How to Choose the Right GitHub Copilot Plan: Step by Step Guide
The configuration surface of GitHub Copilot plans is broad because the needs are broad. A solo developer working on side projects faces a completely different set of privacy and compliance considerations than an enterprise administrator managing thousands of seats across regulated repositories. GitHub Copilot's tiered plan structure is designed to match that range. In 2026, the differences between GitHub Copilot plans come down to privacy boundaries, admin controls, auditability, and the governance your organization needs.
What You Will Learn:
- How to assess your privacy and compliance requirements before choosing a plan
- Complete breakdown of all six GitHub Copilot plan tiers with pricing
- Data handling differences between individual and business plans
- How to configure file exclusion rules for proprietary code
- How to enforce organization-wide policy settings
- How to set up and search audit logs for compliance
- How to automate seat management with the REST API
Step 1: Assess Your Privacy and Compliance Requirements
Before comparing plan features or pricing, determine what you need from a privacy and compliance standpoint. This decision should come first because it eliminates whole categories of plans immediately.
Assess Your Privacy and Compliance Requirements
Map your requirements against these scenarios: Solo developer or side projects can use Free or Pro tiers with opt-out enabled in privacy settings. Freelancers and contractors need the Business plan to provide a contractual defensive barrier for client agreements. Corporate teams with compliance mandates require at minimum the Business tier for isolated data pipelines and administrative governance. Regulated industries like finance and healthcare should default to Enterprise for specialized security configurations and strict data residency requirements.
Step 2: Compare All Plan Tiers and Pricing
GitHub offers four individual tiers and two organizational tiers. GitHub will complete its rollout of usage-based billing in June 2026, replacing the legacy Premium Request Unit framework with GitHub AI Credits. Under the new system, core code completions and Next Edit suggestions remain unlimited and do not consume credits. Advanced operations like multi-file chat, agentic workflows, long-running coding sessions, and deep code reviews consume AI Credits based on token consumption relative to the specific models published API rates.
Compare All Plan Tiers and Pricing
Review the six tiers against your budget and user count. The Free plan offers basic completion and Chat access for casual individual users. Student provides expanded AI Credits for verified students and educators at no cost. Pro costs $10/month with 1,500 total AI Credits and broad IDE integrations. Pro+ costs $39/month with 7,000 AI Credits and includes GitHub Spark access. Business at $19/user/month adds centralized seat management, audit logs, file exclusions, and IP indemnity. Enterprise at $39/user/month adds repository indexing, custom fine-tuning, and global governance but requires an active GitHub Enterprise Cloud subscription at $21/user/month making the true cost $60/user/month.
| Plan Tier | Intended User | Base Pricing | Key Differentiators |
|---|---|---|---|
| Free | Casual individual users | Free | Basic completion and Chat access |
| Student | Verified students and educators | Free | Expanded AI Credits for learning environments |
| Pro | Individual developers | $10/month | Broad IDE integrations and multi-model support |
| Pro+ | Heavy individual power users | $39/month | Large token allocations, GitHub Spark access |
| Business | Teams and organizations | $19/user/month | Seat management, audit logs, IP indemnity |
| Enterprise | Large scale enterprises | $39/user/month | Policy inheritance, custom fine-tuning, Spaces |
New Individual Account Registration Is Paused
Currently, new registrations for GitHub's individual paid accounts including Pro, Pro+, and Student are paused. Existing accounts can upgrade from Pro to Pro+, but new accounts cannot sign up until GitHub completes its transition to the new usage-based AI Credits billing system in June 2026.
Step 3: Evaluate Data Handling and Training Policies
For teams handling proprietary systems, data privacy is usually the deciding factor between personal plans and Business subscriptions. GitHub changed how interaction data collection works for individual Copilot plans in April 2026. Understanding the distinction between code at rest and interaction data is critical.
Evaluate Data Handling and Training Policies
Code at rest — the raw code in your private repository — is not read or ingested into public training sets. Interaction data — prompts, chat queries, cursor context, surrounding code blocks sent via the IDE API during active editing sessions, suggestion acceptance metrics, and feedback logs — follows different rules. On individual plans, interaction data can now be used for model training by default unless the user explicitly opts out. Business and Enterprise agreements have a strict contractual guarantee that interaction data is never used for training purposes under any circumstance, with no manual user intervention required.
| Plan Tier | Interaction Data Used for Training? | Contractual IP Indemnity? | Content / File Exclusions? | Audit Log Access? |
|---|---|---|---|---|
| Free | Yes (Opt-Out Available) | No | No | No |
| Student | Yes (Opt-Out Available) | No | No | No |
| Pro | Yes (Opt-Out Available) | No | No | No |
| Pro+ | Yes (Opt-Out Available) | No | No | No |
| Business | No | Yes | Yes | Yes |
| Enterprise | No | Yes | Yes | Yes |
Common Compliance Leakage Scenario
Imagine a developer uses a personal Copilot Pro account while working inside a corporate repository. If training remains enabled, interaction data tied to that work session including chat histories, code snippets, and cursor context from open editor tabs may enter GitHub's training ecosystem. This scenario is a primary reason organizations adopt Business or Enterprise plans.
