What is ChatGPT Enterprise? Pricing, uses and features

Pricing

The Free, Plus, Pro and Business versions of ChatGPT have the following set pricing:

• Free is $0 per month.
• Plus is $20 per month.
• Pro is $200 per month.
• Business is $25 per user, per month, billed annually or $30 per user, per month, billed monthly.

The Enterprise version, however, does not have a set price. Instead, subscription-based pricing is available upon request. The price is likely to change depending on the organization's size, model usage and other needs. The cost is also likely higher than ChatGPT Business, which is the tier below Enterprise.

Features

ChatGPT Enterprise is designed to offer enterprise-grade features. It contains all the features available from the Business tier below it, plus several key differentiating features, including the following:

• Enterprise-grade security and privacy. Customer prompts and company data are not used to train OpenAI models. Data is also encrypted at rest and in transit, and the software is certified Service and Organization Controls 2 (SOC 2) compliant. Enterprise also offers System for Cross-domain Identity Management (SCIM), user analytics and role-based access controls.
• Management features for enterprise administrators. ChatGPT Enterprise offers an admin console for bulk user management, support for single sign-on and domain verification, and an analytics dashboard for usage insights.
• Improved availability and performance. ChatGPT Enterprise provides users with unlimited high-speed access to the GPT-5 large language model (LLM).
• Data analytics and development features. ChatGPT Enterprise offers unlimited access to advanced data analysis, formerly known as Code Interpreter, and free application programming interface (API) credits for enterprise developers looking to customize ChatGPT further.
• Longer, more detailed prompts. ChatGPT Enterprise extends ChatGPT's context window to 128,000 tokens, quadrupling the potential length of initial user prompts, files and follow-up questions.
• Reusable templates and workflows. ChatGPT Enterprise offers shareable chat templates for internal collaboration and the ability to build custom workflows, which could help users take advantage of the technology without needing advanced prompt engineering skills.
• Support for data residency. ChatGPT Enterprise provides regional data residency options, enabling enterprises to ensure their data is stored and processed in seven specific regions.
• Priority support. OpenAI provides 24/7 priority support, service-level agreements, customizable legal contract terms and access to AI advisors.
• Built for scale. OpenAI offers support for unlimited users, volume discounts and invoicing, as well as automated clearing house billing.

How can businesses use ChatGPT Enterprise?

ChatGPT Enterprise is meant to improve a business's operations, making them more efficient. Businesses can use ChatGPT Enterprise for the following:

• Automation. Users can automate the creation of templates, reports and other tasks to streamline workflows.
• Communication. Users can summarize meetings, generate reports or craft emails to employees or customers.
• Customer service. ChatGPT Enterprise can be integrated into customer support systems to provide responses to customer questions.
• Data analysis. ChatGPT Enterprise can be used to clean, analyze and visualize large amounts of data.
• Marketing. ChatGPT Enterprise can generate ad campaign ideas based on an organization's customer demographics and behavior.
• Research. Advanced data analysis in ChatGPT Enterprise can sift through data from large datasets and summarize it for the user.
• Software development. Developers can use ChatGPT Enterprise to aid in the coding process, such as debugging code, creating tests or writing other documentation.

What's the difference between ChatGPT Enterprise and other plans?

Each ChatGPT plan builds on everything that appears in the underlying tiers. Each plan is suited to a different target audience and use case.

ChatGPT Enterprise vs. ChatGPT Business

ChatGPT Business -- formally Teams -- and Enterprise are the two most related plans.

The Business plan includes everything offered in the Pro plan. Business data is excluded from training, and the plan offers more security and business features than Pro.

ChatGPT Business requires at least two seats -- which are like single-user licenses -- and is ideal for small to mid-size teams.

ChatGPT Enterprise, by comparison, contains all the features included in Business, plus support for longer inputs, enterprise-level security features and support for use at scale.

ChatGPT Enterprise does not have a seat minimum but is best suited for large-scale use in enterprise-level organizations.

ChatGPT Enterprise vs. ChatGPT Pro

ChatGPT Pro is based on usage and does not offer seat-based licenses. It includes everything that appears in Plus, as well as unlimited access to GPT‑5 and all reasoning models, access to GPT-5 Pro, and extended access to other features.

ChatGPT Pro is suitable for small teams of multiple developers or technical users.

ChatGPT Enterprise vs. ChatGPT Plus

ChatGPT Plus is designed for individual use and contains everything in the free version, but it expands on messaging limits, file uploads, and data analysis options, with limited access to video generation through Sora.

While Enterprise is aimed at large-scale use at large organizations, ChatGPT Plus is targeted toward individual professionals or power users.

ChatGPT Enterprise vs. ChatGPT Free

The Free and Enterprise plans differ the most. The free plan limits access to GPT‑5, file uploads, data analysis and image generation. This version is meant for individual use and provides only one seat per account. This plan is aimed at any casual user who wants to explore the use of AI without a structured use case.

How secure is ChatGPT Enterprise?

