Last updated: June 2026
GitKraken Insights gives engineering leaders a single view of how AI tools, code delivery, and team capacity work together. The AI Adoption section measures how much your team is actually using AI, how autonomously, and what AI is actually delivering — in time and dollars.
Plan: GitKraken Insights
Platform: Browser only via gitkraken.dev
Role: Lead, Admin, or Owner
Prerequisite: Connected GitHub and at least one AI provider (Claude Code, Codex, or Cursor). See Connect Your Data.
AI Adoption pages in this section
| Page | What it covers |
|---|---|
| Connect Your Data — Setting Up AI Adoption | The hands-on setup guide: gather access, connect GitHub and your AI tools, map developer identities, and invite your team. |
| Getting Started with AI Adoption | A short tour organized by what you do, with quickstarts for executives, engineering leaders, team leads, and admins. |
| Adoption & Agentic Metrics | How much your team is actually using AI, and how autonomously: Agent Adoption Score, Agent Autonomy Score, AI Tier, Maturity Factor, and Cursor Boost. |
| Output & Throughput Metrics | What your team ships: Output Score, Throughput, Direct Commits, and Effort Score (Complexity). |
| Flow & Cycle Time Metrics | How fast work moves through your system: Cycle Time, Review Cycles, First-Pass Rate, and WIP. |
| DORA & Quality Metrics | The four DORA metrics: Deployment Frequency, Lead Time for Changes, Change Failure Rate (CFR), and Mean Time to Recovery (MTTR). |
| AI Impact & Cost Metrics | What AI is actually delivering, in time and dollars: Productivity Uplift, AI-Assisted Percentage, CapEx / OpEx Split, and Spend by Tier. |
| AI Adoption Playbooks | Action-first guides: set tier weights, roll out AI tooling, investigate a slow cycle time, and interpret a high CFR week. |
| AI Adoption Settings | Configuration reference — what each setting changes, and which metrics depend on it. |
Where AI Adoption shows up in the product
- /ai-adoption/developers — primary surface. Each row has Adoption, Agentic, Tier, and a heatmap.
- /ai-adoption/teams — team averages and tier mix bars.
- /ai-adoption/ai-tools-comparison — cohort comparisons (e.g. team A vs. team B, or Claude vs. Codex users).
- /ai-adoption/executive — hero KPI (“AI Adoption %”) and trend lines.
- /ai-adoption/ai-impact — autonomy deep dive and Business Impact / ROI.
- /ai-adoption/capex — CapEx / OpEx split as the primary surface.
- Adjacent surfaces in the same nav family: /ai-adoption/board-metrics, /ai-adoption/data-connections, /ai-adoption/data-explorer, /ai-adoption/settings/*.
Related pages
- Getting Started with GitKraken Insights — request access, connect repositories, and connect an AI provider.
- AI Impact Metrics — code quality and acceptance-rate metrics from connected AI providers (Duplicated Code, Prompt Acceptance Rate, and more).
