{"id":5934,"date":"2026-10-10T01:24:48","date_gmt":"2026-10-10T04:24:48","guid":{"rendered":"https:\/\/tucumandevelopers.com\/index.php\/2026\/10\/10\/how-oracle-turns-days-of-work-into-minutes-with-chatgpt-and-codex\/"},"modified":"2026-10-10T01:24:48","modified_gmt":"2026-10-10T04:24:48","slug":"how-oracle-turns-days-of-work-into-minutes-with-chatgpt-and-codex","status":"publish","type":"post","link":"https:\/\/tucumandevelopers.com\/index.php\/2026\/10\/10\/how-oracle-turns-days-of-work-into-minutes-with-chatgpt-and-codex\/","title":{"rendered":"How Oracle turns days of work into minutes with ChatGPT and Codex"},"content":{"rendered":"
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Making recruiting research more efficient<\/span><\/h2>\n<\/p>\n<\/div>\n

The talent acquisition team used ChatGPT Work to build a talent market intelligence tool that takes a job description, researches comparable roles, benchmarks compensation, and assesses the talent pool across relevant locations. The tool arms the recruiter with valuable information that they need going into a conversation with the hiring manager, information that previously took 2\u20134 days to compile.<\/span><\/p>\n

\u201cWe\u2019ve gone from zero to a hundred,\u201d says Jan Ackerman, Senior Vice President and Global Head of Talent Acquisition at Oracle. \u201cNow we\u2019re able to sit down and prep for about 15 to 20 minutes using the tool that we\u2019ve built using [ChatGPT] Work.\u201d<\/span><\/p>\n

Not only is the process faster, but it\u2019s also more consistent. Recruiters used to run the intake process differently from one search to the next, but with the talent market intelligence tool, the process is consistent, so every hiring manager has the same quality of data and insights, no matter which recruiter they worked with.<\/span><\/p>\n

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Business users get the answers they need faster<\/span><\/h2>\n<\/p>\n<\/div>\n

The Oracle Applications Lab team, which helps run many of Oracle\u2019s core business processes, built an ontology of the company\u2019s objects, relationships, and rules, so a plain-language business question can be turned into a reliable SQL query with Codex. A business user describes the outcome they want, and Codex decides which internal systems to call, gathers the information, and returns an analysis, a report, or an application.<\/span><\/p>\n

That\u2019s a change from how work used to get done. Lam said one user came to him after asking a question that would normally have taken her a couple of hours to answer. She told Lam, \u201cWith the new tool, I put in the request and got a response almost immediately.\u201d When she checked the result against the old manual process, the numbers matched exactly.<\/span><\/p>\n

In production engineering, site reliability engineers use Codex to gather relevant context about an incident and automatically pull up the right playbook. SREs spend more time guiding decisions and less time hunting for information. \u201cA typical simple incident that used to take an hour to resolve can now be handled in minutes,\u201d says Lam.<\/span><\/p>\n

Even as Codex takes on more of the work, Lam is careful to note that none of this runs on autopilot. Someone still has to make sure the underlying system is built right.<\/span><\/p>\n

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\u201cBusiness users now describe the outcome they want instead of hunting for a report. That is a major shift. I would even call it a business transformation.\u201d<\/p><\/blockquote>\n

\u2014Richard Lam, Group Vice President, Oracle Applications Lab<\/p>\n<\/div>\n

While AI builds the tools, the people are still responsible for the output. A few lessons stand out:<\/span><\/p>\n

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