Trust by Design: A Unified Framework for Explainable, Secure, and Reliable Agentic Artificial Intelligence

Agentic artificial intelligence systems combine autonomous planning, memory, tool use, and multi-agent coordination, creating risks that extend beyond the behavior of an individual model to include interactions with external environments and operational workflows. Trustworthy deployment therefore requires assurance that integrates explainability, security, reliability, and governance across system layers and throughout the lifecycle. This paper proposes a unified framework that connects decision- and action-level explanations with threat modeling, bounded permissions, runtime verification, traceability, and reliability monitoring. It treats explanations as one component of assurance rather than a sufficient basis for trust, and situates them alongside calibrated human oversight and enforceable operational controls. The framework provides a structured basis for designing and evaluating agentic systems whose actions are interpretable, constrained, and auditable.