OpenAI promotes ChatGPT Enterprise as having the following security features, which make it enterprise-grade:

• Data at rest is encrypted using Advanced Encryption Standard 256 encryption.
• Data in transit is encrypted using Transport Layer Security 1.2+.
• Domain verification for proving the organization owns a specific email domain.
• Certified SOC 2 compliant to effectively protect customer data.
• SCIM provisioning to create, modify or delete user accounts and permissions.
• Role-based access controls grant users access to specific systems based on their assigned job role.
• User analytics provide administrators with a dashboard they can use to monitor usage and provide insights into adoption and engagement.

ChatGPT Enterprise also has several privacy features that limit the amount of data shared with OpenAI. For example, OpenAI states that it does not use business data or conversations to train its own models.

How to implement ChatGPT Enterprise

Having a structured implementation framework is critical when integrating ChatGPT Enterprise or any other AI model -- just as it was for previous game-changing technologies such as software as a service (SaaS) and cloud, which are now integral elements of many businesses.

For example, when implementing ChatGPT at the enterprise level, several security and compliance concerns can arise, as well as stakeholder and employee questions and concerns that come with any introduction of generative AI (GenAI). Mitigate these issues by using the following implementation framework to roll out ChatGPT Enterprise.

1. Analyze and define the implementation plan

When implementing a GenAI application of the scope that ChatGPT Enterprise promises, an analysis and definition phase is essential. Some critical steps in this phase include the following:

• Analyze and define the organization's use cases for an LLM and map out the existing enterprise architecture.
• Determine any industry compliance standards or security protocols that the implementation must follow, such as the Health Insurance Portability and Accountability Act or the Sarbanes-Oxley Act.
• Identify where relevant corporate data resides and how ChatGPT Enterprise will access and consume that data.
• Recruit a pilot team from both the IT and business sides of the organization.
• Engage the cybersecurity team throughout the implementation process to weigh in on all security and compliance questions.

2. Review and negotiate pricing, licensing and contracts

Expect that ChatGPT Enterprise licensing and contracts might continue to evolve, even for organizations that aren't among the first wave of customers implementing the software. Take the extra time to perform a thorough legal review of the licensing and contract terms, especially where they concern AI and the security of corporate data.

Unfortunately, there is no public pricing available for ChatGPT Enterprise. Instead, OpenAI refers potential enterprise customers to the sales team; OpenAI's chief operating officer has said that the company will work with customers on a pricing plan based on their needs.

This situation, while typical for startup SaaS vendors, requires organizations to bring their own pricing expertise to the table. This could add another challenge, depending on in-house knowledge and skills. It also raises the potential threat of a price increase surprise at renewal time unless pricing is locked in during initial negotiations.

3. Plan to integrate ChatGPT Enterprise

Integrating ChatGPT into existing applications and systems is a critical step.

The top priority should be API integration: determining how ChatGPT Enterprise will communicate with other corporate applications and back-end systems using APIs. It's also essential to define the data ingestion process that will enable ChatGPT Enterprise to securely consume and update necessary data while adhering to compliance standards. The organization must also plan to implement secure authentication to ensure only authorized users can access ChatGPT Enterprise.

4. Customize the model and train personnel

Training has a dual meaning when implementing enterprise-level GenAI software.

First, expect to spend some time fine-tuning the base LLM on the organization's data to ensure that the model's output is more domain-specific. For example, a niche engineering firm will need to train ChatGPT on the terminology specific to the company's field. This process often involves collecting training data to ensure good performance.

Next, during or shortly after model customization and training, it's essential to train stakeholders and end users on the new GenAI system. Stakeholder training should target managers and executives, with an emphasis on the business realities and value proposition for GenAI, whereas user training should focus on job-related use cases. Plan to create job aids for knowledge transfer to help new and skeptical GenAI users get started and prepare the service desk team to handle inquiries about ChatGPT Enterprise.

5. Conduct a pilot or proof of concept

Don't get lost in the GenAI hype. As with any new tool, whether from a startup or an established enterprise vendor, there's no getting around the need for a pilot or proof of concept inside the organization with real users.

When planning a ChatGPT Enterprise pilot, consider getting creative with the scope. For example, include marketing, analytics and sales use cases. Tying the pilot to scenarios that can help make sales more efficient should answer the questions of GenAI proponents and naysayers alike with verifiable facts and data.

6. Go live

Teams' work in the previous phases culminates in ChatGPT Enterprise going live in the organization. During this phase, project stakeholders and the service desk will be busy supporting users as the new GenAI tool joins existing workflows. Be sure to have feedback channels in place so that teams can learn what is and isn't working regarding GenAI adoption.

7. Engage in continuous learning

Continuous learning takes on new meaning when implementing GenAI in the enterprise. Marketing messages fade as teams cut through the noise by doing the actual work. All signs in the information that OpenAI has released so far on ChatGPT Enterprise point to more learning being key to implementation success.

ChatGPT is flexible in terms of how it can be used in enterprise settings. Learn more about use cases and implementation processes of ChatGPT Enterprise.