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Adaptive Program Management Strategies for AI-Based Cyber Defense Deployments in Critical Infrastructure and Enterprise Digital Transformation Initiatives
Open accessAbstract
As artificial intelligence (AI) becomes an integral component of modern cyber defense, its deployment in critical infrastructure and enterprise environments demands strategic agility and contextual responsiveness.Traditional static program management methodologies are insufficient for navigating the evolving threat landscape, the complexity of AI systems, and the velocity of cyber-physical integration.This paper presents a comprehensive examination of adaptive program management strategies specifically tailored to guide AI-based cyber defense deployments in high-stakes environments, including national infrastructure, utility grids, healthcare networks, and large-scale enterprise IT ecosystems.The discussion begins with a macro-level exploration of the digital transformation challenges facing critical sectors, highlighting increasing threat sophistication, regulatory pressures, and the convergence of operational technology (OT) with information technology (IT).It then narrows to the unique challenges posed by AI-enhanced cybersecurity tools such as model drift, adversarial attacks, and explainability gaps which necessitate continuous oversight and iterative governance models.Leveraging principles from agile, DevSecOps, and continuous delivery frameworks, this paper introduces a hybrid adaptive management framework that supports modular AI integration, real-time risk assessment, and cross-domain collaboration between cybersecurity, data science, and executive governance teams.The proposed model emphasizes continuous stakeholder feedback loops, dynamic threat modeling, and governance structures that evolve in tandem with AI system maturity.Case examples from energy, finance, and defense sectors are analyzed to contextualize best practices and lessons learned, illustrating how adaptive program governance can accelerate secure AI adoption without compromising system integrity or compliance mandates.This strategic lens enables decision-makers to future-proof their digital security investments while fostering resilience and operational continuity in mission-critical domains.
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Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles
Guillen-Aguinaga, M., Aguinaga-Ontoso, E., Guillen-Aguinaga, L., Guillen-Grima, F., & Aguinaga-Ontoso, I. (2025) · Data · doi:10.3390/data10120201 · Cited by 37
Metadata
- Authors
- Adepoju, A. S.
- Corresponding author
- Adepoju, Adewumi Sunday
- Venue
- International Journal of Research Publication and Reviews
- Publisher
- Genesis Global Publication
- Published
- 2025-07
- Volume
- 6
- Issue
- 7
- Pages
- 5599-5615
- ISSN
- 2582-7421 (ISSN-L)
- OpenAlex
- W4412782652
- Cited by
- 3
- References
- 21
- Citations by year
- 2026: 2 · 2025: 1
- FWCI
- 3.13
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Journal of Research Publication and Reviews (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Keywords
- critical infrastructure cybersecurity, enterprise digital transformation, AI governance, model drift, adversarial attacks, explainability, DevSecOps, continuous delivery, IT-OT convergence, energy sector, financial services, defense industry, regulatory compliance
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