Agentic AI
Definition
Agentic AI is the design approach in which AI systems plan and execute multi-step work autonomously, using tools and feedback, instead of generating a single response. It shifts the unit of automation from an answer to a completed task.
The distinction matters commercially: generative AI produces content a person still has to place somewhere; agentic AI completes the process step. That is where measurable hours are saved.
Agentic systems are built with clear termination conditions, retries and fallbacks. Without them, autonomy turns into unpredictable cost and silent errors.
In practice
- Multi-step execution with tool use and self-checking
- Requires budgets, timeouts and stop conditions per run
- Value is measured in completed cases, not generated text
Related terms
- AI agentAn AI agent is a program that pursues a goal on its own: it decides which steps to take, calls tools or APIs to take them, checks the result and repeats until the goal is reached or it hands over. Unlike a chatbot it acts, rather than only answering.
- OrchestrationOrchestration is the coordination layer that decides which agent, model or service handles which step, in what order, with which data, and what happens on failure. It is what turns individual agents into a dependable operational system.
- Human in the loopHuman in the loop means a defined point at which a person reviews, approves or corrects the AI system's work. The handover is designed in advance for specific triggers — value thresholds, low confidence, unknown counterparties — rather than left to chance.