Visit our pricing page for more information.
Customers maintain control over their data contribution preferences; when enabled Asana collects de-identified information regarding platform usage. Known as "Usage Patterns," this data helps us identify common use cases and evaluate our performance so we can build a better product for you. Admins & Super Admins on our Starter, Advanced, and Enterprise plans can opt out at any time via the Admin Console.
To clarify our practices: Derived usage patterns are de-identified, and this data is not used to train or fine-tune AI models. This is designed to analyze high-level usage patterns, providing insights that help us improve your experience using Asana.
Note
For our Enterprise customer on negotiated terms, data contribution to derive usage patterns will start at your next renewal after September 16th, 2026. For our Advanced, Personal, or Starter domains, data contributions will start on September 16th, 2026. A toggle is available in the admin portal to disable Data contributions available in advance so you can update your preferences in advance of the policy applying.
To opt out, an Admin or Super Admin should navigate to Admin Console > Security > Data Contributions and choose ‘Do not share data’:
Note
Data contribution is permanently turned off for Asana Gov and HIPAA customers, and is default disabled for customer with EU Data Residency.
Usage patterns help us build the features your team actually needs, faster so you get more value out of Asana sooner.
Today, we rely heavily on direct customer conversations and manual feedback to understand how Asana is used in practice. That's valuable but it only captures a slice of real-world usage. Usage patterns let us see, at scale, which workflows and AI features are working well and where friction still exists so we can fix quality gaps and ship improvements before they become a support ticket for your team.
This also means our roadmap is shaped by how customers like you actually work, not assumptions. High-impact workflows get prioritized. AI features get tuned to reflect the way real teams structure projects, automate work, and search for information. This translates into faster time-to-value and stronger adoption across your organization. Using aggregated usage data to guide product development this way is standard practice across enterprise software, and one we apply with the privacy safeguards described throughout this article.
Usage patterns are broad category labels that describe the type of action people take in Asana. For example, a request to create a project from a template or summarize project status may be grouped into a general theme. Asana uses these labels to understand which experiences are helpful, where quality gaps exist, and which workflows may need improvement.
To create these labels, an AI or ML model processes the interaction long enough to assign a general theme - Asana employees cannot access the unprocessed data. The usage pattern stored is limited to the labels and, in some cases, a quality score tied to that label.
An end-to-end Example:
|
What a user enters |
How it’s processed |
What Asana keeps & reports on: |
|
A user asks their AI Teammate “Find all tasks assigned to me that are overdue in the Q3 Launch project.” |
An LLM processes the request, and assigns a usage pattern label (or multiple), and identifying user and domain details are removed during processing |
The labels are stored for reporting:
|
When the usage patterns setting is enabled, Asana retains the de-identified labels about the type of work performed, along with high-level account details such as plan tier, approximate domain size, and industry. This data is designed to stay general rather than describe a specific customer’s work.
Usage pattern data is de-identified. Asana does not associate the raw text of prompts or responses to the usage patterns data or to a user name, user ID, domain name, or domain ID. Asana does not use your data to train AI models, and third-party model providers are prohibited from training on customer data.
|
Source |
Input Example The data we transiently process, then discard |
Example label(s) Never tied to an identifiable domain or user |
|
Search queries |
The terms you type when searching for tasks or projects in Asana & applied filters |
‘Keyword search’, ‘task filter’ |
|
AI Teammate instructions |
“Find all tasks assigned to me that are overdue in the Q3 Launch project” |
‘search with assignee & overdue filter’ |
|
Rule and automation configurations |
The conditions and actions you set up in Asana Rules, like “when a task is moved to Done, mark it complete” |
‘mark complete when moved to section’ |
|
Project and section names |
Project named “FY ‘25 Product Roadmap” |
‘development planning’ |
|
Custom field names and types |
Field named “Budget Status” |
‘status’ |
|
AI Chat conversations and prompts |
“Summarize the status of this project for my stakeholders” |
‘project status summary’ |
Admins can manage this setting from the admin console.
Only organization admins and super admins can access this setting. Only Super Admins can opt-in, both Admins & Super Admins can opt-out. Other members and guests cannot change it.
Note
The steps above apply to organization admins only. To opt out of data contributions for a division, your admin should contact Asana Support.
For Starter and Advanced, sharing usage patterns is on by default, and admins can turn it off. For Enterprise and Enterprise+, the default depends on region. Domains in the EU start with the setting off and can turn it on, while domains outside the EU start with the setting on and can turn it off.
Some plans show the setting in a fixed state. Asana Personal keeps the setting on and does not allow changes. Customers with HIPAA or Asana Gov cannot share usage patterns data through this setting; they are permanently disabled
Starting September 1st, existing customers will see the option to configure their usage patterns data contribution setting in advance of their next renewal. This allows Admins to choose their preferred setting before any data contribution occurs.
General
Third Parties & Model Providers
Opt-Out Settings & Details
Re-identification

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