{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T17:32:11Z","timestamp":1793727131155,"version":"4.6.1"},"reference-count":63,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T00:00:00Z","timestamp":1791849600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["WORK: A Journal of Prevention, Assessment &amp; Rehabilitation"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The rapid adoption of artificial intelligence (AI) in the information technology (IT) reshaping the work design, with significant consequences for employee well-being and ergonomics. While AI enhances efficiency through task automation, its influence on workload dynamics and ergonomic consequences remains not sufficiently understood, particularly in emerging economy contexts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Grounded in the Job Demands\u2013Resources (JD-R) framework and informed by Sociotechnical Systems Theory, this study investigates the relationship between AI adoption and employees\u2019 physical and cognitive ergonomic outcomes while examining the mediating roles of trust in AI and workload among information technology professionals in India.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>To assess this, seven reflective constructs were measured. The AI adoption construct has three sun-dimensions: performance expectancy, effort expectancy and usage behavior\/intention. Employee ergonomics has two sub-dimensions: physical ergonomics discomfort, cognitive ergonomics\/digital fatigue, which are modeled as higher-order constructs. However, trust and workload dynamics are modeled as lower-order constructs. The higher-order constructs were assessed along with the lower-order constructs. Exploratory and confirmatory factor analyses were carried out to unravel the structural relationships among the constructs, and hypothesis testing was performed using structural equation modeling.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The findings indicate that AI adoption significantly enhances trust in AI and reduces workload, Trust in AI is negatively associated with workload, while workload positively influences both physical ergonomic discomfort and cognitive fatigue. AI adoption also demonstrates a significant direct effect on employee ergonomics. The mediation analysis revealed that trust and workload fully mediated the relationship between AI adoption and ergonomics, whereas trust partially mediates the relationship between AI adoption and workload. The serial mediation results reveal partial mediation on role of trust and workload in the nexus among AI adoption and ergonomics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Consistent with the Job Demands\u2013Resources (JD-R) framework, the findings demonstrate that AI functions simultaneously as a job resource and a source of new job demands. Trust in AI serves as an important psychological resource that reduces workload and enhances employees\u2019 physical and cognitive ergonomic outcomes. Trust in AI emerges as a vital psychological mechanism that mitigates workload and enhances ergonomic outcomes. The outcome contributes to the development of human-centric AI implementation strategies by highlighting the importance of trust-building and workload management in designing sustainable, ergonomically sound workplaces<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/10519815261491278","type":"journal-article","created":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T15:56:02Z","timestamp":1791906962000},"page":"942-958","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["AI adoption and employees\u2019 physical and cognitive ergonomic outcomes in the information technology sector: The mediating roles of trust in ai and workload"],"prefix":"10.1177","volume":"85","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9921-476X","authenticated-orcid":false,"given":"KDV","family":"Prasad","sequence":"first","affiliation":[{"name":"Symbiosis International (Deemed University)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shivoham","family":"Singh","sequence":"additional","affiliation":[{"name":"Symbiosis International (Deemed University)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ankita","family":"Pathak","sequence":"additional","affiliation":[{"name":"GLA University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ved","family":"Srinivas","sequence":"additional","affiliation":[{"name":"Thiagarajar School of Management"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hemant","family":"Kothari","sequence":"additional","affiliation":[{"name":"President, Pacific Academy of Higher Education and Research University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,10,13]]},"reference":[{"key":"e_1_3_3_2_2","volume-title":"Machine, platform, crowd: Harnessing our digital future","author":"McAfee A","unstructured":"McAfee A, Brynjolfsson E. 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