Principles For The Safe and Ethical Implementation of Artificial Intelligence Agents in Cybersecurity Defense

Abstract

Introduction: Cybersecurity has become a structural precondition for the resilience, trust, and legitimacy of digital societies, while recent advances in agentic artificial intelligence are transforming how defensive capabilities are designed and governed. Objective: This article examines how AI agents can be implemented in cybersecurity defense in ways that are technically safe, ethically robust, and institutionally accountable. Method: The study employs an integrative structured literature review of peer reviewed articles, technical standards, and institutional reports published mainly between 2018 and 2025, synthesizing evidence on multi agent architectures, agent security, and AI governance. Results: The analysis develops a functional taxonomy of cybersecurity AI agents, outlines defense in depth architectures for perception, reasoning, and response, and consolidates empirical findings on multi agent intrusion detection and security operations, together with documented adversarial vulnerabilities, privacy risks, and governance gaps. It proposes a maturity model and a deployment checklist that align agent autonomy with risk appetite, observability, and human oversight. Conclusions: The study concludes that agentic AI can strengthen cyber resilience only when embedded in layered architectures, constrained by explicit policies, supported by continuous evaluation benchmarks, and integrated into multi level governance frameworks that preserve human accountability and recognize the dual use nature of autonomous systems.