Generative AI for enhanced cybersecurity: building a zero-trust architecture with agentic AI

Gurram, Abhyudaya (2025) Generative AI for enhanced cybersecurity: building a zero-trust architecture with agentic AI. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 2380-2396. ISSN 2582-8266

Generative AI is transforming cybersecurity by enhancing zero-trust architecture implementation through dynamic capabilities that adapt to evolving threats. This convergence represents a paradigm shift from traditional perimeter-based security to a model that assumes breach and verifies every access request. The integration of generative AI with zero-trust principles enables continuous authentication through behavioral analysis, autonomous threat hunting, and incident response orchestration while maintaining human oversight. The architecture comprises interconnected components including data collection layers, AI analysis engines, policy enforcement points, human interfaces, and continuous improvement loops. Despite its potential, implementation faces challenges including adversarial attacks against AI systems, data privacy concerns, and the need for model explainability. Organizations can achieve resilient security postures by balancing AI automation with appropriate human judgment, creating a cybersecurity ecosystem that proactively identifies and mitigates threats before traditional indicators appear.