AI supports exploratory data analysis by detecting patterns, clusters, themes, and relationships in large unstructured datasets, helping practitioners understand the data before deeper analysis.

In the Model Context Protocol, the client manages communication between the AI application and MCP servers, coordinating requests for tools, resources, and context needed during task execution.

An approval gate requires human authorization before a high-impact or externally visible action is executed, such as sending an AI-drafted customer email.

Data transformation changes data from one format or structure into another, such as converting CSV rows into a Markdown table for reporting.

When input exceeds the context window, the model cannot process all provided text at once, so earlier content may be truncated or pushed out of the active context.