Oracle Reports 130,000 ChatGPT Users and 95,000 Codex Users

Oracle says employees use ChatGPT Work and Codex to speed up recruiting research, business reporting and incident response across the company.

OpenAI’s October 8, 2026 customer profile describes Oracle employees using ChatGPT Work and Codex in recruiting, business operations and production engineering. The profile reports 130,000 active ChatGPT users and more than 95,000 active Codex users at Oracle; it does not specify how many employees use both products.

In talent acquisition, Oracle built a tool that uses a job description to research comparable roles, compensation and candidate pools in relevant locations. OpenAI says compiling that research previously took two to four days; Oracle’s senior vice president and global head of talent acquisition, Jan Ackerman, said recruiters now prepare with the tool in about 15 to 20 minutes. OpenAI reports a 98% decrease in the time required for talent acquisition research.

Oracle Applications Lab also uses Codex with an internal map of company data objects, relationships and rules. Employees can ask business questions in plain language, which the system turns into SQL queries and uses to return analyses, reports or applications. Oracle executive Richard Lam said a task that could take a business user hours was answered almost immediately, with results matching the previous manual process.

For incident response, Oracle site reliability engineers use Codex to collect incident context and surface relevant playbooks. Lam said a typical simple incident that once took an hour to resolve can now be handled in minutes. The profile says these workflows are not fully autonomous: employees remain responsible for system design, security and reviewing outputs. Lam also cautioned that teams need to work alongside Codex to keep generated code maintainable.

The examples position Oracle’s deployment as a mix of knowledge retrieval, workflow assistance and software development—not a single company-wide automated system. OpenAI says the tools are used across Oracle’s talent acquisition, applications lab and IT organization, while the company’s staff remain accountable for the systems and results.

Industry Impact

AI embedded in daily enterprise work

Recruiting, business operations and production engineering

Overview

Oracle’s reported adoption shows how AI assistants can support distinct internal workflows at enterprise scale: recruiting research, business analysis and incident response. The reported time reductions—from days to minutes for recruiting research and from about an hour to minutes for simple incidents—suggest potential productivity gains, though the profile does not quantify broader cost savings. For business leaders and technical teams, the deployment also highlights the need for human review, secure system design and maintainable generated code.

Key Impact Points

Recruiters reportedly cut research preparation from two to four days to about 15–20 minutes.

Codex helps business users query company data in plain language and supports faster incident triage.

Employees remain responsible for security, system design and reviewing AI outputs; generated code still needs maintainability oversight.

Opportunities

Workflow-specific enterprise AI

Recruiting, business operations and IT

Oracle’s examples suggest an opportunity for organizations to apply AI assistants to recurring, information-heavy workflows where employees already have defined review responsibilities. Internal tools could connect approved company data and playbooks to recruiting research, plain-language business queries or incident context. The article does not establish a standalone product opportunity or disclose revenue; the supported business case is improved employee efficiency and faster access to information. Any deployment would need to preserve human accountability, protect systems and data, and ensure generated code remains maintainable. Results should be measured by workflow-specific time savings and output quality rather than assumed to generalize across the company.

AI assistance for internal workflows
Problem: Recruiting research, business analysis and incident response can require substantial employee time to gather information and follow established processes.
Solution: Apply AI assistants to company-specific data and playbooks to support research, plain-language queries and incident context retrieval, with employees reviewing outputs.
Target Users: Recruiting teams, business users and site reliability engineers.
Business Value: Oracle’s profile reports faster recruiting research and resolution of typical simple incidents, alongside near-immediate answers to some business questions.
Revenue Potential: No direct revenue opportunity is reported; the demonstrated potential is improved productivity and employee capacity.

Reference link

https://openai.com/index/oracle

Image Source Link

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