When to Use an Oracle Analytics AI Agent

This section outlines appropriate scenarios for using an Oracle Analytics AI Agent, ensuring optimal use of automated insights and efficiency in your analytics workflows.

AI agents are domain-specific functional experts. Think of an AI agent as a subject-matter expert in a specific business domain, supporting focused Oracle Analytics AI Assistant interactions. The more focused its scope, the more precise and meaningful its responses will be.

AI agents are designed to support Oracle Analytics AI Assistant users within a clearly-defined business domain. Each agent is associated with a specific dataset, curated knowledge documents, and tailored instructions. Together, these components significantly improve the ability of the Oracle Analytics AI Assistant and underlying LLM to interpret user questions accurately within a particular context.

By reducing ambiguity and grounding the AI in domain-specific semantics, instructions, and documentation, organizations can create highly specialized AI agents. For example, you can create an AI agent focused on the company's sales backlog, another AI agent with an employee attrition focus, or an AI agent focused on customer service request volumes. Each AI agent draws from a targeted set of data sources, applies customized response expectations, and incorporates relevant business knowledge such as competitive information, HR policies, or service level agreements.

AI agents are created by authors for use by consumers. Consumers can view dashboards or workbooks and rely on the Oracle Analytics AI Assistant to interact with their data using natural-language questions. Consumers don’t create new visualizations themselves, instead they use agents to obtain quick clarifications, follow-up answers, and drill-down insights within the context of the analytics content they are exploring.

You can use Oracle Analytics AI Agents within a workbook or independently.