Janice Rimmer explains how GitHub Copilot enabled rapid automation of accessibility governance workflows at GitHub, highlighting the impact on program management and cross-functional accountability.

How GitHub Copilot Automated Accessibility Governance at GitHub

Janice Rimmer shares how GitHub Copilot empowered GitHub’s engineering team to transform their accessibility compliance process through automation and rapid prototyping. The new workflow automates accountability, reduces manual overhead, and provides real-time visibility for stakeholders.

Background

GitHub’s accessibility governance program tracks the accessibility grades of its services (A-F scale), requiring at least a ‘C’ for compliance. Grades are updated weekly, and all updates are visible on a central dashboard. However, the previous system lacked mechanisms to prompt and track remediation when services fell below the compliance threshold, delaying the resolution of accessibility issues and making it difficult for leadership to manage compliance risk.

The Challenge

Delayed Action: Service owners postponed remediation work, potentially impacting users with disabilities.
Visibility Gaps: Leadership could not effectively quantify and manage compliance risk without clear action plans or timelines.

Solution: Copilot-Powered Automation

GitHub Copilot was used to rapidly develop a workflow that:

Automates GitHub Issue creation for accessibility compliance failures using GitHub Actions.
Provides remediation guidance directly in automatically generated issues.
Syncs issues with a GitHub Projects board for global visibility by program managers and leadership.
Automates stakeholder mention and assignee management to maintain transparency.
Auto-closes issues when services return to compliance.

Development Approach

Instead of following a traditional backlog-driven development process, the team:

Used plain-language rules to prompt Copilot for code scaffolding and incremental adjustments.
Created and tested synthetic data fixtures to simulate real-world scenarios.
Established guardrails (idempotent logic, dampening, defensive handling).
Used rapid feedback loops to refine automation and eliminate the need for manual triage.

This approach let a program manager prototype directly with Copilot, reducing dependency on engineering resources and achieving production-ready results in just a few hours.

Rollout and Results

Prototyping started in staging with test repositories and synthetic data.
Workflow was refactored for security (migration to GitHub App) and rolled out to all tracked services.
The automated system now ensures remediation issues are promptly surfaced and tracked, reducing manual tracking and freeing staff for higher-value work.
Program leadership gained direct access to compliance status through automated synchronization of issues and project boards.

Impact

Faster Remediation: Service owners address compliance failures immediately.
Increased Accountability: Clear issue ownership and cross-linking enable greater transparency.
Reduced Manual Work: Automation shrinks clerical and triage overhead.
Replicable Pattern: The process serves as a template for future governance automation.
Empowered Teams: Domain experts can now develop and deploy workflow automation with minimal engineering support.

Thanks to Copilot, compliance tooling that once required lengthy engineering cycles was prototyped and delivered in hours. The process demonstrates the power of AI-enabled development to accelerate cross-functional progress in accessibility and governance.

Learn more: Automating your projects using GitHub Actions

This post appeared first on “The GitHub Blog”. Read the entire article here