Publicação
The outcomes of generative AI in the future of work: The role of technostress creators
| Resumo: | Generative artificial intelligence (Gen-AI) is reshaping the future of work, bringing both opportunities and challenges in an increasingly competitive global economy. Unlike traditional AI models that primarily analyze existing data, Gen-AI leverages advanced machine learning (ML) techniques, such as deep neural networks and transformer architectures, to model probabilistic distributions, generate contextually relevant content, and iteratively refine outputs based on training data and user interactions. While prior studies have explored its applications in specific domains, research on its broader implications for the future of work remains scarce. To address this lack, this study builds on the DeLone & McLean IS success model and aims to explore the outcomes of Gen-AI in the future of work focusing on the role of technostress creators—stressors induced by AI adoption—and their influence on shaping the adoption and integration of Gen-AI in organizational contexts. This study employs the belief-action-outcome (BAO) framework to structure the proposed conceptual model, which examines how user beliefs—such as technostress creators and quality perceptions—influence actions, including system use and satisfaction, ultimately shaping instrumental and humanistic outcomes. The research draws on both theoretical insights from the existing literature and empirical data collected through questionnaires targeting professionals who have some level of contact with this technology, where we gathered 305 valid responses. Our results highlight the strong impact of Gen-AI in the future of work and the role of technostress creators in user satisfaction and workplace outcomes. Moreover, technostress creators, besides explaining the outcomes, act as moderators in the relationship between AI usage and user satisfaction. |
|---|---|
| Autores principais: | Batista, Bárbara Leal |
| Assunto: | Generative AI Future of work Technostress creators Technology adoption SDG 3 - Good health and well-being SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso embargado |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| _version_ | 1868983744601260032 |
|---|---|
| author | Batista, Bárbara Leal |
| author_facet | Batista, Bárbara Leal |
| author_role | author |
| contributor_name_str_mv | Oliveira, Tiago André Gonçalves Félix de RUN |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Batista, Bárbara Leal\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Oliveira, Tiago André Gonçalves Félix de RUN |
| datacite.creators.creator.creatorName.fl_str_mv | Batista, Bárbara Leal |
| datacite.date.Accepted.fl_str_mv | 2025-06-23T00:00:00Z |
| datacite.date.available.fl_str_mv | 2028-06-23T00:00:00Z |
| datacite.date.embargoed.fl_str_mv | 2028-06-23T00:00:00Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_f1cf |
| datacite.subjects.subject.fl_str_mv | Generative AI Future of work Technostress creators Technology adoption SDG 3 - Good health and well-being SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure |
| datacite.titles.title.fl_str_mv | The outcomes of generative AI in the future of work: The role of technostress creators |
| dc.contributor.none.fl_str_mv | Oliveira, Tiago André Gonçalves Félix de RUN |
| dc.creator.none.fl_str_mv | Batista, Bárbara Leal |
| dc.date.Accepted.fl_str_mv | 2025-06-23T00:00:00Z |
| dc.date.available.fl_str_mv | 2028-06-23T00:00:00Z |
| dc.date.embargoed.fl_str_mv | 2028-06-23T00:00:00Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10362/184799 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_f1cf |
| dc.subject.none.fl_str_mv | Generative AI Future of work Technostress creators Technology adoption SDG 3 - Good health and well-being SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure |
| dc.title.fl_str_mv | The outcomes of generative AI in the future of work: The role of technostress creators |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | Generative artificial intelligence (Gen-AI) is reshaping the future of work, bringing both opportunities and challenges in an increasingly competitive global economy. Unlike traditional AI models that primarily analyze existing data, Gen-AI leverages advanced machine learning (ML) techniques, such as deep neural networks and transformer architectures, to model probabilistic distributions, generate contextually relevant content, and iteratively refine outputs based on training data and user interactions. While prior studies have explored its applications in specific domains, research on its broader implications for the future of work remains scarce. To address this lack, this study builds on the DeLone & McLean IS success model and aims to explore the outcomes of Gen-AI in the future of work focusing on the role of technostress creators—stressors induced by AI adoption—and their influence on shaping the adoption and integration of Gen-AI in organizational contexts. This study employs the belief-action-outcome (BAO) framework to structure the proposed conceptual model, which examines how user beliefs—such as technostress creators and quality perceptions—influence actions, including system use and satisfaction, ultimately shaping instrumental and humanistic outcomes. The research draws on both theoretical insights from the existing literature and empirical data collected through questionnaires targeting professionals who have some level of contact with this technology, where we gathered 305 valid responses. Our results highlight the strong impact of Gen-AI in the future of work and the role of technostress creators in user satisfaction and workplace outcomes. Moreover, technostress creators, besides explaining the outcomes, act as moderators in the relationship between AI usage and user satisfaction. |
