Oracle turns days of work into minutes with AI
Oracle is using ChatGPT Work and Codex across recruiting, engineering and operations to turn tasks that once took days into workflows completed in minutes. The company says more than 100,000 employees are using the tools.
Radwan AbdulhadiEditor and technology writer
AI workflows spread across Oracle
Oracle says it is using ChatGPT Work and Codex across talent acquisition, the Oracle Applications Lab and its IT organization. The company’s account, published by OpenAI News, describes a broad shift from specialist-led work that could take days toward repeatable workflows that employees can complete in minutes. Further details are available from OpenAI News in the original source material.
More than a hundred thousand employees across Oracle are using the two tools, according to the company. The applications differ by department, but follow a similar pattern: employees describe the outcome they need, while the AI helps organize research, query internal information or build software needed to produce it.
Oracle presents the change as an operational one rather than a single product deployment. Recruiters can prepare for hiring discussions more quickly, business users can obtain answers without navigating multiple systems, and technical teams can create tools without assembling a large development effort for every project.
Recruiting research in minutes
Oracle’s talent acquisition team used ChatGPT Work to build a talent market intelligence tool. The tool takes a job description, researches comparable roles, benchmarks compensation and assesses the available talent pool across relevant locations.
Jan Ackerman, Oracle’s senior vice president and global head of talent acquisition, says the information previously took two to four days to compile. Recruiters can now use the tool to prepare for a conversation with a hiring manager in about 15 to 20 minutes.
“We’ve gone from zero to a hundred,” Ackerman says in the company’s account. Beyond saving time, Oracle says the tool makes the intake process more consistent. Recruiters previously handled searches differently from one another, while the shared workflow is intended to give hiring managers a similar quality of data and insight regardless of which recruiter leads the search.
Plain-language questions become analysis
The Oracle Applications Lab built an ontology describing the company’s objects, relationships and rules. With that foundation, Codex can translate a business user’s plain-language question into a reliable SQL query.
The user describes the desired outcome, and Codex determines which internal systems to call, gathers the relevant information and returns an analysis, report or application. Oracle says this replaces a process in which answering a question could require a user to spend hours working through a manual flow.
Lam, an Oracle team member cited in the account, describes one user who received a response almost immediately after submitting a request. When she compared the result with the previous manual process, Oracle says the numbers matched exactly. The example illustrates the company’s emphasis on connecting AI to internal data and business rules rather than relying only on general-purpose answers.
Faster incident response for engineers
In production engineering, Oracle site reliability engineers use Codex to gather the relevant context around an incident and automatically bring up the appropriate playbook. The approach is designed to reduce the time engineers spend searching for information and leave more of their attention for decisions about how to resolve the issue.
“A typical simple incident that used to take an hour to resolve can now be handled in minutes,” Lam says. Oracle’s description does not suggest that the system resolves incidents independently. Instead, Codex supports engineers by organizing context and surfacing the procedures they need.
That distinction is central to Oracle’s account of the deployments. Although AI takes on more of the preparatory work, people remain responsible for ensuring that the underlying systems are designed correctly and that the resulting output is fit for use.
Guardrails and code ownership remain essential
Oracle’s technical leaders say faster development does not remove the need for careful system design. Lam says teams must remain responsible for architecture, security and the way Codex is instructed to structure code. The company also stresses that employees need to work alongside the system rather than accept generated code without oversight.
“If you don’t work alongside Codex, you’re going to get into a situation of having lots of code that is not going to be maintainable,” Lam says. The warning positions AI-assisted development as a shared engineering process, with humans accountable for quality and long-term maintenance.
Barry Shilmover, Oracle’s vice president and technical advisor to the CIO, says prototypes have become more useful than written specifications for expressing an idea. Instead of putting an idea on paper first, he says, he puts it into a prototype. That approach allows teams to explore a possible solution while shaping the requirements through direct use.
A new default for solving problems
Oracle says the combination of ChatGPT Work and Codex is changing how employees approach recruiting, analytics and engineering. Rather than starting with the specialist or report needed to answer a question, teams can start by describing the result they want and use AI to help assemble the workflow.
Shilmover says he does not know what his next problem to solve will be, but expects Codex to be one of the first resources he uses. For Oracle, that reflects a broader operating model in which AI becomes an initial step for a wide range of work, while employees continue to provide the judgment, guardrails and accountability required to make the results reliable.
Sources
- OpenAI NewsHow Oracle turns days of work into minutes with ChatGPT and Codex
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