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

Over a hundred thousand employees across Oracle are using ChatGPT Work and Codex, from talent acquisition to Oracle Applications Lab to the IT organization. In each case, work that used to rely on specialists and take days can now be done by anyone and is complete in minutes. Recruiters skip days of market research, business users describe an outcome instead of hunting for a report, and technical leads build tools that used to take a full team months.

“We’ve built our talent market intelligence tool using ChatGPT Work, and it’s really revolutionized how we do the front end of our recruitment process.”

—Jan Ackerman, Senior Vice President and Global Head of Talent Acquisition, Oracle

Making recruiting research more efficient

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 2–4 days to compile.

“We’ve gone from zero to a hundred,” says Jan Ackerman, Senior Vice President and Global Head of Talent Acquisition at Oracle. “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.”

Not only is the process faster, but it’s 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.

Business users get the answers they need faster

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.

—Richard Lam, Group Vice President, Oracle Applications Lab