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| eu_rights_str_mv | embargoedAccess |
| format | masterThesis |
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| id | run_dce2a5a9c2dfe08089fd587c08a58cb5 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10362/184799 |
| inst_facet_str | urn:organizationAcronym:unl{{{_:::_}}}Universidade Nova de Lisboa |
| instacron_str | unl |
| institution | Universidade Nova de Lisboa |
| instname_str | Universidade Nova de Lisboa |
| language | eng |
| network_acronym_str | run |
| network_name_str | Repositório Institucional da UNL |
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| organization_str_mv | urn:organizationAcronym:unl |
| person_str_mv | Batista, Bárbara Leal |
| publishDate | 2025 |
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| reponame_str | Repositório Institucional da UNL |
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| spelling | engpt_PTGenerative artificial intelligence (Gen-AI) is reshaping the future of work, bringing both opportunities and challenges in an increasingly competitive global economy. Unlike traditional AI models that primarily analyze existing data, Gen-AI leverages advanced machine learning (ML) techniques, such as deep neural networks and transformer architectures, to model probabilistic distributions, generate contextually relevant content, and iteratively refine outputs based on training data and user interactions. While prior studies have explored its applications in specific domains, research on its broader implications for the future of work remains scarce. To address this lack, this study builds on the DeLone & McLean IS success model and aims to explore the outcomes of Gen-AI in the future of work focusing on the role of technostress creators—stressors induced by AI adoption—and their influence on shaping the adoption and integration of Gen-AI in organizational contexts. This study employs the belief-action-outcome (BAO) framework to structure the proposed conceptual model, which examines how user beliefs—such as technostress creators and quality perceptions—influence actions, including system use and satisfaction, ultimately shaping instrumental and humanistic outcomes. The research draws on both theoretical insights from the existing literature and empirical data collected through questionnaires targeting professionals who have some level of contact with this technology, where we gathered 305 valid responses. Our results highlight the strong impact of Gen-AI in the future of work and the role of technostress creators in user satisfaction and workplace outcomes. Moreover, technostress creators, besides explaining the outcomes, act as moderators in the relationship between AI usage and user satisfaction.application/pdfpt_PTThe outcomes of generative AI in the future of work: The role of technostress creatorsBatista, Bárbara LealOliveira, Tiago André Gonçalves Félix deHostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptURNurn:tid:2039686702025-06-232028-06-23T00:00:00Z2025-06-23T00:00:00ZHandlehttp://hdl.handle.net/10362/184799http://purl.org/coar/access_right/c_f1cfembargoed accessGenerative AIFuture of workTechnostress creatorsTechnology adoptionSDG 3 - Good health and well-beingSDG 4 - Quality educationSDG 8 - Decent work and economic growthSDG 9 - Industry, innovation and infrastructure928655 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesis2025-06-23http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_f1cfapplication/pdffulltexthttps://run.unl.pt/bitstreams/3ad477b5-ede7-4eab-b12b-0b38ead3290a/download |
| spellingShingle | The outcomes of generative AI in the future of work: The role of technostress creators Batista, Bárbara Leal Generative AI Future of work Technostress creators Technology adoption SDG 3 - Good health and well-being SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure |
| status | SINGLETON |
| subject.fl_str_mv | Generative AI Future of work Technostress creators Technology adoption SDG 3 - Good health and well-being SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure |
| title | The outcomes of generative AI in the future of work: The role of technostress creators |
| title_full | The outcomes of generative AI in the future of work: The role of technostress creators |
| title_fullStr | The outcomes of generative AI in the future of work: The role of technostress creators |
| title_full_unstemmed | The outcomes of generative AI in the future of work: The role of technostress creators |
| title_short | The outcomes of generative AI in the future of work: The role of technostress creators |
| title_sort | The outcomes of generative AI in the future of work: The role of technostress creators |
| topic | Generative AI Future of work Technostress creators Technology adoption SDG 3 - Good health and well-being SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure |
| topic_facet | Generative AI Future of work Technostress creators Technology adoption SDG 3 - Good health and well-being SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure |
| url | http://hdl.handle.net/10362/184799 |
| visible | 1 |