When configuring an advanced DLP rule in Microsoft Purview Data Loss Prevention (DLP), you can use a Sensitive Information Type (SIT) condition to detect and classify specific types of sensitive data, such as credit card numbers, Social Security numbers, or custom sensitive data patterns. This allows you to apply protection and trigger actions based on the identified content.

Explanation:
Box 1: must sign in to the Office 365 Message Encryption (OME) portal to read messages.
Recipients using Gmail can read emails protected by Microsoft Exchange Online mail flow rules set to Protect with OMEv2 (Office Message Encryption version 2). They will typically receive a link to view the message in the Microsoft Purview Message Encryption portal.
Box 2: will have messages decrypted automatically
Recipients from an external Microsoft 365 subscription can read emails protected by a Microsoft Exchange Online mail flow rule set to "Protect with OMEv2" (Microsoft Purview Message Encryption). External recipients will receive a wrapper email with instructions on how to access the encrypted message, either by signing in with their Microsoft account, Google account, Yahoo account, or by using a one-time passcode.
Reference:
https://learn.microsoft.com/en-us/purview/email-encryption
https://learn.microsoft.com/en-us/purview/ome

Seed content files for a custom trainable classifier should be stored in a SharePoint Online folder (or folders) that is dedicated to holding only that seed content. You'll need to create a separate folder for positive examples and another for negative examples. After placing the files, make note of the full URL of the SharePoint site, library, and folder for each set of content.
Note: How to create a trainable classifier: The following process automates the testing of trainable classifiers and shortens the creation workflow from 12 days to two days. In some cases, the process can take only a few hours.
1. Collect between 50 and 500 seed content items that strongly represent the data you want the classifier to positively identify as being in the category. For a list of supported file types, see Default crawled file name extensions and parsed file types in SharePoint Server.
2. Collect a second set of seed content (from 150 to 1,500 items) that represents data that don't belong in the category.
3. Place the positive and negative seed content in separate SharePoint folders. Each folder must be dedicated to holding only the seed content. Make note of the site, library, and folder URL for each set.
4. Sign in to the Microsoft Purview portal with either Compliance admin or Security admin role access and navigate to Data loss prevention > Data classification > Classifiers.
Reference:
https://learn.microsoft.com/en-us/purview/trainable-classifiers-get-started-with

https://docs.microsoft.com/en-us/cloud-app-security/azip-integration

Considerations for DSPM for AI to manage data security and compliance protections for AI interactions To prevent users from sharing sensitive information with third-party generative AI websites when Windows devices are onboarded to Microsoft Purview, you can configure Data Loss Prevention (DLP) policies. These policies allow you to restrict access to specific service domains and block file uploads or sensitive data sharing with those domains.
Reference:
https://learn.microsoft.com/en-us/purview/dspm-for-ai-considerations