{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T11:00:01Z","timestamp":1773226801080,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032129673","type":"print"},{"value":"9783032129680","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"vor","delay-in-days":69,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Organizational strategies and employee responses shape\u00a0Artificial Intelligence (AI) in the workplace. Although AI can enhance performance, increase flexibility, and drive creativity, it can also\u00a0pose challenges, such as job insecurity, technostress, and distrust of data privacy. Employee attitudes are influenced by perceived usefulness, job-task fit, and the benefit of AI visibility. However, concerns\u00a0about job losses and a lack of transparency can hinder adoption and feed resistance. To compare trends across Europe, we included data from the 2024 Special Eurobarometer 554 survey. A combination of cluster analysis and Pearson correlation coefficients was utilized to map clusters of AI acceptance within nations. The results show considerable differences in the avowals across Europe. The report presents a divided landscape in which European workers\u2019 mindsets are key, influenced by their surroundings and organizational transparency, which will significantly affect AI\u2019s future in Europe\u2019s labor markets.<\/jats:p>","DOI":"10.1007\/978-3-032-12968-0_36","type":"book-chapter","created":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T14:14:39Z","timestamp":1773152079000},"page":"329-337","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Navigating the Human Side of AI: Insights into Employee Attitudes, Risks, and Regional Variations"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2468-8981","authenticated-orcid":false,"given":"S\u00f3nia","family":"Avelar","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0229-7579","authenticated-orcid":false,"given":"Carlos","family":"Farinha","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3569-3789","authenticated-orcid":false,"given":"Fl\u00e1vio","family":"Tiago","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4419-0673","authenticated-orcid":false,"given":"Teresa","family":"Borges-Tiago","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,3,11]]},"reference":[{"key":"36_CR1","doi-asserted-by":"publisher","unstructured":"Rane NL, Kaya \u00d6, Rane J (2024) Artificial intelligence, machine learning, and deep learning for sustainable industry 5.0: deep science publishing. 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