language models (LLMs), is reshaping the nature of work across occupations and industries. As one of the world’s most open and technologically advanced economies, Singapore stands at the forefront of this transformation. This project develops the first comprehensive, data-driven measure of how AI—especially LLM technologies—affects labour demand in Singapore. Building on detailed task-level information from the U.S. O*NET framework and a newly secured dataset of Singapore job postings, the study will construct a Singapore AI–LLM Exposure Index that quantifies the extent to which each occupation is susceptible to AI-driven change. ​

Recognizing that GPT-based task evaluations are inherently noisy, the project introduces a novel econometric framework to model and correct for measurement error, producing uncertainty-adjusted exposure measures with explicit confidence intervals. Extending this approach, a signed exposure index will be developed to distinguish between complementary and substitutive effects of AI on human labour, allowing policymakers to identify which jobs are likely to benefit from AI adoption and which face greater displacement risk. ​

The resulting indices will form the first reproducible, transparent, and publicly accessible measures of occupational AI exposure for Singapore. These tools will equip government agencies, firms, and researchers to anticipate areas of technological disruption, design targeted reskilling and inclusion strategies, and benchmark Singapore’s workforce resilience against other economies. Beyond policy relevance, the project contributes methodological innovations for handling noisy AI-based assessments and establishes Singapore as a regional leader in empirical research on AI and the future of work. 

Building on the development of Singapore’s first AI-LLM Exposure Index, the research has expanded to examine labour market impacts across Singapore and China. Using occupation and task-level exposure data, the study compares AI-related labour market trends across Singapore, Beijing and Shanghai, generating insights for policymakers, employers and workforce development agencies.

Background

AI and large language models (LLMs) are transforming labour markets worldwide. Yet there is limited rigorous evidence on how these technologies affect specific occupations and tasks, particularly in Asia, with existing studies focused largely on Western economies.

This project examines AI’s impact on labour markets in Singapore and China, which offer a compelling comparative setting due to their contrasting economic structures, occupational compositions and stages of AI adoption.

The research is motivated by three core questions:

1. How can we rigorously measure the impact of AI on different occupations, labour demand and the most vulnerable worker groups?
2. How do differences in economic structures and institutions lead to different AI impacts across labour markets in different countries?
3. How can we design effective, evidence-based public policies to enhance workforce resilience in the face of AI-driven change?

Developing the AI-LLM Exposure Index

To answer the questions, the project developed Singapore’s first AI-LLM Exposure Index, a measurement tool that analyses real job postings and workplace tasks to identify which occupations are most exposed to AI-driven change.

The AI-LLM Exposure Index works as follows. First, data on millions of occupations and their associated tasks are collected. Each task is then compared with the capabilities of current AI and LLMs (i.e. how much of the task AI could perform today?) and assigned a score — for example, 2 if AI can perform the task and 0 if it cannot. The task-level scores are then aggregated to produce an overall Exposure Score for each occupation. A higher Exposure Score indicates a greater potential for the job to be affected by AI.

The Index also tracks how labour markets are changing over time, including shifts in hiring patterns and educational needs.

Results

In Singapore and China, the jobs most affected by AI are higher-skilled, white-collar occupations, with significant implications for wages, job demand and evolving skills requirements.

The AI-LLM Exposure Index has tracked occupation data in Singapore, Beijing and Shanghai every month since 2012.
An excerpt of 2018–2025 data shows that jobs in Singapore are more exposed to AI than those in Beijing and Shanghai — this is driven by differences in occupation types across the three cities’ changing labour markets.

Explore the Interactive AI-LLM Exposure Index

Experience the AI-LLM Exposure Index through the interactive visualisation developed by the research team. The tool enables users to explore AI exposure across occupations and compare labour market trends across Singapore, Beijing and Shanghai over time.

Policy Applications

By measuring both the disruptive and enabling effects of AI on the labour market, the Index has real-world applications across various domains and can offer practical insights for reskilling, workforce planning and employability. Here are some of the ways it can be applied.

• Early Warning Systems — establishing continuous labour market monitoring frameworks to provide timely, forward-looking warnings of AI-driven disruptions to specific occupations and sectors.
• Targeted Training — using the task-level exposure data to inform skill adaptation strategies and design reskilling programmes tailored to occupation- and task-specific exposure levels.
• Social Safety Nets — strengthening social protection systems to absorb shocks and support worker transitions in occupations most affected by AI.
• Cross-city Benchmarking — applying the Index to other cities and economies to assess AI’s impact on local labour markets, supporting more targeted workforce strategies in diverse urban contexts.

Conclusion

Lead researcher Professor Li Jia says: “This project provides an evidence-based understanding of how AI is reshaping occupations and skills in Singapore and China through an AI-LLM exposure study. By doing so, policymakers, educators and employers can respond to AI-driven disruption with data rather than guesswork. Discussions are underway with SkillsFuture Singapore to explore a partnership to operationalise the findings.”

Research Impact: Measuring AI’s Disruptive and Enabling Effects on Singapore’s Labor Market.