How to connect AI usage to business value

OpenAI has added analytics tools in the ChatGPT Admin Console to help administrators track how teams use ChatGPT Work and Codex, linking usage and spending to measurable results. The platform combines data on active users, credits, and task completion to show where AI adoption is growing or lagging, enabling targeted support and cost reviews. Admins can filter usage by group or user to identify low-adoption areas and assess training or workflow adjustments needed to improve engagement.

The Insights overview breaks down credit distribution across tasks such as account research and planning, highlighting where teams spend the most. A Use Cases table further details credits, messages, and active users per task, while task details reveal how models, reasoning, and speed settings contribute to credit usage. This granular data helps administrators evaluate whether current setups align with task requirements and where training on model selection may be beneficial.

The Outcomes view tracks Codex’s contributions to merged commits and lines of code, alongside code-review activity, allowing engineering leaders to assess whether AI is improving software delivery efficiency. Trends and filters for groups or repositories help identify adoption patterns and guide decisions on expanding access or providing additional support where needed.

The Admin plugin and Admin API enable administrators to generate reports comparing adoption, spending, and task performance, which can be shared with stakeholders or integrated into existing dashboards. These tools automate data compilation and produce actionable insights, such as linking credit usage to ticket resolution times or other business metrics, to help teams evaluate the financial and operational value of AI investments.