AI adoption and usage
The AI adoption and usage segment lets you track AI adoption and engagement in your organization over a period of time by providing insight into how many users in your organization are actively using AI. You can also track the consumption of AI Credits and have an overview of users who have reached their monthly limits. This can help you analyze the extent of AI adoption and identify where further action may be needed.
The following adoption and usage metrics are available:
Each metric is presented as a bar chart. The chart can be filtered by the following criteria:
Select one of the predefined time filters that show the last specified period or select a custom date range.
Show only usage data originating from the selected IDEs.
Search for and select users or groups to filter the data. Selecting a group includes all of its members, including members of its subgroups. Expand the group to select which subgroups to include or exclude.
Sources of adoption and usage data
The data in this analytics segment comes from a specific set of products, tools, and AI agents. For details about what the metrics do and don't include, see the following sections.
Data included in the metrics
The data shown in this analytics segment is mostly based on AI Credit consumption for the use of agents and models through the following products and tools:
AI Assistant in JetBrains IDEs, either when using a supported agent or in Chat mode.
JetBrains Central CLI, when using a supported agent wired through the CLI.
JetBrains Air, when using a supported agent in the desktop or web version of JetBrains Air.
The following AI agents are currently supported for data collection:
Junie, an AI coding agent developed by JetBrains. Data is also collected when Junie is used through its dedicated tool window.
Claude Agent, a third-party coding agent by Anthropic.
Pi, a minimal, open-source agent harness.
GitHub Copilot, a third-party coding agent by GitHub.
The charts may also show data labeled as Uncategorized, which includes consumption of AI Credits by new or less common tools that don't have a dedicated categorization.
Data excluded from the metrics
The metrics in this analytics segment exclude the following usage of products and tools as they don't consume AI Credits:
Using in-editor features such as Next edit suggestions and Code completion.
Using models from third-party AI providers configured locally in AI Assistant. When you provide your own API key from a supported AI provider directly in AI Assistant, the usage is also charged directly by the third-party provider and doesn't consume AI Credits.
Using agents in AI Assistant with provider accounts or provider-specific authentication methods.
Active AI users
The Active AI users bar chart shows how many users in your organization are actively using AI. This lets you identify the current level of AI adoption in your organization, as well as adoption trends over time.
The following sub-metric is included:
Active AI users: The total number of unique users who made at least one request to JetBrains AI that spent AI Credits.
Depending on the period selected in the time-based filtering, the chart shows data per day, month, or year. Each user is counted only once per bar on the chart. For example, if a user makes a request on January 15 and another one on January 26, they are counted only once in the bar for January if the chart shows data per month.
AI Credits consumption
The AI Credits consumption chart shows the number of AI Credits spent by users. The consumption information includes both the quota included with an AI license and top-up AI Credits. For more information, see License with AI.
The AI Credits consumption chart shows the following sub-metrics:
Built-in quota: The number of AI Credits from the built-in quota that the users in your organization spent. For more information, see AI quota.
Top-up AI Credits: The number of AI Credits purchased in addition to the included quota that the users in your organization spent. For more information, see Top-up AI Credits.
Based on the two sub-metrics, you also get the Total AI Credits spent information, which is the total number of all spent AI Credits. This sub-metric is the sum of spent Built-in quota and Top-up AI Credits.
Number of users who hit their AI Credits limit
This chart shows the number of unique users who used up all of their AI Credits. These insights let you identify usage patterns and potential needs to adjust user licenses or amounts of top-up AI Credits.
Depending on whether a user has an allocation of top-up AI Credits, they are added to the count of users who hit their limit in the following ways:
If the user has top-up AI Credits in addition to the built-in quota, they are added to the count once they have spent their top-up AI Credits (in addition to already spending their built-in quota).
If the user doesn't have any top-up AI Credits, they are added to the count when they spend their entire built-in quota.
The chart includes the following sub-metric:
Total number of unique users who hit their limit: The total number of unique users who hit their limit during the selected period.
For a list of individual users who hit their limit, see the Users who hit their AI Credits limit table.
In the following specific cases, users are added to the count even though they still have available AI Credits:
If the user spends their initial allocation of built-in quota and top-up AI Credits and then receives additional top-up AI Credits, they are added to the count when they spend the initial top-up AI Credits.
If the user has multiple licenses, once they have spent the entire built-in quota and top-up AI Credits in one license, they are added to the count. They can then switch to a different license and use the available AI Credits from that license.
Users who hit their AI Credits limit
This table lists all users who reached their AI Credits limit during the selected period. The table includes the user's name, email, and the date when they hit the limit. As a single user can hit their quota limit multiple times in a single time period, there may be multiple entries for the same user in the table. However, since limit hits are aggregated on a daily level, if a user hits more than one limit during the same day, a single entry is added to the table.
