Published via [GitHub Executive Insights](https://github.com/solutions/executive-insights "Executive insights, curated just for you")

GitHub Copilot is an enterprise-grade productivity tool, [enabling teams code up to 55% faster](https://resources.github.com/learn/pathways/copilot/essentials/measuring-the-impact-of-github-copilot/). Developers using Copilot find that it helps them ship more efficiently, reduce time spent producing boilerplate code, and stay in the flow longer. But here’s the catch: Simply purchasing Copilot does not **immediately** unlock its value.

To realize Copilot’s full potential, leaders need to roll out Copilot strategically, thinking holistically about access, governance, enablement, and adoption. The effort is worth it. Done well, Copilot adoption at scale accelerates delivery, improves developer satisfaction, and creates lasting ROI for your business.

This document will help you empower your developers to fully embrace the product and make the most of AI-powered development. 

### **1\. Subscribe your organization**

Before you begin your rollout, you’ll need to ensure your organization has an active [Copilot subscription](https://docs.github.com/en/copilot/managing-copilot/managing-github-copilot-in-your-organization/managing-the-copilot-plan-for-your-organization/subscribing-to-copilot-for-your-organization) in place. There are two ways to subscribe:

* **Copilot Business**: An individual organization can subscribe directly to Copilot Business. This plan includes core Copilot capabilities like code completion, chat, and code review features.

* **Copilot Enterprise**: For organizations that are part of an enterprise account, Copilot is enabled and managed at the enterprise level. Enterprise owners control subscription and access across multiple orgs within the enterprise.

What’s the key difference between these plans? Some advanced features—like [Copilot coding agent](https://docs.github.com/en/copilot/using-github-copilot/coding-agent), knowledge bases, and fine-tuning with GitHub Models—are only available with Copilot Enterprise. If your organization wants early access to new capabilities or deeper AI customization, Copilot Enterprise provides the broader feature set. 

Pro tips: If you’d like help on deciding which plan is right for your organization, see [this guide to choosing your enterprise’s plan for GitHub Copilot](https://docs.github.com/en/copilot/rolling-out-github-copilot-at-scale/planning-your-rollout/choosing-your-enterprises-plan-for-github-copilot). And If you’re unsure which plan you're currently on, or need enterprise-level access, visit your [Copilot settings](https://github.com/settings/copilot) to request access or talk with your enterprise owner.

**2\. Set policies that fit your needs**

Next, you’ll need to [set up policies](https://docs.github.com/en/copilot/managing-copilot/managing-github-copilot-in-your-organization/managing-policies-for-copilot-in-your-organization) to control how Copilot behaves in your org. This includes deciding whether features like [Copilot Chat](https://docs.github.com/en/copilot/using-github-copilot/copilot-chat) or [Copilot coding agent](https://docs.github.com/en/copilot/managing-copilot/managing-github-copilot-in-your-organization/adding-copilot-coding-agent-to-organization) are enabled and setting filters for content or code matching.

But policies aren’t just technical controls, they’re also a key part of your rollout strategy. Use role-based permissions to pace adoption, manage demand, and build momentum across your teams.

Here’s how a phased rollout can look:

* **Start small:** Many organizations begin by enabling Copilot for a select group of early adopters. This helps surface blockers, uncover edge cases, and create internal champions who can help others adopt the tool.

* **Expand deliberately:** As confidence grows, you can scale access team-by-team or business unit-by-business unit.

* **Leverage self-service:** Many successful organizations enable self-service licensing, allowing developers to claim seats without lengthy approvals, accelerating adoption while keeping license management flexible.

Why take this approach? A phased rollout gives you better visibility into adoption patterns, developer satisfaction, and technical blockers, leading to a smoother, more durable rollout at full scale. Learn more with these [tips for a successful rollout of GitHub Copilot](https://resources.github.com/learn/pathways/copilot/essentials/tips-for-a-successful-rollout-of-github-copilot/).

**3\. Set up networking (if needed)**

While most teams can start using Copilot immediately, certain enterprise environments may require additional networking configuration to ensure seamless access. If your developers connect through a [proxy server or firewall, you'll need to configure a few things for Copilot](https://docs.github.com/en/copilot/managing-copilot/managing-github-copilot-in-your-organization/configuring-your-proxy-server-or-firewall-for-copilot):

* Add key Copilot-related URLs to your allowlist  
* Ask your developers to configure proxy settings in their IDE and install custom SSL certificates [if required](https://docs.github.com/en/copilot/managing-copilot/configure-personal-settings/configuring-network-settings-for-github-copilot).

