Abstract
Agentic artificial intelligence combines goal-directed reasoning, planning, memory, tool use, adaptation and multi-agent coordination with the ability to affect external systems. This capability raises problems of authorization, safety, human oversight, accountability and the evidence required to justify reliance. This non-systematic integrative survey distinguishes AI ethics, responsible AI, governance, trustworthiness, assurance, explainability, security and controllability; synthesizes preventive, detective, corrective, human-based and agent-based controls; and compares responsibility and oversight arrangements across the agent lifecycle. Building on established governance and meaningful-human-control research, it proposes an authority-control-assurance-accountability mapping that connects normative requirements to delegated decision rights, enforceable controls, observable evidence, escalation conditions and identifiable organizational owners. Two fictional cases illustrate the proposed mapping for document access and software changes. The framework is a conceptual synthesis rather than an empirically validated assurance standard. The survey identifies limitations of supervisory-agent independence, long-horizon explanation, dynamic authorization and continuous re-assurance, and specifies research questions for future evaluation.