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Based on theoretical analysis, six hypotheses are proposed regarding three aspects of AI\u2019s influence on on-the-job learning. Empirical results demonstrate that AI significantly inhibits people\u2019s on-the-job learning and this conclusion holds true in a series of robustness and endogeneity checks. The impact mechanism is that AI makes workers more pessimistic about the future, leading to burnout and less motivation for on-the-job learning. In addition, AI\u2019s replacement, mismatch, and deskilling effects decrease people\u2019s income while extending working hours, reducing their available financial resources and disposable time for further learning. Moreover, it has been found that AI\u2019s impact on on-the-job learning is more prominent for older, female and less-educated employees, as well as those without labor contracts and with less job autonomy and work experience. In regions with more intense human\u2013AI competition, more labor-management conflicts, and poorer labor protection, the inhibitory effect of AI on further learning is more pronounced. In the context of the fourth technological revolution driving forward the intelligent transformation, findings of this paper have important implications for enterprises to better understand employee behaviors and to promote them to acquire new skills to achieve better human\u2013AI teaming.<\/jats:p>","DOI":"10.3390\/systems11030114","type":"journal-article","created":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T05:01:32Z","timestamp":1677042092000},"page":"114","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Does Artificial Intelligence Promote or Inhibit On-the-Job Learning? Human Reactions to AI at Work"],"prefix":"10.3390","volume":"11","author":[{"given":"Chao","family":"Li","sequence":"first","affiliation":[{"name":"Business School, Shandong University, Weihai 264209, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhan","family":"Zhang","sequence":"additional","affiliation":[{"name":"HSBC Business School, Peking University, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoru","family":"Niu","sequence":"additional","affiliation":[{"name":"School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264209, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feier","family":"Chen","sequence":"additional","affiliation":[{"name":"Business School, Shandong University, Weihai 264209, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongyan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Business School, Shandong University, Weihai 264209, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Agrawal, A., Gans, J., and Goldfarb, A. 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