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Exploring generation Z's use of AI advice in business decision-making

Bibliographic Details
Main Author: Correia, Inês Monteiro Saraiva
Publication Date: 2024
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.14/47885
Summary: There is an increasing number of companies employing AI in business decision-making. Companies are composed by a diverse workforce with different experiences and backgrounds thus, it becomes imperative to understand if generations rely differently on AI. This thesis aims to understand the differences between Generation Z and Generation X regarding their reliance on AI advice and explore how this relationship is affected by trust. Additionally, it assesses the moderating effect of confidence in own judgement. To collect the data, a quantitative betweensubjects survey was employed, where participants from both generations were presented with two hypothetical decision-making scenarios to evaluate their reliance on AI advice. Findings reveal that Gen Z relies more on AI advice compared to Gen X. Interestingly, no significant differences were found in dispositional trust in AI between the two generations. However, a strong positive correlation was identified between dispositional and situational trust, with situational trust significantly enhancing reliance on AI advice. This indicates that higher levels of situational trust are correlated with greater reliance on AI. Surprisingly, the moderating effect of confidence in own judgment was not confirmed. Exploratory analysis suggests that familiarity with AI might mediate the relationship between generational differences and reliance on AI advice. Additionally, it was found that higher confidence in own judgement negatively impacts reliance on AI advice. These insights underscore the complexity of understanding how trust affects reliance on AI across generational cohorts and highlight the importance of considering this factor in order to foster effective AI integration strategies within companies.
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spelling Exploring generation Z's use of AI advice in business decision-makingExplorar a utilização de inteligência artificial, pela geração Z, no processo de tomada decisões empresariaisArtificial intelligenceGeneration ZGeneration XBusiness decision-makingAI adviceTrustInteligência artificialGeração ZGeração XTomada de decisões empresariaisConselhos de IAConfiançaThere is an increasing number of companies employing AI in business decision-making. Companies are composed by a diverse workforce with different experiences and backgrounds thus, it becomes imperative to understand if generations rely differently on AI. This thesis aims to understand the differences between Generation Z and Generation X regarding their reliance on AI advice and explore how this relationship is affected by trust. Additionally, it assesses the moderating effect of confidence in own judgement. To collect the data, a quantitative betweensubjects survey was employed, where participants from both generations were presented with two hypothetical decision-making scenarios to evaluate their reliance on AI advice. Findings reveal that Gen Z relies more on AI advice compared to Gen X. Interestingly, no significant differences were found in dispositional trust in AI between the two generations. However, a strong positive correlation was identified between dispositional and situational trust, with situational trust significantly enhancing reliance on AI advice. This indicates that higher levels of situational trust are correlated with greater reliance on AI. Surprisingly, the moderating effect of confidence in own judgment was not confirmed. Exploratory analysis suggests that familiarity with AI might mediate the relationship between generational differences and reliance on AI advice. Additionally, it was found that higher confidence in own judgement negatively impacts reliance on AI advice. These insights underscore the complexity of understanding how trust affects reliance on AI across generational cohorts and highlight the importance of considering this factor in order to foster effective AI integration strategies within companies.Lettl, ChristopherKommol, ErikVeritatiCorreia, Inês Monteiro Saraiva2025-01-23T15:44:53Z2024-10-172024-09-092024-10-17T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.14/47885urn:tid:203731310enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-13T13:35:35Zoai:repositorio.ucp.pt:10400.14/47885Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T01:57:56.042036Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Exploring generation Z's use of AI advice in business decision-making
Explorar a utilização de inteligência artificial, pela geração Z, no processo de tomada decisões empresariais
title Exploring generation Z's use of AI advice in business decision-making
spellingShingle Exploring generation Z's use of AI advice in business decision-making
Correia, Inês Monteiro Saraiva
Artificial intelligence
Generation Z
Generation X
Business decision-making
AI advice
Trust
Inteligência artificial
Geração Z
Geração X
Tomada de decisões empresariais
Conselhos de IA
Confiança
title_short Exploring generation Z's use of AI advice in business decision-making
title_full Exploring generation Z's use of AI advice in business decision-making
title_fullStr Exploring generation Z's use of AI advice in business decision-making
title_full_unstemmed Exploring generation Z's use of AI advice in business decision-making
title_sort Exploring generation Z's use of AI advice in business decision-making
author Correia, Inês Monteiro Saraiva
author_facet Correia, Inês Monteiro Saraiva
author_role author
dc.contributor.none.fl_str_mv Lettl, Christopher
Kommol, Erik
Veritati
dc.contributor.author.fl_str_mv Correia, Inês Monteiro Saraiva
dc.subject.por.fl_str_mv Artificial intelligence
Generation Z
Generation X
Business decision-making
AI advice
Trust
Inteligência artificial
Geração Z
Geração X
Tomada de decisões empresariais
Conselhos de IA
Confiança
topic Artificial intelligence
Generation Z
Generation X
Business decision-making
AI advice
Trust
Inteligência artificial
Geração Z
Geração X
Tomada de decisões empresariais
Conselhos de IA
Confiança
description There is an increasing number of companies employing AI in business decision-making. Companies are composed by a diverse workforce with different experiences and backgrounds thus, it becomes imperative to understand if generations rely differently on AI. This thesis aims to understand the differences between Generation Z and Generation X regarding their reliance on AI advice and explore how this relationship is affected by trust. Additionally, it assesses the moderating effect of confidence in own judgement. To collect the data, a quantitative betweensubjects survey was employed, where participants from both generations were presented with two hypothetical decision-making scenarios to evaluate their reliance on AI advice. Findings reveal that Gen Z relies more on AI advice compared to Gen X. Interestingly, no significant differences were found in dispositional trust in AI between the two generations. However, a strong positive correlation was identified between dispositional and situational trust, with situational trust significantly enhancing reliance on AI advice. This indicates that higher levels of situational trust are correlated with greater reliance on AI. Surprisingly, the moderating effect of confidence in own judgment was not confirmed. Exploratory analysis suggests that familiarity with AI might mediate the relationship between generational differences and reliance on AI advice. Additionally, it was found that higher confidence in own judgement negatively impacts reliance on AI advice. These insights underscore the complexity of understanding how trust affects reliance on AI across generational cohorts and highlight the importance of considering this factor in order to foster effective AI integration strategies within companies.
publishDate 2024
dc.date.none.fl_str_mv 2024-10-17
2024-09-09
2024-10-17T00:00:00Z
2025-01-23T15:44:53Z
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