Evaluating public sector employee perceptions towards artificial intelligence and generative artificial intelligence integration

This study investigates the emerging field of innovative technology applications for public usage, focusing on employee perspectives. The research employs a questionnaire-based approach, collecting responses from 439 participants and examining demographics, technological proficiency, utility perceptions, personal data concerns, attitudes towards artificial intelligence and generative artificial intelligence, and willingness to endorse technology adoption. The data analysis minimises discrepancies between predicted and actual values through multiple linear regression. In addition, statistical methods such as Spearman’s ρ, the Wilcoxon–Mann–Whitney test and chi-square statistics are employed to consolidate the findings, ensuring the thoroughness and validity of the research process. The results indicate a positive inclination among participants to perceive artificial intelligence as augmentative rather than a replacement in public usage contexts. The research’s originality lies in the unique contribution of employees to technology adoption and strategic knowledge asset renewal for the management in the public domain.

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Institutions

Publication Details

Journal
Journal of Information Science
Published
2024-11-20
DOI
https://doi.org/10.1177/01655515241293775
Citations
9
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
4.76
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article

Evaluating public sector employee perceptions towards artificial intelligence and generative artificial intelligence integration

Luca Giraldi, Edyta Rudawska, Luca Rossi
9 citations
Journal of Information Science
Big Data and Business Intelligence
4.76
article

Evaluating public sector employee perceptions towards artificial intelligence and generative artificial intelligence integration

Luca Giraldi, Edyta Rudawska, Luca Rossi
article en
9 citations

Abstract

This study investigates the emerging field of innovative technology applications for public usage, focusing on employee perspectives. The research employs a questionnaire-based approach, collecting responses from 439 participants and examining demographics, technological proficiency, utility perceptions, personal data concerns, attitudes towards artificial intelligence and generative artificial intelligence, and willingness to endorse technology adoption. The data analysis minimises discrepancies between predicted and actual values through multiple linear regression. In addition, statistical methods such as Spearman’s ρ, the Wilcoxon–Mann–Whitney test and chi-square statistics are employed to consolidate the findings, ensuring the thoroughness and validity of the research process. The results indicate a positive inclination among participants to perceive artificial intelligence as augmentative rather than a replacement in public usage contexts. The research’s originality lies in the unique contribution of employees to technology adoption and strategic knowledge asset renewal for the management in the public domain.

Journal of Information Science
University of Szczecin (PL), University Niccolò Cusano (IT), University of Macerata (IT)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Big Data and Business Intelligence
4.76
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