Step 4: Set Up File Exclusion Rules
Implementing file exclusion rule sets is one of the most effective ways to defensively secure an environment. Content exclusion prevents the local IDE agent from processing specific file contents, making them completely invisible to inline completions, chat boxes, and background agentic operations. Note that GitHub Copilot CLI, Copilot cloud agent, and Agent mode in Copilot Chat in IDEs do not support content exclusion.
Configure File Exclusion Rules
Navigate to your GitHub repository or organization Settings. Under Code and automation in the Copilot settings sidebar, fill in the Paths to exclude box. At the repository level, use simple glob patterns. At the organization level, prefix each rule with the repository reference. Common baselines should prioritize hard credentials, production orchestration profiles, sensitive proprietary algorithmic modules, and highly regulated compliance folders. Test path patterns using staging repositories because malformed wildcards can fail open.
# Ignore the /src/some-dir/kernel.rs file in this repository.
- "/src/some-dir/kernel.rs"
# Ignore files called secrets.json anywhere in this repository.
- "secrets.json"
# Ignore all files whose names begin with secret anywhere in this repository.
- "secret*"
# Ignore files whose names end with .cfg anywhere in this repository.
- "*.cfg"
# Ignore all files in or below the /scripts directory of this repository.
- "/scripts/**"
REPOSITORY-REFERENCE:
- "/PATH/TO/DIRECTORY/OR/FILE"
- "/PATH/TO/DIRECTORY/OR/FILE"
Step 5: Configure Organization-Wide Policies
Enforcing organization-wide policy settings guarantees that corporate security is determined by the administration team instead of individual developer preferences. This is available on Business and Enterprise plans only.
Feature Toggles
Globally activate or suppress Copilot Chat inside development environments, command-line interfaces via the Copilot CLI, or advanced agentic code-review systems across your entire organization from a single control panel.
Public Code Filter
A legal control mechanism that blocks Copilot from returning code suggestions that closely match public open-source repositories on GitHub, reducing open-source licensing compliance risks.
Model Choice Restrictions
Restrict which specific GPT or Claude variants developers can select, allowing you to manage latency, credit consumption, and performance across the organization. Lock down expensive model usage to approved teams.
Custom Organization Instructions
Inject standard markdown policy files that append corporate coding patterns, security frameworks, and architectural paradigms to every prompt sent by your developers, ensuring consistent code quality and compliance.
Configure Organization-Wide Policies
In your Organization Settings under Copilot, enable the public code filter to block suggestions matching public repositories. Set feature toggles for Copilot Chat, CLI, and agentic code review. Restrict available models to approved variants to control costs. On Enterprise, the policy engine follows a rigid hierarchical inheritance cascade: Enterprise Policy overrides Organization Policy which overrides User Preferences. Enterprise administrators can lock policies globally, permit selective organizational overrides, or completely delegate control down the hierarchy.
Step 6: Set Up and Search Audit Logs
When compliance auditors need verification of your software supply chain or security teams trace a data leak, audit logs provide the record of platform modifications. The system records seat assignments and revocations, modifications to the public code duplication filter, alterations to file and directory exclusion patterns, and feature enablement states.
Set Up and Search Audit Logs
Navigate to the Organization Settings panel to access audit log streams. Query the interface using specific action qualifiers. Business tiers focus on organization-scoped action event streams. Enterprise accounts unlock systemic cross-organization forensic telemetry and support streaming audit events directly into external SIEM systems such as Splunk or Datadog for automated alerting and centralized immutable preservation.
# Filter logs to identify who adjusted Copilot access privileges
action:copilot.seat_assignment_created
# Identify changes made to systemic exclusions within a date window
action:copilot.content_exclusion_updated created:2026-05-01..2026-05-31
Step 7: Automate Seat Management with the REST API
Manually provisioning user seats through the UI dashboard works for small teams but breaks down under high-volume corporate onboarding workflows. Using the GitHub Copilot REST API seats endpoints allows you to treat identity and access management entirely as code.
