Introduction
Your Docebo learning platform is powered by Artificial Intelligence (AI), with several AI features included in your platform to enhance the way enterprises deploy and manage their learning programs, internally and across the extended enterprise, and is designed to deliver automated and personalized learning at scale.
All users in your platform - Learners, Managers, and Admins - can benefit from AI-powered features, and as with any features and functionalities in your platform, we want to ensure that you know exactly what’s going on and how to best use these innovative and time-saving features. This article outlines some questions and answers that you may have about Docebo’s Artificial Intelligence, as well as where you’ll find the features in your platform.
How does Artificial Intelligence work in my Docebo platform?
The Artificial Intelligence in your platform lets your platform automatically perform some of the actions that you would do manually yourself, either as a learner or an Admin, such as tagging training materials included in courses and the social learning assets that you contribute to the Discover, Coach & Share module, or suggesting which courses are most relevant for learners.
The concept is simple: We use specialized algorithms to safely and securely analyze nearly all of the different types of content that you’re adding to your platform and how you’re using the platform, and find ways to enhance and simplify the learner or Admin experience.
What do I need to know about how Docebo uses and/or stores the data used in algorithms?
The content and data that are analyzed and used in Docebo’s Artificial Intelligence algorithms are used only for the purpose of enhancing the learning or Admin experience in your specific platform, and all data is anonymized. Docebo does not share or sell any data used for these algorithms, and the artificial intelligence used in the platform is GDPR compliant.
Data is not shared from learner-to-learner, from learner-to-Superadmin (and vice-versa), nor from your platform to Docebo staff.
Where can I find AI features in my platform?
The list below is an updated outline of where you’ll find AI-powered features in your Docebo platform:
Virtual Coach
The Docebo Virtual Coach, powered by Artificial Intelligence, provides learners with a unique learning experience through conversations. It’s a proactive learning coach for every single user in your platform, who can guide and steer them continuously through their learning activities and work within the learning platform. Learners can interact with their Virtual Coach directly on the desktop platform or in the Go.Learn mobile app. The Virtual Coach speaks English, Italian and French at the moment, and it is focused on improving the experiences of learners in your platform. Therefore, it doesn’t focus on or assist in any Admin functionalities or operations. More details on:
AI-Powered Deep Search
Docebo’s AI analyzes learning content of any nature, understanding its content and using that content to exponentially improve learning content discoverability with the platform’s search feature. Upon sharing a new learning asset or creating new training material, AI analyzes the asset to produce search results that are more relevant. For example, a video is searched and discovered by its spoken content to produce much more effective learning experiences by putting content that the learners want in front of them more easily and more effectively. Learn more about the search engine in your platform.
Auto-Tagging
AI analyzes learning assets (formal and informal), identifying key phrases and creating tags for the assets automatically. This helps make content easier to find using the deep search mentioned above. For example, upon sharing a video as a new learning asset, AI “listens” to the entire video, understands its key phrases, and it generates up to 10 suggested tags for the learning asset uploader in order to help with content categorization and search. Tags can also be manually edited if necessary, and, given the stochastic nature of the language understanding algorithms used in auto-tagging, human supervision of the suggested tags is recommended. You can disable the auto-tagging feature in your platform’s Advanced Settings. Learn more about creating and sharing formal content and informal content in your platform.
Docebo’s AI needs a minimum number of words (16 words) to process to be able to compute tags, and that, for security reasons, auto-tagging is not performed on private content (that is, content requiring authentication to be accessed). When uploading private content, we suggest you add tags manually. Please note that only Superadmins and experts can add tags manually when uploading an informal asset, while users can add or edit manual tags only once the asset has been published.
The auto-tagging feature may encounter problems when processing SCORM and XAPI training material created through the use of certain authoring tools embedding textual contents directly into programming files, and compressing images so that their quality does not allow Optical Character Recognition (OCR). We are currently working to confront this limitation by collaborating with some of the major authoring tools providers.
Skill-Tagging
Artificial Intelligence analyzes learning content as it is uploaded to your platform, identifying automatically what skills from the Skills Catalog are most relevant for each content, and immediately proposing them to you as you complete the upload process. You can pick and choose from the skills proposed by Artificial Intelligence, and you can also enter your skills manually. This makes adding skills to your content easier and more consistent. Remember that the skills listed in the Docebo Catalog are in English only. You can disable the automatic association of content with skills in your platform’s Advanced Settings.
Personalized Suggestions
There are several places within your learning platform in which the AI will provide personalized suggestions on training materials, courtesy of our recommendation systems. Suggestions also come in a variety of flavors: below there are details on the major applications of our recommendation system. More details on the principles and the criteria used by our current recommendation system to produce suggestions.
- Invite-To-Watch Invite-to-Watch elevates the social learning experience by making it simple to share content with peers. When a learner shares an asset in Discover, Coach & Share and wants to invite a specific audience to watch that asset, AI suggests the employees who would benefit most from it. Learn more about this feature. Also note that some other considerations apply, such as the rules of visibility of users for the content being watched.
- Enrollment Suggestions for Admins: Admins will see an AI-suggested list of learners when enrolling them into a course, so they spend less time searching and brainstorming which users will benefit most from the course.
- Formal Content Suggestions for Managers: Managers can see suggestions for courses in which they should enroll their team members from the My Team area of the platform, allowing them to continue their learning journey without Admin intervention.
- Next Content Suggestions for Learners: Learners are provided with accurate informal content suggestions that their colleagues are contributing in the platform when they’re already watching an asset so that they can focus on relevant content that creates an individualized learning experience. Learn more about Discover, Coach & Share.
Which languages are supported by Docebo AI algorithms?
Most of Docebo’s AI features (including the deep platform search) work with our available product languages. However, the auto-tagging feature works only for English, Spanish, French, German, Italian and Portuguese content at the moment, but there is full intention to add support for a number of other platform languages for these features over time. We will roll out these capabilities for other languages, together with incremental enhancements and maintenance of all AI functionality. Keep an eye on the Product Update page (opens in a new tab) for more information in the future.
Best Practices on Audio and Video for Auto-Tagging
The auto-tagging algorithm can extract tags also from any spoken audio of multimedia learning contents (both formal and informal) that you upload on your platform. However, there are some best practices for the correct interpretation of spoken audio by the state-of-the-art speech-recognition technology the company relies on:
- there are no significant background noises that could cover the spoken audio
- there is no or very little overlap between the speakers (in the event that more speakers speak)
- the spoken audio language is the same throughout the course of the recording
- a very strong speaker accent can lead to less precision
An audio track with any of the above characteristics extends the ability of speech recognition and comprehension technology to clearly distinguish spoken words and turn them into text, on which the automatic encoding algorithm operates. In these cases, the suggested tags produced through auto-tagging may be poor, irrelevant, or non-existent.