{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T05:00:22Z","timestamp":1785214822400,"version":"3.55.0"},"reference-count":45,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T00:00:00Z","timestamp":1785196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:p>This study examines how exposure to artificial intelligence (AI) shapes Chinese workers\u2019 occupational mobility and how the consequences differ across AI\u2019s labor-saving and labor-augmenting channels. Using 2,446 worker-year observations from the China Labor Force Dynamics Survey 2012\u20132018, we measure occupation-level AI exposure as the semantic similarity between Chinese task descriptions and AI patent texts and decompose it along routine and non-routine task lines. Causal identification uses an instrumental variable that interacts 2010 baseline occupation-level exposure with lagged cumulative U.S. patent stocks from the USPTO AI Patent Dataset. The 2SLS estimates yield three findings. First, a one-log-unit increase in total AI exposure raises minor-group switching by 3.6 percentage points and intermediate-group switching by 3.4 points, with no significant effect at the major-group level. In the decomposed estimates, only the labor-augmenting component has significant positive coefficients beyond the minor-group margin, reaching 4.6 points at the intermediate and 6.9 points at the major-group distance. The labor-saving coefficients are statistically indistinguishable from zero in the full-sample switching-incidence IV estimates. The short-distance response is concentrated among women, and among less-educated workers labor-saving exposure predicts lower and labor-augmenting exposure higher major-group mobility, suggesting a labor-saving-related barrier to long-distance transitions. Second, among switchers, labor-augmenting exposure exhibits positive but attenuated origin\u2013destination sorting in all three switching samples. Labor-saving sorting is positive in the minor-group sample, statistically indistinguishable from zero in the intermediate-group sample, and negative in the major-group sample. Third, among switchers, greater labor-saving exposure in the origin occupation is associated with longer hours in the minor- and intermediate-group samples and with lower skill-match satisfaction in all three samples, whereas favorable associations with origin labor-augmenting exposure are confined to specific samples. The study extends organizational-psychology research by linking instrumented AI exposure to occupational switching as an observable career-adaptation behavior and to the fit and demand conditions of destination jobs. The findings suggest targeted reskilling and organizational support for less-educated workers in occupations with high labor-saving exposure.<\/jats:p>","DOI":"10.3389\/fpsyg.2026.1799093","type":"journal-article","created":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T04:26:35Z","timestamp":1785212795000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["AI exposure, occupational mobility, and post-transition job quality in China: labor-saving and labor-augmenting channels"],"prefix":"10.3389","volume":"17","author":[{"given":"Ling","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Economics, Jinan University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenzhen","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Economics, Jinan University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,28]]},"reference":[{"key":"ref1","first-page":"1043","volume-title":"Handbook of Labor Economics","author":"Acemoglu","year":"2011"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"S293","DOI":"10.1086\/718327","article-title":"Artificial intelligence and jobs: evidence from online vacancies","volume":"40","author":"Acemoglu","year":"2022","journal-title":"J. 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