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Agentic AI

Von Juan Beltrán, Industrial B2B AI Transformation Executive.

Agentic AI is appropriate when a system must make a bounded decision, act across tools, and verify the result without a human closing the normal path. The executive design problem is not how autonomous the demo looks, but where autonomy creates enough value to justify its control burden.

Kernaussagen

  • Agents change the unit of software from app to workflow.
  • Human-in-the-loop is the new technical debt when used as a default.
  • Machine identity and audit trails are now first-class governance concerns.

Entscheidungsbriefing

Agentic AI is appropriate when a system must make a bounded decision, act across tools, and verify the result without a human closing the normal path. The executive design problem is not how autonomous the demo looks, but where autonomy creates enough value to justify its control burden.

Entscheidungskriterien

  • The workflow has a repeatable objective and bounded action space.
  • Failures are detectable, reversible, and proportionate to the value.
  • Identity, permissions, evidence, escalation, and accountability are designed.

Zu prüfende Evidenz

  • Autonomous completion and exception rates.
  • Action-level logs from context through outcome.
  • Comparison with a simpler assisted or automated workflow.

Was ich am Montag tun würde

Apply the Button Test to your highest-profile agent: identify every manual approval in the core loop, then decide whether to remove it with controls or describe the system honestly as an assistant.

Über den Autor

Juan Beltrán, Executive für KI-Transformation im industriellen B2B, mit Sitz in Zug (Schweiz). Wie diese Website recherchiert, Quellen belegt und Fehler korrigiert.

Rechtlicher Hinweis

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Kanonische URL: https://juanbeltran.ch/de/topics/agentic-ai