Learning admins and sub-admins can customize Role Guides by modifying AI-generated role Titles, Skills, and Description, and uploading the custom content from their organization.
Customizations to Roles populate the LinkedIn Learning ecosystem, including:
To customize existing Role on LinkedIn Learning:
Log in to LinkedIn Learning and access Learning Management.
Select Content > Roles.
Click the
An intermediate preview page appears, with four sections:
To customize the role title, add the titles of your choice in the text box provided. Up to five titles can be input to reflect associated titles, with the first title displayed as the main title on the Role.
The learner will see the remaining titles displaying in the The role is also called section.
To add custom content, click the Add content
Click Publish. Your updates and customization will reflect in the learner experience.
To create a new Role:
Log in to LinkedIn Learning and access Learning Management.
Select Content > Roles.
Select Add new roles > Create a new role. Enter data for all relevant fields. Add up to five alternative or associated titles in the Alternative titles section.
Add role Description, Skills, and Content related to the role.
Click Publish at the bottom of the page to see a preview of that guide for the role.
Select Mark as priority role at the top of the page to ensure role shows up for learners in the Setting a career goal feature (up to 10 priority roles can be featured).
To upload multiple new Roles:
Log in to LinkedIn Learning and access Learning Management.
Select Content > Roles.
Select Add new roles > Upload CSV file.
In the pop-up module, you’ll see a link to Download .CSV template which you can then use offline to upload role titles, descriptions, skills, proficiency levels, leveling/career path information, and more.
Populate the template with your company’s talent architecture (role title, description, skills, levels).
Upload the template via the same module by selecting either Upload .CSV file or dragging your file into the Upload module.
For a more detailed step-by-step guide, visit our customer Learning Center.
After you have uploaded your .CSV, you’ll see a summary of the total number of roles processed along with a breakdown of the number of roles that were “Automatically published”, “Needs review”, and in process.
Automatically published: Roles that have the minimum required amount of data (a standardized role title, role description, and skills) will be automatically published to LinkedIn Learning. You can review and edit these roles from the Published tab within Roles.
Needs review: Roles that are uploaded with incomplete information or published roles with conflicting data (see also "Review LinkedIn suggestions for published Roles" below) are labeled as “Needs Review”.
To review and edit a Role:
Log in to LinkedIn Learning and access Learning Management.
Select Content > Roles.
Click In review on the left rail.
Use the available filters to select for roles to review according to job function, language, or the source of the role (CSV upload, LinkedIn member data, or public LinkedIn Jobs data).
Click any individual role to view the "Status" (i.e., missing information) and see the AI-assisted Suggestions powered by LinkedIn.
For any selected role, you’ll see both suggested data (e.g., a suggested role description or suggested skills to apply to that role) and the source of that suggestion (AI, LinkedIn member data, or public LinkedIn Jobs data).
You can continue editing from within the dropdown, or click Publish to accept recommendations and publish your new role.
Click Dismiss to close the dropdown, dismiss suggestions, and keep a role unpublished.
To publish all or multiple roles with LinkedIn suggestions, select either all roles via the checkbox at the top of the table, or individual role checkboxes. Select Publish in the presented actions.
For a more detailed step-by-step guide, visit our customer Learning Center.
Once you publish your selected Roles, LinkedIn Learning uses AI and LinkedIn data to help you maintain your talent architecture by making periodic suggestions to update Role descriptions and skills.
Consider the following factors when reviewing suggestions for published Roles:
LinkedIn Learning helps you expand your talent architecture by making suggestions to create new Roles with LinkedIn data.
Roles identified from public job postings or employees’ profiles that have not been uploaded through a CSV file can be found in the Needs Review tab. Those roles can be published with LinkedIn suggestions following the same steps as outlined above under "Review and publish uploaded Roles".
To download published roles and roles for review offline:
Log in to LinkedIn Learning and access Learning Management.
Select Content > Roles.
Select Download published roles to export all existing published roles.
Select Download roles that need review to select roles in the Needs review tab.
LinkedIn Learning can help you enhance your existing talent architecture via suggestions from different sources. You can decide which sources of data to use, or whether to refuse suggestions altogether.
To manage which data sources to use for suggestions:
Log in to LinkedIn Learning and access Learning Management.
Select Content > Roles.
Click Settings on the left rail.
Toggle on or off each data source that is available to your organization.
Available data sources include the following: