AI Training Practices
Training on Personal Data
Yes
Training on User Interactions
Yes
Training on Public Content
No
AI Data Sharing
Unclear
AI Use Cases
- Content Processing — AI and machine learning technologies are used to facilitate the processing of personal information.
- Personalization — AI is likely used to improve and optimize services, understand user behavior, and develop new features, leading to personalization. Also explicitly for personalized advertisements.
- Recommendation — AI is used for displaying personalized advertisements, which are a form of recommendation.
- Fraud Detection — AI is likely used for maintaining security, detecting unauthorized use, and fraud monitoring and prevention.
- Other — AI is used for developing new products, services, features and functionality.
Risk Assessment
The extremely low deterministic score (0/70) is a critical red flag, indicating severe underlying privacy and security deficiencies despite the policy's stated compliance with GDPR/CCPA. This suggests a significant gap between policy and practice. The broad collection of user data, including conversation records, combined with sharing with vaguely defined 'third parties' for advertising, further elevates privacy risks.
Recommended Actions
- Exercise extreme caution when sharing any sensitive personal or business information with Intercom.
- Thoroughly review the actual data handling practices and security measures if you must use their services, as the policy may not reflect reality.
- Utilize their data request form to understand precisely what data they hold on you and consider requesting deletion.
- Explore alternative services with higher privacy ratings and a proven track record of robust data protection.
AI Overview
Trains on user dataYes
Trains on interactionsYes
Opt-out availableNo
AI disclosureYes
Third-party AIYes
AI Products Detected
generative AIDetected
AI Training Opt-Out
No opt-out mechanism available.