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Poll: How satisfied are you with the current Oracle AI & Analytics product roadmap?

Alexandria Toothman-Oracle

On a scale from 1 to 10, how satisfied are you with the Oracle AI & Analytics product roadmap published on September 15th? (10 = Very satisfied; 5 = Somewhat satisfied; 1 = Not satisfied)

View the recently released Oracle AI & Analytics Product Roadmap https://community.oracle.com/products/oracleanalytics/kb/articles/32-product-roadmaps

Screenshot 2026-10-05 at 12.56.20 PM.png

Each quarter, we publish the Oracle AI & Analytics product roadmap, which includes AI Data Platform, OCI Enterprise AI, Fusion Data Intelligence, and Oracle Analytics. We take your feedback seriously. Please rate your satisfaction with the September 15 update, and share in the comments any areas you would like us to prioritize or clarify in future roadmap updates.

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Comments

D Grogan-Oracle

User_OCIPE

Not satisfied.

Oracle continues to position DV as the strategic analytics platform, yet key capabilities available in Classic Analytics are still missing. Customers are encouraged to migrate from Answers/Dashboards to DV, but the lack of features such as Calculated Items and Groups creates unnecessary migration barriers and forces reliance on workarounds.

The roadmap should focus not only on new AI capabilities but also on closing long-standing functional gaps that directly impact customer adoption, migration efforts, and day-to-day reporting requirements. Product parity with existing Oracle Analytics capabilities should be a higher priority.

AndresGlz2109

While I appreciate the continued investment in AI across Oracle’s portfolio, I still see a significant gap between Oracle’s AI capabilities and the pace and usability of leading platforms such as ChatGPT and Claude.

From an enterprise customer perspective, I would like to see Oracle place much more emphasis on openness and interoperability. Integrating Oracle data and applications with external LLMs and AI platforms is still more complex than it should be. Customers should be able to securely expose Oracle Fusion and FDI data to the AI platform of their choice through standardized capabilities such as MCP, APIs, and other native connectors, without requiring significant custom development or additional layers of infrastructure.

The commercial model is another concern. It is often difficult to understand the incremental cost of enabling and scaling the different AI capabilities across OCI, Fusion, FDI, and the AI Data Platform. A simpler and more transparent pricing model would make it much easier to build a business case for adoption.

Ultimately, Oracle has a tremendous advantage because it already owns the applications, business processes, security model, and enterprise data. However, that advantage is reduced if customers find it easier, faster, and more cost-effective to build AI solutions using external platforms.

I would like future roadmaps to focus more clearly on closing that usability gap: simpler integration with leading LLMs, stronger native MCP capabilities, easier access to Fusion transactional data, clearer pricing, and practical end-to-end use cases that demonstrate how customers can move from an AI concept to a production solution quickly.

Andres G

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