Business and Social Sciences
Business and social sciences | Online ISSN 3067-8919
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Volume 1 Number 1 2021
RESEARCH ARTICLE (Open Access)
AI-Driven Threat Intelligence and Cybersecurity Performance in US Organizations: Examining the Roles of Adoption, System Complexity, and Workforce Expertise
Md Jahidul Islam Ridoy1*, Chowdhury Amin Abdullah2
Business and Social Sciences 1 (1) 1-8 https://doi.org/10.25163/business.1110777
Submitted: 31 January 2021 Revised: 30 March 2021 Accepted: 05 April 2021 Published: 07 April 2021
Abstract
Background: Cybersecurity has become one of the defining operational challenges of the digital age, yet the organizational conditions that determine how well AI-based defense systems actually perform remain surprisingly underexplored. This study set out to examine three factors — AI adoption, system integration complexity, and workforce expertise — and their relative contributions to cybersecurity performance outcomes across United States-based organizations.
Methods: A cross-sectional, quantitative survey design was employed, with data collected from 325 cybersecurity professionals and IT policy stakeholders recruited through purposive sampling. Cybersecurity performance was operationalized as a composite index integrating detection accuracy, response efficiency, and system stability — three dimensions assessed alongside the predictor variables using validated five-point Likert instruments. Pearson correlation and multiple linear regression analyses were conducted to examine bivariate relationships and multivariate predictive effects respectively.
Results: The results were, broadly speaking, coherent and theoretically consistent. AI adoption emerged as the strongest individual predictor of cybersecurity performance (β = 0.41), followed by workforce expertise (β = 0.34) and system complexity (β = 0.26). Together, the three predictors explained 67% of variance in performance outcomes (R² = 0.67, F = 138.2, p = 0.048). Relative contribution analysis further confirmed AI adoption as the dominant influence, accounting for approximately 38% of explained variance.
Conclusion: These findings suggest that effective cyber defense is neither purely technological nor purely human — it is fundamentally socio-technical. Organizations and policymakers seeking to strengthen national cybersecurity posture will likely need to invest simultaneously in AI infrastructure, workforce development, and architectural simplification to realize the full protective potential that these systems promise.
Keywords: Cybersecurity performance; AI-driven threat intelligence; workforce expertise; system integration complexity; socio-technical systems
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