Dissecting the Problem of Agentic AI Accountability:

In 2026, A. Stavropoulos accurately diagnosed the managerial gap in agentic AI: machines act at millisecond speed, institutions at the speed of meetings. Yet his commentary stops precisely where engineering begins — at the call to “take accountability into account.” The present work goes further: it dissects the problem and presents a ready-made architectural solution — a four-level system of responsibility and compliance (a hard regulator, an AI trend analyst, an IQ conflict verifier, and a human situation center) with an external legal depository. The key thesis: agentic AI accountability is not an institutional utopia, but an engineering task solved by embedding control loops into the architecture itself. Academic discourse that describes the gap without moving to design leaves the problem open at exactly the point where it must be closed. We also show that even the formulation of the problem became operationally accessible only after its core was extracted by the AI tool DeepSeek — a symptom in itself: the analysis of complex texts increasingly requires a co-analyst capable of separating substance from rhetoric. The result: there is no need for the court to chase the agent. The court must be embedded in the loop before the agent does something irreversible.