Policy Brief: Ethical Governance for Healthcare Cybersecurity: A Protocol for Agentic Artificial Intelligence

Abstract

<ns7:p>Background Healthcare systems face escalating cyber threats that compromise patient safety and institutional resilience. While artificial intelligence (AI) is increasingly deployed for intrusion detection and automated response, many systems remain reactive and insufficiently aligned with governance and regulatory standards. Methods This policy brief proposes a Governance Protocol for Ethical Agentic Artificial Intelligence in healthcare cybersecurity. The protocol articulates procedural and infrastructural principles for embedding ethical rule enforcement, explainability, regulatory alignment, and structured human oversight within autonomous AI decision loops. An operational illustration is provided through the Agentic Artificial Intelligence Framework (AAIF), developed using a Design Science Research methodology and evaluated in a simulated healthcare network environment using benchmark cybersecurity datasets. Results Evaluation across more than 280,000 healthcare-relevant network events demonstrated improvements in response time (34.8% reduction), recovery rate (41.6% increase), adaptability (27.5% improvement), and detection accuracy (96.8%). Governance metrics, including Ethical Compliance Rate (0.99), zero false escalations, and 35 ms decision latency, indicate that embedding governance constraints did not compromise technical performance. Conclusions Governance-embedded AI architectures can reconcile cybersecurity resilience with ethical accountability and regulatory coherence. Embedding governance as an architectural design condition rather than an external compliance layer offers a scalable pathway toward trustworthy digital health ecosystems, particularly in resource-constrained settings.</ns7:p>

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