Totara – our approach to AI
Totara and our Partner network are here to support your organisation’s AI strategy
AI presents L&D and HR with endless opportunities to enable efficiencies and smarter ways of working. From voice-activated chatbots that train (& assess) staff in soft-skill scenarios, to streamlined content creation and advanced personalised learner experiences, there are endless use cases.
The rapid rise of generative AI is now progressing beyond trade-show discussions – organisation’s require a cohesive AI strategy to maintain a competitive edge.
Totara’s LMS has been using machine learning to personalise the learner experience for years, and with the launch of our Open AI integration, we’re opening the door to an exciting new world where generative AI can query content and data hosted within Totara’s LMS.
Machine-Learning recommendations
Totara’s OpenAI Integration
A framework that evolves with you
Revolutionise your learning strategy using AI in your LMS
By incorporating generative AI into your LMS, you can:
- Deliver personalised learning at scale: Automatically curate and recommend content tailored to each learner’s preferences, skill level, and learning objectives.
- Individualised tutoring and coaching: Empower learners with AI-driven tutoring solutions that provide instant, customised feedback and one-to-one coaching.
- Boost efficiency and reduce workload: Automate time-consuming administrative tasks, such as content tagging and data enrichment, saving valuable time.
- Engage learners like never before: Provide learners with interactive, AI-assisted experiences that keep them motivated and immersed in their learning journey.
Totara’s approach to human-centric AI
Our core principles are here to ensure that a human-centric approach is at the heart of how AI is used within your Totara LMS.
AI offers incredible opportunities to drive L&D efficiencies and offer exceptional, personalised learning experiences. However, we acknowledge the technology is both new and rapidly evolving, and so ethical application and respecting privacy is key.
What do we mean by a human-centric approach to AI?
Transparency
AI-generated content is clearly labelled to the user.
Auditable
Records of use are logged and auditable.
Relevant
Human verification is required (for example, approval of suggested course tags is needed).
Compliant
Data protection is key – personally identifiable information (PII) is off-limits.
Purposeful
AI plugins and Integrations have restricted access to approved data sets and content within Totara.
Inclusive
We encourage all our partners to consider bias when testing their AI solutions.
Totara’s innovative Partner network delivers tailor-made AI solutions
Our extensive network of 75+ LMS specialists build and deploy tailor made solutions to your exact requirements.
Totara’s highly adaptable architecture allows limitless customisation and access to thousands of plugins and endless integrations that span both learning and business ecosystems.
So whatever tools, platforms, or systems you’re using to develop your AI strategy, Totara’s LMS is here to support it. With AI technology rapidly evolving, Totara has the flexibility and power to adapt with you, as your AI strategy evolves.
From chatbots that assess your interactions on voice-driven scenarios, to everyday time-savers such as course and content tagging, you dream it, our partners build it.
Looking for a partner to bring your AI strategy to life?
What does AI in an LMS look like?
For more inspiration, catch this webinar clip that shows how MaibornWolff and Totara’s Platinum Partner LearnChamp are developing an AI Learning Assistant that sits within Totara.
Totara’s Open AI Integration
Totara’s OpenAI Integration launched in version 18.8 of Totara. This LLM integration model provides a simple option to connect a Totara site with OpenAI’s products such as ChatGPT.
With this integration, and the supporting pluggable architecture, Partners can develop custom plugins that enable AI functionality to work within Totara sites.
In practice, this means that chatbots can access specific data sets within Totara, such as course content and metadata, support documents etc. These chatbots can then be tested and trained on this content to ensure the end result – in this example an interactive chatbot on the specified content – will meaningfully benefit the learners.
As per our principles highlighted above, limited and only pre-approved data sets within Totara can be accessed, and Personally Identifiable Information will not be accessed or retrievable.
Note that Totara’s scalable architecture allows integrations with other Large Language Model (LLM) providers to be built, such as Llama, Anthropic, and Gemini.
Totara’s AI-assisted Course Tag Recommendations generator
In this example, the LLM processor (ChatGPT) has been given access to fields such as Course Title, Course Description, as well as previously-generated Course Tags from the course content catalogue.
The AI assistant suggests to the course administrator tags that could be relevant. The user can choose to ‘regenerate tags’ if no suitable options are presented, which then suggest new tags.
Totara’s Machine Learning recommendation engine
Totara’s LMS uses the power of machine learning to recommend a blend of learning (from formal learning such as courses to social learning) that fits into the flow of everyday work.
We continually refine our machine learning methodologies to serve up personalised recommendations based on factors such as existing learner profiles, actions, trending and recently viewed content.