Automate Seat Management with the REST API
Common API workflows include listing seat assignments, assigning new seats, removing seats, retrieving usage metrics, and reading organization Copilot settings. Authentication requires fine-grained personal access tokens with admin:org scopes or authorized GitHub App permissions with organization-level Copilot management privileges. Common automation patterns include connecting an HR system like Workday or Okta to auto-provision seats, running scheduled scripts to reclaim inactive seats after 30 days of no usage, and pulling daily consumption telemetry for department-level cost-center cross-charging.
import requests
# Identity Configuration
TOKEN = "YOUR_ORGANIZATION_ADMIN_PAT"
ORG = "your-corporate-org"
USERNAME = "target-developer-user"
url = f"https://api.github.com/orgs/{ORG}/copilot/billing/selected_users"
headers = {
"Authorization": f"Bearer {TOKEN}",
"Accept": "application/vnd.github+json",
"X-GitHub-Api-Version": "2022-11-28"
}
payload = {
"selected_usernames": [USERNAME]
}
response = requests.post(url, json=payload, headers=headers)
if response.status_code == 201:
print(f"Successfully allocated Copilot seat to {USERNAME}.")
else:
print(f"Failed allocation. Status: {response.status_code}")
print(response.json())
IP Indemnity and Billing Considerations
GitHub Copilot Business and Enterprise include intellectual property indemnification coverage for generated code. Individual plans do not. Indemnity means GitHub contractually agrees to provide legal protection under specified circumstances if the generated code creates intellectual property disputes. A freelancer shipping code for clients should pay close attention to this distinction.
On billing, individual plans use self-serve methods mapped directly to personal accounts. Business plans centralize billing with admin-granted seats. The organization pools its monthly allotted AI Credits based on the number of users. Enterprise plans provide even finer control with granular budget enforcement limits, cost-center grouping, and department-level allocations to prevent a single development team's heavy agentic workflows from exhausting the entire corporate credit allotment.
Enterprise Requires GitHub Enterprise Cloud
GitHub Copilot Enterprise requires an active GitHub Enterprise Cloud subscription at $21/user/month. Combined with the Copilot Enterprise license at $39/user/month, the true minimum cost is $60/user/month. This does not apply to the Copilot Business tier, which can be purchased natively by organizations running on GitHub Free or GitHub Team plans.
| Scenario | Best Option | Realistic Cost |
|---|---|---|
| Solo developer or side projects | Free or Pro | $0 - $10/month |
| Freelancers and contractors | Business | $19/user/month |
| Corporate teams, compliance mandates | Business | $19/user/month |
| Regulated industries (finance, healthcare) | Enterprise | $60/user/month (incl. E Cloud) |
| Team of 10-50, productivity focus | Business | $19/user/month |
| Enterprise, 500+ users, multi-org | Enterprise | $60/user/month (incl. E Cloud) |
Frequently Asked Questions
What is the difference between GitHub Copilot Business and Enterprise?
Business includes centralized seat management, audit logs, IP indemnity, file exclusions, and organizational policy controls at $19/user/month. Enterprise adds enterprise-wide policy inheritance, Copilot Spaces for internal documentation, enhanced GitHub.com Chat, and hierarchical governance across child organizations at $39/user/month, but requires an active GitHub Enterprise Cloud subscription ($21/user/month) making the true cost $60/user/month.
Does GitHub Copilot train on private repository code?
No. GitHub states that code at rest in private repositories is not ingested into public training sets. However, interaction data including prompts, chat queries, cursor context, and suggestion acceptance metrics from individual plans (Free, Pro, Pro+) may be used for model training unless users explicitly opt out. Business and Enterprise plans have contractual guarantees that interaction data is never used for training.
What are GitHub Copilot audit logs used for?
Audit logs track seat assignments and revocations, modifications to public code duplication filters, file and directory exclusion pattern changes, and feature enablement states. Business tiers provide organization-scoped event streams. Enterprise accounts unlock cross-organization forensic telemetry and support streaming audit events into external SIEM systems like Splunk or Datadog.
What is GitHub Copilot file exclusion and which plans support it?
File exclusion prevents Copilot from accessing specified files or directories for completions, chat, and AI-generated suggestions. When an exclusion match occurs, inline completions are blocked, and Copilot Chat returns a notice stating the file cannot be reviewed due to organizational policy. This feature is available on Business and Enterprise plans only. GitHub Copilot CLI and cloud agent do not support content exclusion.
How do I automate GitHub Copilot seat management?
GitHub provides REST API endpoints for listing, assigning, and removing seats, retrieving usage metrics, and reading organization settings. Authentication requires fine-grained personal access tokens with admin:org scopes or authorized GitHub App permissions. Common patterns include automated identity onboarding via HR system webhooks, scheduled inactive seat reclamation after 30 days, and financial dashboards pulling daily consumption telemetry for cost-center cross-charging.
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About the author
Co-founder & AI Practice Lead, Braincuber Technologies
Co-founder at Braincuber. Builds production AI agents (Anthropic Claude, OpenAI, AWS Bedrock) for US fintech, healthcare, and retail clients with SOC 2 Type II / HIPAA-scope deployments. Joins every architecture review personally.