Why this matters: Addressing network prerequisites early avoids common deployment blockers, reduces support tickets, and ensures your developers can begin using Copilot without delays. This is especially important if you're running a staged rollout where early adopters serve as your first test group. Identifying network issues at this stage helps clear the path for wider adoption.

More detailed guidance is available in [GitHub’s networking configuration documentation](https://docs.github.com/en/rest/code-security/configurations?apiVersion=2022-11-28).

**4\. Grant access to the right people**

Deciding who gets access and when is one of the most important levers you have to drive a successful rollout. [Common access models](https://docs.github.com/en/copilot/managing-copilot/managing-github-copilot-in-your-organization/managing-access-to-github-copilot-in-your-organization/granting-access-to-copilot-for-members-of-your-organization) include:

* **Targeted pilots:** Enable Copilot for select teams or early adopters who are excited to test and provide feedback.

* **Org-wide deployment:** Grant access to all eligible developers at once, if you’re confident in your environment and the demand.

* [**Self-service model**](https://docs.github.com/en/copilot/rolling-out-github-copilot-at-scale/assigning-licenses/setting-up-a-self-serve-process-for-github-copilot-licenses)**:** Allow developers to claim a license without requiring manual approval (a highly effective approach we see across many customers).

Why start with early adopters? Smaller pilot groups help surface technical blockers, build internal champions, and generate early wins. These teams often become internal advocates who help promote Copilot adoption across the organization.

You can find more rollout strategies in [GitHub’s rollout best practices](https://resources.github.com/learn/pathways/copilot/essentials/tips-for-a-successful-rollout-of-github-copilot/).

**5\. Drive adoption across the org**

The most successful deployments [build support and energy around Copilot](https://docs.github.com/en/copilot/rolling-out-github-copilot-at-scale/enabling-developers/driving-copilot-adoption-in-your-company). They educate teams, share use cases, and track success.

Strategies that drive lasting adoption include:

* **Internal champions:** Empower enthusiastic developers to serve as advocates and peer coaches.

* **Training sessions:** Host lunch-and-learns, office hours, or Q\&A sessions to share best practices and answer common questions.

* **Leadership alignment:** Ensure executives are visibly supportive of Copilot adoption to signal org-wide commitment.

* **Success tracking:** Monitor usage patterns and gather feedback to refine your rollout as adoption grows.

The goal, of course, is to not just help employees access Copilot, but to actually integrate it into their daily work and start unlocking real productivity gains and ROI. Implementing a strong [enablement plan](https://resources.github.com/engineering-system-success-playbook/) ensures your AI adoption efforts actually stick.

**6\. Enhance the Copilot experience**

Once your teams are comfortable with Copilot, it’s time to glean even more value with GitHub’s latest AI features, including:

* [**Copilot coding agent**](https://docs.github.com/en/copilot/rolling-out-github-copilot-at-scale/enabling-developers/using-copilot-coding-agent-in-org): Automate tasks asynchronously and reduce manual toil.

* [**Copilot code review**](https://github.blog/changelog/2025-04-04-copilot-code-review-now-generally-available/): Get intelligent, customizable suggestions during pull requests.

* [**Copilot Spaces**](https://www.youtube.com/watch?v=c5iFS0nlAxM): Share context across teams to improve Copilot’s relevance and recommendations.

* [**GitHub Models**](https://github.blog/news-insights/product-news/introducing-github-models/): Build custom developer tools that call AI models within your enterprise environment.

* [**Copilot Autofix**](https://docs.github.com/en/code-security/code-scanning/managing-code-scanning-alerts/responsible-use-autofix-code-scanning): Automatically remediate security vulnerabilities flagged in code scanning.

As adoption matures, these capabilities allow you to optimize security, automation, and code quality. Want to see how it all comes together? Check out [**this example**](https://github.blog/news-insights/product-news/from-pair-to-peer-programmer-our-vision-for-agentic-workflows-in-github-copilot/) of how GitHub’s AI features work in tandem across the software development lifecycle.

## The bottom line

Rolling out Copilot across your org is a chance to boost velocity, creativity, and collaboration among your dev teams. But getting it right means thinking beyond activation and focusing on the experience, security, and strategy behind it.

Copilot is ready to work hard for your teams, helping deliver increased productivity and profit. Are you ready to let it fly?

