AI Glossary · Agentic AI
Agentic AI
AI systems that pursue goals autonomously by planning multi-step actions, calling tools and APIs, and revising their approach based on feedback — rather than only responding to a single prompt.
Why it matters
Shifts AI from advisor to operator; changes org design, controls and ROI models.
Related terms in Agentic AI
- AI Agent
- A software entity built around an LLM that perceives context, reasons over a task, invokes tools, and produces an outcome — often on behalf of a user or another agent.
- Autonomy Level
- A taxonomy (advisor → co-pilot → supervised agent → autonomous agent) describing how much human oversight a workflow requires.
- Digital Employee
- A packaged agent (with a role, tools and SLAs) that performs a bounded function — collections, scheduling, tier-1 support — measured like a human FTE.
- Function Calling / Tool Use
- A model capability that produces structured JSON to invoke external functions, APIs or databases — the mechanism behind most agentic workflows.
- MCP (Model Context Protocol)
- An open protocol for exposing tools, data and prompts to AI models in a standardized way, simplifying agent-to-system integration.
- Memory (Agent Memory)
- Persistent state an agent carries across turns or sessions — short-term (scratchpad), long-term (vector store), episodic (past runs).