How do you protect your data when using AI in ChatGPT for Enterprise?
Here’s what you need to know around the AI risk.
We assess each vendor’s AI risk posture using 26 risk vectors mapped to leading frameworks like OWASP for LLM. This page will show a high-level snapshot of some information for each vendor. For the full, vendor-specific AI risk report, click the image below.
Feature Overview
Each vendor provides a unique set of features, and implements AI in certain ways. Let's see what types of AI features they have to offer:
ChatGPT for Enterprise | Microsoft Copilot |
---|---|
Allows ChatGPT to operate a web browser and terminal on the user's behalf, with access to additional connected data sources (e.g., web search, Gmail, GitHub, etc.). |
Build and customize no-code and low-code apps that automate processes and connect to data; integrate AI-powered components to analyze information and generate insights. |
… see more in full report |
Want to see all AI features?
Pricing Details
Let's dive into the relevant pricing details for accessing AI, as providers vary widely in their pricing models and cost drivers.
Vendor | Description | ChatGPT for Enterprise |
---|---|---|
Freemium | Offers free tiers | |
Per License/Seat | Charges per user or access point | |
Consumption-Based | Pay per taken, API call, inference, etc. | |
Outcome-Based | Pay only when certain results or performance goals are achieved |
Some Quick facts about each vendor
Here are some facts about ChatGPT for Enterprise
ChatGPT for Enterprise |
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ChatGPT Enterprise was officially launched in August 2023, marking OpenAI’s entry into the enterprise AI market. |
The brand exists because business leaders demanded stricter security, data control, and compliance features than consumer AI tools provided; this pushed OpenAI to accelerate development and shift its branding toward “trusted business partner”. |
ChatGPT Enterprise is positioned as a scalable business platform, offering dedicated support and customizable integration to fit organizational requirements and workflows. |
If your app pulls in third-party content — like URLs, comments, or files — LLM features can be tricked into leaking private data through indirect prompt injection. Most teams don’t even realize it’s happening.
According to a 2025 Gartner survey,
73%
of enterprises have suffered an AI-related security breach in the last year
$4.8M
average cost per incident — with indirect prompt injection and data leakage via LLMs now among the top attack vectors for financial services and healthcare organizations
In recent incidents, platforms like ChatGPT and Microsoft 365 Copilot were exploited by attackers using hidden prompts and indirect content injection, leading to unintended data exposure
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