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Perplexity

Based exclusively on public evidence • 20 criteria (Privacy + AI)
Last review: 13 Feb 2026

C-
AITS IA

AI Trust Summary

AI Training
NO — explicit policy
Data Retention
Partially mentioned (no defined period)
Opt-out
Only generic controls (cookies, ads)
AIPrivacy
C-
BasePrivacy
A-

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Attention Points in AI (2)

AI criteria that require attention. Buy the Premium Analysis to see all 2 criteria.

Ethical AI principles and anti-bias measures not documented

AI decision contestation mechanism not available

Source: vendor public documents

Compliances in AI (3)

AI criteria the company meets. Buy the Premium Analysis to see all 3 criteria.

AI data retention policy clearly documented

AI training opt-out control available

Automated AI decisions explained in an understandable way

Source: vendor public documents

Highlights in Privacy (3)

Most relevant criteria for this category. Buy the Premium Analysis to see all 3 criteria.

Data controller identity and contact clearly disclosed

Privacy contact channel available

Data controller and processor roles clearly defined

Source: vendor public documents

Conformance analysis (20)

Premium Feature
AITS Criterion 5
Non-compliant

Ethical AI principles and anti-bias measures not documented

Reference: ISO/IEC 42001 (6.1) + ISO/IEC TR 24028 + EU AI Act (Art. 9)

AITS Criterion 8
Non-compliant

AI decision contestation mechanism not available

Reference: ISO/IEC 42001 (8.3)

AITS Criterion 1
Compliant

AI data retention policy clearly documented

Reference: ISO/IEC 42001 (8.2) + ISO/IEC 27701 (7.4.6)

Source: vendor public documents

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Perplexity: A Comprehensive Review of Privacy and AI Governance

Transparency in Data Usage Policies

Perplexity excels in its transparency regarding data usage policies, which is crucial for users concerned about privacy. With an impressive AITS Privacy Score of 89%, the platform clearly outlines how user data is utilized for AI training. This clarity helps users understand what data is being collected and how it contributes to the AI's functionality. For users, this means you can engage with the platform knowing that your data is handled with care, and you have a clear understanding of its implications.

Moreover, Perplexity provides explicit information about the identity and contact details of the data controller. This is a significant strength, as it allows users to easily reach out for any privacy-related inquiries or issues. Users should take advantage of this by familiarizing themselves with the contact information provided, ensuring they know whom to approach if they have concerns about their data.

Clear Declaration of AI Usage

Another notable strength of Perplexity is its clear declaration of AI usage within its policies. This transparency is essential for users who want to understand how AI impacts their interactions with the software. Knowing that the platform openly discusses its AI capabilities can enhance user trust, as it indicates a commitment to ethical practices in AI deployment. Users should review these policies to grasp how AI influences their experience and to ensure that they are comfortable with the technology being used.

Lack of Documented Ethical AI Commitments

Despite its strengths, Perplexity has notable weaknesses, particularly concerning its commitments to ethical AI practices. The absence of documented commitments raises concerns about how the platform addresses potential biases or ethical dilemmas in AI decision-making. For users, this means you may want to approach the use of the software with caution, as the lack of transparency in ethical considerations could impact the fairness and reliability of AI outputs.

To mitigate this risk, users should stay informed about updates to Perplexity's policies and actively seek out any forthcoming commitments to ethical AI practices. Engaging with the platform's community or support channels can also provide insights into how these issues are being addressed over time.

Absence of AI Decision Contestation Mechanism

Another significant weakness is the lack of a mechanism for contesting AI decisions. This absence can be problematic for users who may find themselves affected by automated decisions made by the AI. Without a clear process for contestation, users may feel powerless if they disagree with an AI-generated outcome.

To safeguard against this, users should document their interactions with the AI and any decisions made. If you encounter a decision that seems unfair or incorrect, reach out to the data controller using the contact information provided. This proactive approach can help ensure that your concerns are heard and addressed.

Opt-Out Controls for AI Training

Perplexity does offer opt-out controls for AI training, which is a positive aspect for users who wish to limit the data used for training purposes. However, it is essential to understand how to effectively utilize these controls. Users should navigate to the settings menu to ensure that they have opted out if they prefer not to contribute their data to AI training. This step is crucial for maintaining a level of privacy and control over personal data.

Practical Steps for Enhanced Privacy

To enhance your privacy while using Perplexity, consider reviewing and adjusting your privacy settings regularly. Familiarize yourself with the platform's privacy policies and stay updated on any changes. Additionally, if you have concerns about data usage or AI decision-making, do not hesitate to reach out to the data controller for clarification. Engaging with the platform’s community can also provide valuable insights and support from other users who share similar concerns. By taking these proactive steps, you can better navigate the complexities of privacy and AI governance while using Perplexity.

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Scope & Limitations

TrustThis/AITS assessments are based exclusively on publicly available information, duly cited with date and URL, following the AITS methodology (privacy & AI transparency).

The content is indicative in nature, intended for screening and comparison, not replacing internal audits.

TrustThis/AITS does not perform invasive tests, does not access vendor technology environments and does not process customer personal data. Conclusions reflect only the vendor's public communication at the date of collection.

Source: vendor public documents