A Quantitative Study of Risk Scores and the Effectiveness of AI-Based Cybersecurity Awareness Training Programs

Cybersecurity awareness training plays a dynamic role for organizations in certifying resources\u27 accessibility. This paper determines the correlation between an employee\u27s risk score and the effectiveness of AI-based security awareness training that deals with cyber threats. The research uses the Unified Theory of Acceptance and Use of Technology to update prior research, revealing that at-risk employees\u27 behavior and information security awareness training implementation make up successful interventions. However, those studies did not discuss AI training, and so this research fills that literature gap. This study used a quantitative research design. The researcher analyzed survey responses using Pearson\u27s Correlation and an independent t-test to determine statistically significant relationships and differences between employees\u27 risk scores and an AI-based security awareness training programs\u27 effectiveness. The calculations came from a sample of 200 participants from two different organizations. The Pearson product correlation of employee\u27s risk scores and the effectiveness of the security awareness training program was statistically significant. The researcher also conducted an independent-samples t-test to compare the employees\u27 risk scores by gender. There were no significant differences in scores. Male was higher than female ones. The mean difference was minimal. The findings herein help interpret the role of information security awareness training in the workplace, promoting behavioral changes that would impede data violations by including the users\u27 vulnerability and the severity of intimidation, and the response to a threat in prognosticating behavior intentions