By name: ai-adoption-dashboard-builder displayName: AI Adoption Dashboard Builder tagline: Generate a dashboard tracking AI tool usage, active users, top workflows, and productivity metrics. description: | Creates a multi-tab analytics dashboard for tracking AI tool adoption across your engineering organization. Includes executive KPIs, team-level adoption curves, per-tool usage breakdowns, productivity impact comparisons, and cost tracking. Optionally generates a Grafana dashboard JSON for real-time monitoring. department:
- Engineering
- AI Enablement Leaders
- Data & Analytics use_cases:
- Documentation
- Cost Optimization
- Workflow Automation tools_required:
- Google Sheets MCP
- Grafana MCP agents_compatible:
- Claude / Claude Code
- Cursor
- Windsurf
- ChatGPT
- GitHub Copilot
- Any MCP-compatible agent author: Webrix verified: true updatedAt: 2026-02-24 version: 1.0.0 exampleInput: | Organization: 150 engineers across 8 teams AI tools in use: GitHub Copilot, Cursor, Claude Metrics to track: Adoption rate, usage frequency, productivity impact, cost Data sources: GitHub API, SSO logs, billing invoices exampleOutput: | AI Adoption Dashboard — February 2026
EXECUTIVE SUMMARY Active Users: 112/150 (75%) ↑ 8% from last month Monthly Cost: $6,200 Budget: 78% utilized Time Saved: 1,840 hrs ≈ $159,160 value Top Tool: GitHub Copilot (98 active users)
ADOPTION BY TEAM Platform: 92% | Frontend: 81% | Backend: 78% | Data: 65% Mobile: 62% | DevOps: 58% | QA: 45% | Security: 38%
TOP WORKFLOWS
- Code completion (Copilot) — 12,400 acceptances/week
- Code review assist (Claude) — 340 reviews/week
- Test generation (Cursor) — 180 test files/week
Generated: Google Sheet (6 tabs) with charts and sparklines Generated: Grafana dashboard JSON (4 rows, 12 panels)
AI Adoption Dashboard Builder
Generate a dashboard tracking AI tool usage, active users, top workflows, and productivity metrics.
Integrations: Google Sheets, Grafana
When to Use
- The user wants to track AI tool adoption across their organization
- Leadership needs a dashboard for AI usage visibility
- The user mentions "adoption dashboard", "AI metrics", or "usage tracking"
- Teams want to measure which AI tools and workflows have the most impact
Steps
Step 1: Define Metrics to Track
Help the user select from these metric categories:
| Category | Metrics |
|---|---|
| Adoption | Total users, active users (daily/weekly/monthly), adoption rate by team, new activations per week |
| Usage | Sessions per user, prompts per day, tokens consumed, tool-specific usage (Copilot completions, Claude conversations) |
| Workflows | Top workflows by usage, time saved per workflow, most popular skills installed |
| Productivity | PRs merged per developer, cycle time change, bug fix time change, code review turnaround |
| Cost | Cost per user, cost per team, cost trend, budget utilization percentage |
Step 2: Identify Data Sources
Map metrics to data sources:
| Data Source | Metrics Available |
|---|---|
| GitHub/GitLab API | PRs, commits, review time, Copilot usage stats |
| AI tool admin dashboards | Seat usage, active users, token consumption |
| Jira/Linear | Ticket cycle time, story points velocity |
| SSO/IdP logs | Login frequency, tool access patterns |
| Billing data | Cost per tool, cost trends |
Step 3: Build Google Sheets Dashboard
Create a spreadsheet with:
- Sheet 1: Executive Summary — High-level KPIs with sparkline charts (adoption rate, ROI, active users)
- Sheet 2: Adoption Trends — Weekly/monthly adoption curves by team and tool
- Sheet 3: Usage Details — Per-tool usage breakdown, top users, least-used tools
- Sheet 4: Productivity Impact — Before/after comparisons of engineering metrics
- Sheet 5: Cost Tracking — Budget vs actual, per-tool cost, cost per developer
- Sheet 6: Raw Data — Data import template with sample data format
Step 4: Build Grafana Dashboard (Optional)
If the user has Grafana, provide dashboard JSON with:
- Row 1: Overview — Stat panels for total users, active today, weekly growth rate
- Row 2: Adoption — Time series of adoption by team, bar chart of tool popularity
- Row 3: Productivity — Before/after gauge panels, cycle time trend
- Row 4: Cost — Budget burn-down, cost per developer trend
Provide the Grafana dashboard JSON configuration and data source setup instructions.
Step 5: Set Up Data Collection
Recommend a lightweight data collection approach:
- Weekly manual update — For small teams, a simple form that team leads fill out
- API integration — Scripts to pull from GitHub API, AI tool APIs
- Survey-based — Monthly developer survey for qualitative metrics
Provide a sample data collection script or form template based on the user's preference.
Output
Deliver:
- A ready-to-use Google Sheets dashboard with sample data
- Grafana dashboard JSON (if requested)
- Data collection templates or scripts
- A guide for updating the dashboard weekly/monthly