Agentic AI refers to artificial intelligence systems designed to pursue goals autonomously, chaining multiple steps without the need for constant human supervision. Unlike a model that is limited to answering a specific question, an agent plans a sequence of actions, decides which tools to use, and acts on its environment, adjusting its behavior based on the results it obtains.
Its relevance lies in the leap from text generation toward the execution of real tasks. These systems typically combine several capabilities:
- Reasoning and planning to decompose a goal into subtasks.
- Use of external tools, such as web searches, APIs, or databases.
- Memory to maintain context between successive steps.
A practical example would be an agent that, when tasked with organizing a trip, searches for flights, compares prices, books accommodation, and adds events to the calendar. The important nuance is gradual autonomy: the greater the capacity to act without intervention, the greater the need for control mechanisms, traceability, and well-defined safety boundaries.