Oracle has rolled out ChatGPT Work and Codex across recruiting, applications, and engineering teams to convert specialist knowledge into fast, repeatable workflows. Tasks that previously depended on experts and took days can often now be completed in minutes.
Users and measurable impact
More than one hundred thousand Oracle employees use ChatGPT Work and Codex in areas such as talent acquisition, the Oracle Applications Lab, and the IT organization. For example, the talent acquisition team built a talent market intelligence tool with ChatGPT Work that takes a job description, researches comparable roles, benchmarks compensation, and assesses the talent pool across relevant locations. Information that once required 2–4 days to compile is now available to recruiters before a hiring manager conversation. Jan Ackerman, Senior Vice President and Global Head of Talent Acquisition at Oracle, said: “We’ve gone from zero to a hundred. Now we’re able to sit down and prep for about 15 to 20 minutes using the tool that we’ve built using [ChatGPT] Work.”
Aside from speed, the process has become more consistent: the intake and research are standardized so every hiring manager receives the same quality of data and insights regardless of which recruiter handled the search.
From plain-language questions to SQL and reports
The Oracle Applications Lab created an ontology of the company’s objects, relationships, and rules that enables Codex to translate plain-language business questions into reliable SQL queries. A business user describes the desired outcome, Codex determines which internal systems to query, gathers the data, and returns an analysis, report, or application.
Oracle staff reported cases where queries that previously took hours now return almost immediate answers, and in checks the AI-generated results matched those from the manual process.
Production engineering and incident response
Site reliability engineers use Codex to gather incident context and automatically surface the correct playbook. As a result, SREs spend more time guiding decisions and less time searching for information; Lam said a typical simple incident that once took about an hour to resolve can now be handled in minutes.
Human oversight and best practices
Oracle stresses that AI does not replace human responsibility. Team leaders highlighted several lessons:
- Apply the right guardrails: “You have to still be very responsible about your system design, your architecture, your security, and how you would like Codex to structure the code for you,” Lam warned.
- Provide prototypes rather than detailed specs: Barry Shilmover, Vice President and Technical Advisor to the CIO, said he now captures ideas as prototypes instead of on paper.
- Own and maintain the code: Lam cautioned that failing to work alongside Codex can lead to unmaintainable code.
Changing how the company operates
Oracle is shifting how work is done across lines of business: teams describe the outcome they want and let Codex and ChatGPT determine how the work is executed. With thousands of ChatGPT and Codex users already, employees apply these tools to many tasks. As Barry Shilmover put it: “I don’t know what the answer is because I don’t know what my next problem to solve will be. I just know that one of the first things I’ll do is I’ll leverage Codex to do that.”
Oracle’s experience shows AI can significantly reduce preparation times, standardize procedures, and speed decision-making—provided human oversight, careful system design, and code ownership remain in place.
