Harder or Easier? Impact of the AI Exposure Index on China’s Online Labor Market: An Occupation-Based Perspective

This study explores the impact of artificial intelligence (AI) on the labor market from the perspective of occupations. We innovatively construct an AI exposure index based on local Chinese data by measuring the semantic similarity between AI capabilities and occupational task requirements using large language model and Sentence-BERT models. Using the retrieval-augmented generation method, we analyze online job postings in China from 2019 to 2024, examining the impact of AI exposure on employment opportunities, occupational wages, and job matching. Results show that overall, AI exposure has steadily increased across tasks and occupations in China. AI exposure shows significant substitution effect on traditional occupations but no significant creation effect on emerging ones. High AI exposure is associated with low wages, especially in occupations with high proportion of routine tasks, although task complexity mitigates this effect. In addition, AI exposure reduces job filling rates and prolongs recruitment time, indicating increased matching friction.