Glossary
Agentic AI
AI systems that autonomously execute multi-step tasks to reach a goal.
Definition
Agentic AI describes AI systems that can plan, choose tools, take actions, and verify outcomes across multiple steps to complete a goal — rather than just generating a single response to a single prompt. Modern agentic systems combine large language models with tool use, memory, and feedback loops.
Context
Agentic AI is the practical successor to copilots. Copilots assist a human doing the work; agents do the work and surface a result the human signs off on. In enterprise settings, agentic AI is used for document operations, decisioning, retrieval, and customer-facing automation where the work is too long-running or branching for a single-shot prompt.
Related terms
Large Language Model (LLM)A neural network trained on massive text corpora to predict next tokens.Read Tool UseAn LLM calling external functions to extend its capabilities.Read Retrieval-Augmented Generation (RAG)Injecting retrieved documents into an LLM prompt to ground outputs.Read AI Evaluation (Evals)The practice of systematically measuring AI system quality.Read