Oracle AI Assistant

Oracle Analytics AI Assistant is an AI-powered assistant built into Oracle Analytics Cloud (OAC) that helps users analyze data and create, modify, and refine visualizations using natural-language prompts. Instead of requiring users to manually configure every visualization, the Assistant lets them ask questions about indexed datasets or subject areas and receive visualizations and data insights in response.

The Assistant is designed primarily for business analytics workflows. Users can ask questions such as sales or profitability queries, continue conversations with follow-up prompts, refine the generated visualization, and add useful visualizations to an OAC workbook or watchlist. Visualizations can also be exported and shared.

Oracle has expanded the AI capabilities available across Oracle Analytics Cloud beyond conversational visualization creation. Current AI Assistant features include natural-language data analysis, visualization generation, dataset preparation assistance, metadata generation, natural-language summaries, and deeper AI-powered analytical insights.

Oracle Analytics AI Assistant can work with Oracle’s built-in generative AI capabilities or with supported customer-selected generative AI models. Oracle states that its embedded model is optimized for analytics conversations and understands the context of the current workbook and datasets.

The platform also supports Oracle Analytics AI Agents. These agents allow organizations to provide custom instructions and organizational knowledge to improve the relevance of Assistant responses. Oracle uses retrieval-augmented generation (RAG) with AI Agents so relevant enterprise information can be retrieved before the LLM generates an answer.

Security and governance are important parts of the service. Assistant requests are processed within Oracle Cloud Infrastructure, and Oracle states that customer data is not used to train its models. Administrators can control access through permissions and determine which datasets and subject areas the Assistant can use.

The Assistant is particularly useful for organizations that already use Oracle Analytics Cloud and want to make analytics more accessible to analysts, business users, and executives without requiring every user to have advanced dashboard-building or data-analysis skills.

Pricing

Oracle Analytics AI Assistant is primarily a capability within Oracle Analytics Cloud, rather than a separately marketed standalone AI chatbot.

Oracle Analytics Cloud uses consumption-based pricing. Oracle states that OAC pricing can be based on OCPU/hour consumption or user/month, depending on the selected pricing model. Named-user subscriptions are also available.

Generative AI features can additionally consume AI Data Platform Units (AIDP Units). Oracle Analytics Cloud uses AIDP Units to measure generative AI consumption across supported models. The number of units consumed depends on the model and the requests processed.

Oracle’s current documentation states that customers can purchase additional AIDP Units, enable usage-based billing for additional consumption, or use a free LLM option when applicable. Oracle also notes that overage charges are scheduled to begin on or after September 30, 2026.

Pricing Model: Consumption-based

Pricing Note: Oracle Analytics Cloud is priced according to OCPU/hour or user/month options. Generative AI usage can consume AIDP Units depending on the selected model and AI feature. Pricing therefore varies according to the OAC deployment, subscription, model, and usage.

Review

Oracle Analytics AI Assistant is a strong option for organizations that want conversational AI directly inside an enterprise analytics platform. Its biggest advantage is the connection between natural-language interaction and actual analytics workflows: users can ask questions, generate visualizations, refine them through follow-up prompts, and add the results to their workbooks.

Its support for multiple generative AI models and Oracle Analytics AI Agents also gives organizations flexibility when building more specialized analytics experiences. AI Agents can incorporate organizational knowledge and RAG, making the system more useful for context-specific business questions.

The main limitation is that it is designed around Oracle Analytics Cloud rather than being a general-purpose AI assistant. Organizations that do not already use Oracle’s analytics ecosystem may find the platform less suitable than standalone AI assistants or dedicated business intelligence tools.

Another consideration is AI usage cost. Although Oracle Analytics Cloud provides different pricing options, generative AI features can consume AIDP Units, meaning organizations need to monitor usage and model selection to manage costs effectively.