Autonomous systems where AI agents iteratively plan, execute, and evaluate multi-step tasks using integrated tools and environmental feedback.
Unlike conversational LLMs that need a human prompt at each step, Agentic Workflows work toward high-level goals on their own. They break objectives into sub-tasks, execute code, query databases, and correct their own errors. Managing the Control Boundaries around these autonomous agents is the main challenge in enterprise deployment.
See also Control Boundaries, Private AI, Digital Transformation and Enterprise Architecture.