GitHub Copilot adoption
GitHub Copilot Adoption and Enablement
Help your developers use AI assistance well, safely and consistently.
GitHub Copilot brings AI code suggestions, chat and agents into the editor, the command line and GitHub itself. We help engineering teams roll it out with clear policies, sensible repository setup and working habits that keep quality and security high.
What we cover
- Organisation policies and settings
- Repository custom instructions
- IDE, chat and agent mode setup
- Coding agent and code review workflows
- Security and content exclusions
- Usage and outcome measurement
Requirement-led advice · Documented handover
- Advice based on your requirements
- Works with your existing stack
- Documented, maintainable delivery
What Is GitHub Copilot?
GitHub Copilot is GitHub's AI coding assistant. It offers inline code completion, Copilot Chat and agent mode in editors such as Visual Studio Code, Visual Studio and JetBrains IDEs, and a coding agent that can work on an assigned issue and open a pull request for review. Copilot can also review pull requests and answer questions about a repository on GitHub.
For companies, Copilot Business and Copilot Enterprise add central licence management, policy controls, content exclusions and usage reporting. Repository-level custom instructions tell Copilot about your conventions, so suggestions fit your codebase rather than generic examples.
When GitHub Copilot is a good fit
- Your code is hosted on GitHub, or your developers work in VS Code, Visual Studio or JetBrains IDEs.
- You want one assistant managed centrally with organisation policies.
- You use GitHub issues and pull requests and want an agent to work inside that flow.
- You want adoption measured, not just licences handed out.
Where Teams Use GitHub Copilot
The tasks where AI assistance tends to help most. Developers still review and own every change.
Everyday coding
Boilerplate, tests, small functions and refactors in the editor.
Test writing
Generate unit tests for existing code, then review edge cases.
Understanding code
Explain unfamiliar modules and legacy code in chat.
Issue to pull request
Assign well-defined issues to the coding agent and review its pull request.
Code review assistance
A first review pass before a human reviewer.
Upgrades and migrations
Help with framework upgrades, such as older .NET versions.
Documentation
Draft README files, comments and API documentation.
Scripts and infrastructure
Pipeline YAML, scripts and infrastructure-as-code templates.
GitHub Copilot Services We Deliver
Each piece of work has a clear output, so you know what you will receive.
Readiness assessment
Review repositories, tools, policies and risks before rollout.
Deliverables: readiness report, rollout plan
Organisation setup
Licences, policies, model access, content exclusions and audit settings.
Deliverables: configured organisation, policy record
Repository setup
Custom instructions and conventions so suggestions match your code.
Deliverables: instruction files, prompt library
Developer enablement
Hands-on workshops based on your own codebase.
Deliverables: workshops, usage guidelines
Agent workflows
Issue templates and review rules for the coding agent.
Deliverables: issue templates, branch protections, review checklist
Measurement
Track adoption and delivery outcomes over time.
Deliverables: metrics dashboard, quarterly review
GitHub Copilot Features We Configure
Available features depend on your plan and the policies you enable.
In the editor
- Code completion
- Copilot Chat
- Agent mode
- Next edit suggestions
On GitHub
- Copilot coding agent
- Pull request reviews
- Chat on github.com
- Copilot in the CLI
Customisation
- Repository custom instructions
- Prompt files
- Model selection
- Model Context Protocol servers
Administration
- Organisation and enterprise policies
- Content exclusions
- Audit logs
- Usage metrics
Listing a feature here does not mean every project uses it. We recommend what fits your requirements, skills, licensing and running costs.
How GitHub Copilot Fits Your Stack
Copilot works across languages, and we see strong results in .NET and ASP.NET Core, Python and TypeScript codebases. Teams on Azure DevOps can still use Copilot in their editors; the coding agent and pull request features need repositories on GitHub.
Many teams use more than one assistant. We can help you compare Copilot with Claude Code, OpenAI Codex and Cursor, and set shared rules for code review and security whichever tool a developer uses.
Implementation Considerations
- Set policies before giving out licences, including public code matching and which models are allowed.
- Exclude secrets and sensitive files, and keep secret scanning switched on.
- Keep code review mandatory; AI-written code needs the same scrutiny as any other.
- Give the coding agent small, well-described issues with clear acceptance criteria.
- Measure outcomes such as cycle time and review effort, not just acceptance rates.
- Train developers on what to ask, and on when not to use the assistant.
How We Work With GitHub Copilot
The same four steps we use across our technology work, adapted to your scope.
Discover
Goals, users, constraints and the systems GitHub Copilot must work with.
Select
Confirm GitHub Copilot is the right fit and agree the architecture and scope.
Build and integrate
Deliver in short iterations with testing, reviews and documentation.
Operate and improve
Monitor, support and improve the solution as your needs change.
GitHub Copilot Questions, Answered
What is GitHub Copilot?
An AI coding assistant from GitHub that offers code completion, chat, agent mode and a coding agent across editors, the command line and GitHub.
Which plan does a company need?
Copilot Business suits most organisations; Copilot Enterprise adds features for larger GitHub Enterprise customers. We compare current plans against your needs.
Is our code used to train the models?
GitHub states that code from Copilot Business and Enterprise is not used for model training. We review the current terms and settings with you.
Can Copilot work with Azure DevOps repositories?
Editor features work with any repository. The coding agent and pull request reviews need repositories on GitHub.
How do we keep quality high?
Mandatory code review, tests in CI, repository instructions and clear guidance for developers on when to rely on suggestions.
How long does a rollout take?
A pilot with one or two teams usually comes first, then a wider rollout once policies and guidelines are proven.
Rolling Out GitHub Copilot?
Tell us about your teams, repositories and goals, and we will suggest a pilot that proves value safely.
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