From Classroom to Cyber Front: AI Literacy for National Security Workforces
Abstract
Purpose. To systematically review the literature on the integration of artificial intelligence (AI) into higher education for national security workforce development, with particular attention to developing-country contexts.
Method. Following PRISMA 2020 reporting guidelines, relevant publications from 2019–2026 were selected through structured searches of bibliographic databases, publisher platforms, and institutional repositories. The heterogeneous evidence base, comprising peer-reviewed studies, conference papers, policy documents, and institutional reports, was analysed using narrative thematic synthesis. The findings were organised around the research questions and interpreted through securitization theory and human capital theory.
Findings. The reviewed evidence identifies foundational AI literacy as a prerequisite for developing applied digital competencies and security-specific capabilities. National strategies increasingly assign higher education an important role in AI workforce development. However, the evidence from developing-country contexts indicates persistent constraints, including limited AI-specialised programmes, low faculty adoption outside STEM fields, resource limitations, and institutional fragmentation.
Theoretical implications. The review integrates securitization theory and human capital theory to interpret the gap between the strategic prioritisation of AI-capable security workforces and the educational investment required to develop them. AI-literate workforce capacity is conceptualised as a form of security-relevant human capital rather than as a referent object of securitization.
Originality/value. The study proposes the AI-Ready Security Workforce (ARSW) conceptual readiness framework, comprising four interrelated dimensions: foundational AI literacy, applied digital competencies, domain-specific security integration, and strategic national capacity. The framework is presented as a diagnostic heuristic rather than an empirically validated maturity scale.
Limitations/future research. The evidence base is heterogeneous, cybersecurity education is used as a proxy for broader national security professions, and the developing-country evidence is limited. The ARSW framework has not been empirically validated. Future research should validate the framework across different national and institutional contexts and examine the transition of graduates from AI-integrated curricula into security-sector employment.
Paper type: Review article.
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References
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