[Build what’s next with Copilot today \>](https://github.com/features/copilot/copilot-business)

---

Want to learn more about the strategic role of AI and other innovations at GitHub? Explore [Executive Insights](https://github.com/solutions/executive-insights) for more thought leadership on the future of technology and business.

To realize Copilot’s full potential, leaders need to roll out Copilot strategically, thinking holistically about access, governance, enablement, and adoption.

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August ‘25 enterprise roundup

Published via [GitHub Executive Insights](https://github.com/solutions/executive-insights "Executive insights, curated just for you") | Authored by [Jared Bauer](https://github.com/jaredsb)

Code review with fast turnaround times helps developers [feel 20% more innovative](https://azure.microsoft.com/en-us/blog/quantifying-the-impact-of-developer-experience/) by enabling them to move to their next idea quickly. And how developers feel directly affects the quality and momentum of their work. Now that AI is authoring more code, how are code review practices adapting in response? To answer this, we've been collecting perspectives from engineering teams across the industry about AI's impact on their workflows. What we've learned might just change your approach to code reviews, too. These emerging patterns highlight both unexpected challenges and promising opportunities that forward-thinking engineering leaders should be evaluating now.

### What's new on the horizon 

* **AI reviews first:** Developers are using AI to review their code before human eyes ever see it.

  *“If I don't see that someone else from my company has requested a review from Copilot, then I'm requesting it first. Then I’ll go do some other work, come back to the review, and read through the Copilot comments.”*

  \- Mikołaj Bogucki, Software Developer

* **"Needle-in-haystack"** detection skills for spotting critical issues within large AI-generated changes. Successful teams are developing their intuition regarding where to focus on reviews that have been generated with AI and code segments that deserve extra attention.  
* Developers **guard against confirmation bias** by recognizing that AI tools may not pick up every possible opportunity for improvement. They acknowledge the subtle psychological trap where an AI review returning minimal feedback can be misinterpreted as comprehensive validation. Forward-thinking teams deliberately counteract this tendency by maintaining healthy skepticism toward AI reviews, establishing clear expectations around what AI reviews can realistically detect.  
* **Strategic tool-switching** between IDEs (for complex semantic reviews) and browsers (for simpler changes).

  *“I will use \[the GitHub web UI\] for light technical reviews. If I know that I'm going to look through this code and I'm doing a full architectural review; I want to sit down and make sure that their code makes sense, there's not too many impacts up and down stream, then I do that in VS code."*

  \-Jack Timmons, Senior Software Engineer

### What remains bedrock

* **Keeping changes small** to ensure that the ease of writing code with AI doesn’t impact delivery time by making pull requests too large for effective review  
* **Tests** as a necessary, but not sufficient, tool for ensuring quality. Engineers continue to have a critical role in testing ensuring that as a code base evolves test coverage remains comprehensive    
* **Human experience, oversight, and foresight** for logical correctness and consistency with the codebase. This ensures that changes always align with organizational priorities.  

  *“I tend to think that If an AI agent writes code, it’s on me to clean it up before my name shows up in git blame.”* 

  \-Jon Wiggins, Machine Learning Engineer 

This is just the beginning of what promises to be an evolution in how we ensure code quality. These observations aren't universal yet. Different teams are finding different paths. But these insights affirm our approach at GitHub. We've always believed that AI's greatest value isn't just in generating more code faster, but in elevating the entire development experience to produce better software.

---

Unlock engineering success with GitHub’s ESSP, our [three-step playbook](https://resources.github.com/engineering-system-success-playbook/) for productivity, velocity, and impact.

Balance AI-powered code review with essential human oversight to enhance the development experience.

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Catch up on the latest information on GitHub products released daily. In this webinar, we will summarize the updates announced in the Changelog by product, such as GitHub Copilot, Actions, and security. 

Presentation slides and video will be published later.

[GitHub Korea official X (formerly Twitter) account](https://x.com/githubkr)</a> posts the latest information. Please follow us.

This webinar is in Korean only: Introducing the latest GitHub updates

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Video and slides published: GitHub update webinar on Aug 21 (in Korean)

In this webinar, we summarized the updates announced in the Changelog by product, such as GitHub Copilot, Actions, and Security. In addition, we welcomed JFrog as a guest and introduced the integration between GitHub and JFrog and the JFrog Copilot Extension.

This webinar is in Japanese only: Introducing the latest GitHub updates and JFrog integrations

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