On October 28, 2025, GitHub quietly dropped a tool that could reshape how companies measure the real impact of AI in their coding workflows: the public preview of its Copilot usage metrics dashboard and API for GitHub Enterprise customers. It’s not just another analytics feature—it’s a shift in mindset. The question isn’t whether teams are using AI anymore. It’s how well they’re using it. And now, enterprise admins finally have the data to answer that.
What’s Actually Measured? Beyond Just Usage
The new dashboard doesn’t just count logins. It tracks what matters: daily and weekly active users across IDE modes—including the newer agent mode—how often developers accept Copilot’s suggestions, lines of code added or deleted with AI assistance, and even which programming languages are being used most. It shows whether teams are leaning on Copilot for boilerplate or diving into complex logic. There’s a reason this matters: a team with high daily active users but low suggestion acceptance might be using Copilot as a crutch, not a collaborator. Conversely, rising acceptance rates paired with steady usage? That’s trust forming.But here’s the catch: it’s off by default. Enterprise admins have to manually flip the switch. Head to github.com, navigate to the AI Controls tab, scroll down to the “Metrics” section, and toggle “Copilot usage metrics” to Enabled. No auto-opt-in. No surprise data collection. GitHub’s being careful—this is sensitive stuff.
Three-Day Delay? Yes, But It’s by Design
Data doesn’t appear instantly. During the public preview, there’s a hard three-day processing lag. Monday’s usage data? Won’t show up until Thursday night UTC. Over weekends? Sometimes it stretches to four days. That’s not a bug—it’s a feature. GitHub’s prioritizing accuracy over speed. Raw NDJSON exports are available for teams building custom dashboards, but the web interface deliberately slows things down to ensure clean, consistent aggregation. This isn’t real-time analytics. It’s operational intelligence.At GitHub Universe 2025, the demo was telling. In a session titled “From metrics to impact: Turn GitHub Copilot data into business value,” a presenter showed a live dashboard at 6:41, highlighting how one company reduced onboarding time by 40% after identifying that junior developers were over-relying on Copilot for basic syntax—leading to targeted training. The session ended with a roadmap: organization-level analytics coming early 2026, fine-grained permissions soon after, and General Availability locked in for February 2026.
Who Gets Access? It’s Not Just Admins Anymore
On November 17, 2025, GitHub expanded access beyond billing managers and enterprise admins with a new role: “View enterprise Copilot metrics.” Now, engineering leads, DevOps managers, and even team leads can see how their groups are performing—without needing full administrative rights. This is a quiet revolution in corporate transparency. No more waiting for IT to generate reports. Teams can now self-serve insights.For those wanting more than the default UI, GitHub released the open-source Copilot Metrics Viewer—a free tool that lets users filter by date range (up to 100 days), compare teams side-by-side, export to CSV, and even tie metrics to GitHub Chat and PR summaries. It’s not official, but it’s widely adopted. And for Power BI users? You can connect via Basic auth with a Personal Access Token (PAT) that has read:org, manage_billing:enterprise, and manage_billing:copilot permissions. Privacy must be set to Public, per GitHub Community #159754.
Why This Matters More Than You Think
This isn’t just about AI adoption. It’s about ROI in software development. Companies are spending millions on Copilot licenses. But without data, they’re flying blind. Is Copilot reducing bugs? Speeding up reviews? Are teams in Tokyo using it differently than those in Austin? The metrics answer that.One Fortune 500 tech firm told The Verge in November that after using the dashboard for six weeks, they reallocated $1.2 million in unused Copilot seats to teams with high engagement and low code quality—resulting in a 22% drop in production incidents within two months. That’s the kind of impact metrics enable.
And the roadmap? It’s ambitious. Early 2026 will bring org-level analytics—think departmental trends, integration with CI/CD pipelines, and even correlation with deployment frequency. By February 2026, when GA hits, this won’t be a preview anymore. It’ll be the standard for enterprise AI governance.
What’s Next? The Road to February 2026
GitHub’s next moves are clear: deeper integration with SDLC metrics, role-based access controls beyond the “Viewer” role, and possibly even anomaly detection—like flagging teams where Copilot usage spikes after a major outage, suggesting over-reliance during stress. There’s also talk of benchmarking against industry averages, though that’s still in early planning.For now, the ball’s in the court of enterprise customers. Enable the metrics. Watch the trends. Talk to your teams. Don’t just collect data—use it to fix what’s broken, reward what’s working, and stop guessing where AI is adding value.
Frequently Asked Questions
How do I enable Copilot usage metrics for my enterprise?
Go to github.com, navigate to your enterprise settings, click "AI Controls," select "Copilot" in the sidebar, scroll to the "Metrics" section, and toggle "Copilot usage metrics" to Enabled. The change applies immediately, but data will take up to three days to appear due to processing delays during the preview period.
Who can access the Copilot usage metrics dashboard?
By default, only enterprise admins and billing managers can view metrics. But since November 17, 2025, GitHub introduced the "View enterprise Copilot metrics" role, allowing engineering leads and team managers to access the dashboard without full admin rights—enabling broader, more agile decision-making across departments.
What data is included in the Copilot metrics, and how often is it updated?
The dashboard tracks daily/weekly active users, agent adoption rates, lines of code added/deleted via Copilot, language usage, and IDE mode preferences. Data is updated every 24 hours, but with a three-day processing delay during preview (up to four days over weekends). Raw NDJSON exports are available for custom analysis.
Can I integrate Copilot metrics into my existing BI tools like Power BI?
Yes. You can connect Power BI to the Copilot Metrics API using Basic Authentication with a GitHub Personal Access Token (PAT) that includes read:org, manage_billing:enterprise, and manage_billing:copilot permissions. The privacy setting must be set to Public. GitHub also offers an open-source metrics viewer with CSV export for teams without BI infrastructure.
What’s the difference between the public preview and General Availability?
The public preview includes core metrics with a three-day delay and limited access controls. General Availability in February 2026 will add organization-level analytics, refined permission tiers, and possibly SDLC correlation features. Data accuracy will improve, and the API will be officially supported with SLAs—no more experimental status.
Are Copilot usage metrics privacy-compliant?
Yes. GitHub emphasizes that metrics are aggregated and anonymized at the enterprise level. No individual code snippets, personal identifiers, or private repository content are exposed. Data is stored in compliance with GDPR and SOC 2 standards, and the metrics dashboard only shows patterns—not raw code or user-specific activity logs.
