MC1041459 - Microsoft Viva Learning: Surfaces will be personalized according to user skills/interests

Service

Microsoft Viva

Last Updated

Apr 17, 2025

Published Mar 26, 2025

Tag

Updated message
New feature
User impact
Admin impact

Platforms

Desktop
Web

Summary

Microsoft Viva Learning will personalize content based on user-selected and inferred skills from Microsoft Graph. The rollout for Public Preview started in mid-March 2025, and General Availability will begin in mid-April 2025. Organizations should enrich content with detailed information to improve recommendation accuracy.

More information

Updated April 17, 2025: We have updated the rollout timeline below. Thank you for your patience.

Viva Learning surfaces will be personalized based on user-selected skills and inferred skills derived from the user's role and activity within Microsoft Graph. This ensures that the learning content is tailored to each user's unique needs and professional context.

This message is associated with Microsoft 365 Roadmap ID 479751.

When this will happen:

Public Preview: We began rolling out in mid-March 2025 and expect to complete by late March 2025.

General Availability (Worldwide): We will begin rolling out in mid-April 2025 (previously early April) and expect to complete by late April 2025 (previously mid-April).

How this will affect your organization:

  • The Viva Learning home page carousels Browsing by Provider, Duration, and Learning Path will now use the user selected skills/interests to show relevant content.
    If there is no user selected skill, then Viva Learning uses the inferred skill of the user to show relevant content.  
  • The More from Providers carousel in the Details page is enhanced to show information relevant to the content skills. 
  • If Skills experience is not enabled for a user, then relevance will work as per the interests chosen by the user.

What you need to do to prepare:

Since Skills-based relevance relies on content titles, descriptions, skill tags, and keywords, we recommend that Viva Learning curators enrich their content with detailed information on these attributes. This will help the recommendation engine to better understand the content and provide more accurate suggestions for user queries.