OpenAI publishes ROI guide for ChatGPT admins
OpenAI has published a how-to for enterprise administrators on using ChatGPT Admin Console analytics to tie AI usage to business outcomes, illustrated with a hypothetical sales scenario returning 245% in year one.
The guide walks through analytics that span ChatGPT Work and Codex. The Usage view aggregates active users, credits and token usage, filterable by group or user to surface pockets of low adoption. A task classifier in Insights samples messages and sorts them into use cases and tasks — software engineering into feature development and code maintenance, sales & revenue into account research and planning — surfaced through Overview and Use cases tabs. Task details break out Models, Reasoning and Speed as a share of credits per task, which OpenAI frames as a prompt to test cheaper or faster configurations on routine work. A Plugin leaderboard and Skills view show which tools support a task.
For engineering leaders, an Outcomes view reports Codex contributions to merged commits and lines of code alongside code-review activity, with group, user and repository filters. An Admin plugin in ChatGPT Work can assemble findings into a leadership deck; the Admin API supports piping analytics into internal dashboards next to business-system data such as ticket resolution time.
The ROI example is explicitly illustrative: 20 sellers saving three hours on each of two account briefs a week over 46 weeks yields 5,520 hours, half of it valued at a fully loaded $75 per hour, against $60,000 in first-year AI, setup and support costs.
OpenAI does not provide verified customer ROI figures, pricing, or availability details in the guide.