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How Oracle turns days of work into minutes with ChatGPT and Codex

By Jakub Antkiewicz

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2026-10-09T14:59:14Z

Oracle Integrates OpenAI Models for Productivity Gains

Enterprise technology firm Oracle has begun integrating generative AI models from OpenAI, specifically ChatGPT and Codex, into its internal workflows. The initiative is aimed at significantly compressing task completion times, with the company citing the ability to turn processes that previously took days into a matter of minutes. This development is notable as it demonstrates a major incumbent in the enterprise software market leveraging third-party AI to directly address operational efficiency and developer productivity.

The implementation focuses on applying each model to its area of specialization within Oracle's business and engineering units. By utilizing OpenAI's technology, Oracle is targeting specific bottlenecks in both software development and administrative processes. The goal is to automate and accelerate tasks that are historically manual and time-intensive, freeing up personnel to focus on more complex strategic work.

Technical Applications and Broader Implications

  • ChatGPT: Applied to natural language tasks such as generating technical documentation, summarizing complex reports, and drafting internal communications.
  • Codex: Used to accelerate application development, assist in debugging, and generate complex SQL queries for Oracle's core database products.

Oracle's move to adopt these tools has implications for the broader enterprise software market. It puts pressure on competitors to demonstrate similar AI-driven productivity enhancements within their own operations and product offerings. Furthermore, it underscores a growing trend where large technology companies opt to integrate established, high-performing AI models from specialists like OpenAI rather than relying exclusively on in-house development, thereby accelerating their time-to-market for AI-powered features.

Oracle's adoption of OpenAI models is less about technological novelty and more a pragmatic move to embed generative AI directly into core business processes, shifting the competitive battleground from model creation to practical, high-ROI application.
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