The standard for AI-assisted software development
GitHub Copilot has become the most widely adopted AI coding assistant in the enterprise. Backed by Microsoft and GitHub — and trained on the world’s largest body of public code — it integrates deeply with the tools development teams already use.
For companies that want a solid rollout with enterprise support and clear privacy terms, GitHub Copilot Business and Enterprise are usually the safest place to start.
Key features
Inline code suggestions
Copilot’s core feature is context-aware code completion. The model suggests anything from a single line to an entire function, inferring the developer’s intent from existing code and plain-language comments. It stays out of the way: developers accept, edit, or ignore each suggestion without breaking their flow.
Copilot Chat in the IDE
Chat lets developers discuss code right in the editor: explain what a snippet does, suggest refactors, generate unit tests for an existing function, or fix errors using the context of the open code. It’s available in VS Code, JetBrains, Visual Studio, and the terminal.
Copilot in pull requests
GitHub Copilot writes automatic pull request summaries describing what changed, why, and what risks it may carry. That shortens reviews and improves change documentation for teams with a fast release cadence.
Security vulnerability detection
Copilot scans both generated and existing code for known vulnerability patterns: SQL injection, exposed secrets, insecure token handling, and other common weaknesses. It doesn’t replace a security audit, but it acts as an early first line of defense.
Impact data
In a controlled GitHub experiment, developers using Copilot completed a programming task 55% faster (Peng et al.). Real-world impact varies with the type of work: the gains are larger for boilerplate, tests, and documentation than for complex business logic or architecture decisions.
What does hold across comparable rollouts is less time spent looking up syntax, documentation examples, and fixes for standard problems. Developers spend more time thinking about the problem and less time figuring out how to express it in code.
Copilot Business vs. Enterprise
Business is the standard choice for companies: per-user licenses, a privacy policy that keeps customer code out of training, and centralized administration in GitHub.
Enterprise adds the ability to index your company’s private repositories, so Copilot understands your organization’s own conventions and patterns. That makes suggestions far more relevant in complex projects with many internal rules.
Rollout and training with AIRES
Installing Copilot takes minutes. Getting the most out of it takes new habits: writing descriptive comments that guide the model, reviewing generated code with your own judgment, and agreeing on team conventions for when and how to use the tool.
We support development teams through Copilot adoption with training sessions, usage policies, and an impact review four and eight weeks after rollout.
Frequently asked questions
Does GitHub Copilot learn from our company’s private code?
With Copilot Business and Enterprise, customer code isn’t used to train public models. That’s a key difference from the individual plan, and it’s backed by GitHub’s enterprise data processing agreements.
Does it work well with less common languages or internal frameworks?
Performance is excellent in widely used languages (Python, JavaScript, TypeScript, Java, C#). With less represented languages or highly specific frameworks, suggestions are less accurate. Copilot Enterprise improves this by indexing your organization’s own code.
What does rollout look like for a team of ten developers?
The technical side — assigning licenses, setting the organization policy, installing the IDE extension — takes a day. The training and adoption work that drives the return takes two or three hands-on sessions and four to six weeks of follow-up to lock in the new working habits.