Intelligent Protection: A Study of the Key Drivers of Intention to Adopt Artificial Intelligence (AI) Cybersecurity Systems in the UAE

Aim/Purpose: This research investigates factors influencing consumers’ decisions to use artificial intelligence cybersecurity technology in the United Arab Emirates. Background: The cyber-security risks are getting more complex as technology develops, putting the United Arab Emirates (UAE) businesses and government agencies at risk of severe losses from cybercrime. Methodology: A correlational study design and a quantitative research approach were employed, and 340 professionals working for different government and semi-government organizations in the United Arab Emirates were given questionnaires. The PLS-SEM approach was used to analyze the replies. Contribution: The present research framework remedies the inherent limitations in the PMT model by adding factors used to explain the influence of environmental factors and individual difference factors on behavior. This research framework is an extended application of the PMT model in the context of AI-based cybersecurity systems. Meanwhile, this study confirms the importance of perceived vulnerability in AI technology scenarios. Findings: The findings demonstrated that users’ adoption intentions were significantly and favorably impacted by social influence, facilitating conditions, perceived vulnerability, and perceived response efficacy. Meanwhile, job insecurity enhanced employees’ resistance to change, making resistance to change a major resistance to the intention to adopt AI-based cybersecurity systems. Recommendations for Practitioners: The report offers crucial insights that organizations can utilize to evaluate their readiness for adopting AI-based cybersecurity technologies and create plans to lessen employee resistance to advancements in the cybersecurity industry. Recommendation for Researchers: Researchers on this specific application can make use of the extension of the framework. Impact on Society: The research can be utilized to evaluate their readiness to adopt AI-based cybersecurity technologies. Future Research: Future research should broaden the scope to acquire a more thorough understanding of the behavioral intentions to use AI-cybersecurity systems in the United Arab Emirates. Other elements that could be considered include facilitating settings, Artificial Intelligence knowledge, social impact, effort efficacy, and other frameworks.

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Publication Details

Journal
Interdisciplinary Journal of Information Knowledge and Management
Published
2025-01-01
DOI
https://doi.org/10.28945/5430
Citations
1
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
2.48
Controls
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article

Intelligent Protection: A Study of the Key Drivers of Intention to Adopt Artificial Intelligence (AI) Cybersecurity Systems in the UAE

Normalini Md Kassim, Mohammed Rashed Mohamed Al Humaid Alneyadi
1 citations
Interdisciplinary Journal of Information Knowledge and Management
Organizational and Employee Performance
2.48
article

Intelligent Protection: A Study of the Key Drivers of Intention to Adopt Artificial Intelligence (AI) Cybersecurity Systems in the UAE

Normalini Md Kassim, Mohammed Rashed Mohamed Al Humaid Alneyadi
article en
1 citations

Abstract

Aim/Purpose: This research investigates factors influencing consumers’ decisions to use artificial intelligence cybersecurity technology in the United Arab Emirates. Background: The cyber-security risks are getting more complex as technology develops, putting the United Arab Emirates (UAE) businesses and government agencies at risk of severe losses from cybercrime. Methodology: A correlational study design and a quantitative research approach were employed, and 340 professionals working for different government and semi-government organizations in the United Arab Emirates were given questionnaires. The PLS-SEM approach was used to analyze the replies. Contribution: The present research framework remedies the inherent limitations in the PMT model by adding factors used to explain the influence of environmental factors and individual difference factors on behavior. This research framework is an extended application of the PMT model in the context of AI-based cybersecurity systems. Meanwhile, this study confirms the importance of perceived vulnerability in AI technology scenarios. Findings: The findings demonstrated that users’ adoption intentions were significantly and favorably impacted by social influence, facilitating conditions, perceived vulnerability, and perceived response efficacy. Meanwhile, job insecurity enhanced employees’ resistance to change, making resistance to change a major resistance to the intention to adopt AI-based cybersecurity systems. Recommendations for Practitioners: The report offers crucial insights that organizations can utilize to evaluate their readiness for adopting AI-based cybersecurity technologies and create plans to lessen employee resistance to advancements in the cybersecurity industry. Recommendation for Researchers: Researchers on this specific application can make use of the extension of the framework. Impact on Society: The research can be utilized to evaluate their readiness to adopt AI-based cybersecurity technologies. Future Research: Future research should broaden the scope to acquire a more thorough understanding of the behavioral intentions to use AI-cybersecurity systems in the United Arab Emirates. Other elements that could be considered include facilitating settings, Artificial Intelligence knowledge, social impact, effort efficacy, and other frameworks.

Interdisciplinary Journal of Information Knowledge and ManagementVol. 20
Hospital Universiti Sains Malaysia (MY)
Openalex Percentile: Top 12%
Organizational and Employee Performance
2.48
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