Business Value Creation Through Artificial Intelligence-Enabled Cybersecurity Systems
Abstract Cybersecurity has traditionally been framed as a cost centre concerned with loss prevention, yet a growing body of practitioner and academic opinion now argues that, when powered by artificial intelligence (AI), cybersecurity can function as a genuine driver of business value rather than a purely defensive expenditure. This study examines the contribution of AI-enabled cybersecurity systems to business value creation, conceptualised across three dimensions: cost efficiency and loss avoidance, operational performance and productivity, and competitive advantage and stakeholder trust. Anchored on the Resource-Based View (RBV) of the firm, the study formulated three objectives, three research questions and three corresponding hypotheses. A descriptive survey design was adopted, involving 226 purposively sampled managers and information-security personnel drawn from finance, telecommunications and professional-services firms. Data were analysed using descriptive statistics and chi-square tests of association at the 0.05 level of significance. Findings show that AI-enabled cybersecurity significantly influences all three value dimensions, with competitive advantage and stakeholder trust recording the strongest observed effect, followed by cost efficiency and loss avoidance, and then operational performance and productivity. The study concludes that AI-enabled cybersecurity meets the conditions of a valuable, rare, imperfectly imitable and non-substitutable strategic resource capable of generating sustained business value beyond risk mitigation alone. Recommendations are offered for business leaders, chief information security officers and institutions engaged in cybersecurity capacity-building. Keywords: Artificial intelligence; Cybersecurity; Business value creation; Competitive advantage; Resource-Based View
Authors
- PhD Nsikak Stephen Edet
- M.Sc. Precious Nsikak Stephen
- Peter Anthony Ene M.Sc.*
Institutions
- Baze University (NG)
- University of Uyo (NG)
- Embedded Systems (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-05
- DOI
- https://doi.org/10.5281/zenodo.22330267
- Primary Topic
- Supply Chain Resilience and Risk Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00