{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T10:11:50Z","timestamp":1788775910966,"version":"build-2803163510"},"reference-count":59,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Behav. Sci.","Behavioral Sciences"],"abstract":"<jats:p>Background: With the widespread application of artificial intelligence technology in organizational contexts, understanding its implications for employees\u2019 motivation and well-being has become increasingly important. Yet, how employees\u2019 AI usage is prospectively associated with intrinsic motivation and job burnout remains insufficiently understood. Based on conservation of resources theory, this study adopted a two-wave longitudinal design to examine the relationships among employees\u2019 artificial intelligence usage, intrinsic motivation, and job burnout. Methods: Data were collected through a two-wave questionnaire survey. The final sample consisted of 313 employees. A cross-lagged panel model was adopted for analysis. Results: AI usage positively predicted subsequent job burnout and negatively predicted subsequent intrinsic motivation after accounting for prior levels and other model variables. Intrinsic motivation negatively predicted subsequent job burnout. In addition, higher job burnout positively predicted subsequent AI usage, indicating a potential bidirectional prospective relationship between AI usage and job burnout. The sensitivity analysis showed a generally similar directional pattern, although the job burnout to AI usage pathway was attenuated and became nonsignificant. Conclusions: Artificial intelligence usage should not be viewed solely as a job resource. Although it may enhance work efficiency and convenience, it may also be associated with higher subsequent job burnout and lower intrinsic motivation. Intrinsic motivation may represent an important psychological pathway linking AI usage to later job burnout.<\/jats:p>","DOI":"10.3390\/bs16091587","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T09:23:37Z","timestamp":1788773017000},"page":"1587","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Workplace AI Usage, Intrinsic Motivation, and Job Burnout: Evidence from a Longitudinal Study"],"prefix":"10.3390","volume":"16","author":[{"given":"Kaiyue","family":"Wang","sequence":"first","affiliation":[{"name":"Faculty of Health and Wellness, City University of Macau, Macau 999078, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6231-9258","authenticated-orcid":false,"given":"Yongxin","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Psychology and Behavior, Henan University, Kaifeng 475004, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1037\/ocp0000056","article-title":"Job demands\u2013resources theory: Taking stock and looking forward","volume":"22","author":"Bakker","year":"2017","journal-title":"Journal of Occupational Health Psychology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1146\/annurev-orgpsych-031413-091235","article-title":"Burnout and work engagement: The JD-R approach","volume":"1","author":"Bakker","year":"2014","journal-title":"Annual Review of Organizational Psychology and Organizational Behavior"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1002\/job.2735","article-title":"A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice","volume":"45","author":"Bankins","year":"2024","journal-title":"Journal of Organizational Behavior"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1080\/01608061.2024.2319623","article-title":"Conceptualizing job burnout through a behavioral lens: Implications for organizational behavior management","volume":"45","author":"Bottini","year":"2025","journal-title":"Journal of Organizational Behavior Management"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.jbusres.2020.08.018","article-title":"Productive employment and decent work: The impact of AI adoption on psychological contracts, job engagement and employee trust","volume":"131","author":"Braganza","year":"2021","journal-title":"Journal of Business Research"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1017\/jmo.2016.55","article-title":"Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees\u2019 perceptions of our future workplace","volume":"24","author":"Brougham","year":"2018","journal-title":"Journal of Management & Organization"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Cajnko, P., and Cajnko, K. 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