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---
stage: Plan
group: Optimize
info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://handbook.gitlab.com/handbook/product/ux/technical-writing/#assignments
---
# AI Impact analytics
DETAILS:
**Tier:** Ultimate with GitLab Duo Enterprise - [Start a trial](https://about.gitlab.com/solutions/gitlab-duo-pro/sales/?type=free-trial)
**Offering:** GitLab.com, Self-managed
> - [Introduced](https://gitlab.com/gitlab-org/gitlab/-/issues/443696) in GitLab 16.11 [with a flag](../../administration/feature_flags.md) named `ai_impact_analytics_dashboard`. Disabled by default.
> - [Generally available](https://gitlab.com/gitlab-org/gitlab/-/issues/451873) in GitLab 17.2. Feature flag `ai_impact_analytics_dashboard` removed.
> - Changed to require GitLab Duo add-on in GitLab 17.6 and later.
AI Impact analytics displays software development lifecycle (SDLC) metrics for a project or group in the month-to-date and the past six months.
Use AI Impact analytics to:
- Measure the effectiveness and impact of AI on SDLC metrics.
- Visualize which metrics improved as a result of investments in AI.
- Track the progress of AI adoption.
- Compare the performance of teams that are using AI against teams that are not using AI.
For a click-through demo, see the [AI Impact analytics product tour](https://gitlab.navattic.com/ai-impact).
## AI Impact metrics
AI Impact analytics displays key metrics and metric trends for a project or group.
### Key metrics
- **Code Suggestions: Unique users**: Percentage of users that engage with Code Suggestions every month. It is calculated as the number of monthly unique Code Suggestions users divided by total monthly [unique contributors](../../user/profile/contributions_calendar.md#user-contribution-events). Only unique code contributors, meaning users with `pushed` events, are included in the calculation.
- **Code Suggestions: Acceptance rate**: Percentage of code suggestions provided by GitLab Duo that have been accepted by code contributors in the last 30 days.
- **Duo Chat: Unique users**: Percentage of users that engage with Duo Chat every month. It is calculated as the number of monthly unique Duo Chat users divided by the total GitLab Duo assigned users.
### Metric trends
The **Metric trends** table displays metrics for the last six months, with monthly values, percentage changes in the past six months, and trend sparklines.
#### Lifecycle metrics
- [**Cycle time**](../group/value_stream_analytics/index.md#lifecycle-metrics)
- [**Lead time**](../group/value_stream_analytics/index.md#lifecycle-metrics)
- [**Deployment frequency**](dora_metrics.md#deployment-frequency)
- [**Change failure rate**](dora_metrics.md#change-failure-rate)
- [**Critical vulnerabilities over time**](../application_security/vulnerability_report/index.md)
#### AI usage metrics
- **Code Suggestions usage**: Monthly user engagement with AI Code Suggestions.
- The month-over-month comparison of the AI Usage unique users rate gives a more accurate indication of this metric, as it eliminates factors such as developer experience level and project type or complexity.
- The baseline for the AI Usage trend is the total number of code contributors, not just users with GitLab Duo seats. This baseline gives a more accurate representation of AI usage by team members. To learn more about AI Impact analytics, see the blog post [Developing GitLab Duo: AI Impact analytics dashboard measures the ROI of AI](https://about.gitlab.com/blog/2024/05/15/developing-gitlab-duo-ai-impact-analytics-dashboard-measures-the-roi-of-ai/).
- To analyze the performance of teams that use AI versus teams that don't, you can create a custom [Value Streams Dashboard Scheduled Report](https://gitlab.com/explore/catalog/components/vsd-reports-generator) based on the AI Impact view of projects and groups with and without GitLab Duo.
NOTE:
Usage rate for Code Suggestions is calculated with data starting from GitLab 16.11.
For more information, see [epic 12978](https://gitlab.com/groups/gitlab-org/-/epics/12978).
## View AI Impact analytics
Prerequisites:
- [Code Suggestions](../../user/project/repository/code_suggestions/index.md) must be enabled.
- [ClickHouse for contribution analytics](../../user/group/contribution_analytics/index.md#contribution-analytics-with-clickhouse) must be configured.
1. On the left sidebar, select **Search or go to** and find your project or group.
1. Select **Analyze > Analytics Dashboards**.
1. Select **AI impact analytics**.
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