Trending
The most viewed courses, resources and playlists based on user interaction over the last few days
Micro-learning
Resources recommended to the active user with a read or watch time of less than five minutes
Courses
Courses recommended to the active user
Workspaces
Workspaces recommended to the active user
Using AI in an LMS – Frequently Asked Questions
I’m an existing Totara customer and am interested in using the Open AI Integration. What are my next steps?
Is the Open AI Integration available for TotaraGov customers?
Can I learn more about Totara’s AI Course Tag recommendation solution?
You can enable and use AI tag recommendations for courses. This feature uses a Totara integration with OpenAI to recommend tags to add to each course, based on the information included within that course. This tool will only suggest existing tags, and will not create new ones. If you have tags in multiple languages, this tool will only suggest tags in the user’s preferred language.
Note this feature requires an OpenAI API account.
For more information on implementing this feature see our help guide.
What are the costs associated with using AI within Totara?
This will depend on which LLM service you use. Most LLM services used at an organisational level will have a charge for their service. As such, when your LLM processor access and runs your AI solution within Totara, there will be a cost associated. You’ll need to check the terms of your LLM provider to understand what these costs are.
Note that as integrating AI solutions within Totara involves customised work to build, test and deploy within Totara, you should consult with your partner to understand these costs.
What AI integrations are available?
Totara’s highly configurable architecture means integrations can be built or customised for almost any service. In addition to the Open AI offering, integrations can be made for other LLM providers such as Llama, Anthropic, and Gemini.
You can also explore AI integration options available through Workato.
Please get in touch with your partner, or contact us to find out more.
What are the use cases for AI in an LMS?
The use cases for integrating AI to support your L&D strategy are vast, and can be tailored to specific organisation needs. Common use cases include:
Deliver personalised learning at scale: Automatically curate and recommend content tailored to each learner’s preferences, skill level, and learning objectives.
tutoring and coaching: Empower learners with AI-driven tutoring solutions that provide instant, customised feedback and one-to-one coaching.
Boost efficiency and reduce workload: Automate time-consuming administrative tasks, such as content tagging and data enrichment, saving valuable time.
Engage learners: Provide learners with interactive, AI-assisted experiences that keep them motivated and immersed in their learning journey.
Is my data safe when using AI tools?
Yes, absolutely. As described in ‘our AI principles’ section on this page above, AI integrations within Totara only access the data and content prescribed by our customers, and never include Personally Identifiable Information.
Totara has integrated AI and Machine Learning (ML) technologies in several areas to enhance user experience and streamline content discovery. These features are designed to be opt-in, giving customers full control over their use.
The AI Course Tag Recommendations feature uses machine learning to suggest relevant tags for courses, enabling easier categorisation and discovery of content. This feature is powered by a third-party provider, specifically OpenAI, and involves processing data externally. The AI system analyses course titles and course descriptions to generate appropriate tag suggestions. This feature is opt-in and requires the use of the customer’s own OpenAI API account, allowing customers to decide whether they want to enable external data processing.
For more information, visit AI Course Tag Recommendations Documentation.
Totara’s Recommendations Engine leverages machine learning to provide personalised content suggestions based on user activity within the Totara platform. Unlike the AI Course Tag feature, the Recommendations Engine processes data entirely within Totara’s environment, ensuring that no external data sharing is involved. The engine analyses patterns and user preferences to offer tailored course and resource suggestions to enhance the learning experience.
For more information, visit How the Recommendations Engine Works.
Opt-In AI Features
Both the AI Course Tag Recommendations and the Recommendations Engine are opt-in features. Customers have the flexibility to activate or deactivate these AI-powered tools depending on their data privacy preferences and needs. This aligns with Totara’s commitment to transparency and user control over AI interactions within the product.
What is Totara’s AI roadmap?
At present Totara’s approach is partner first, enabling customised solutions that are tailored to customer’s exact needs. Our Open AI integration was launched in version 18.8 and is our first step to enabling generative AI within Totara.
We do, however, recognise the demand for native features to be available within Totara’s LMS. Feedback has pointed to AI driven course tutors and enhanced content discovery functionality being desired features.
We are actively exploring what native features we can offer that support our AI principles, with data security being a primary concern.
We are always open to hearing specific feedback on roadmap items you would like to see. You can submit roadmap requests by logging in to your community dashboard. In the menu, access ‘Collaborate’ and then ‘Roadmap and Feature requests’
Does Totara use AI for content recommendations or adaptive learning?
Does the platform use AI to make recommendations based on learners role, location, learning preferences, behaviour, or what other team members are doing?
Yes. These docs outline how recommendations are made. It mostly focuses on what other team
members are doing and how they have interacted with content. We use AI recommendations to ensure that popular content with likes, shares, and active comments are surfaced to other learners.
Can users opt-out of AI based recommendations and data tracking?
We provide different AI/ machine learning models that allow the site owner to decide whether
user’s metadata should be used when conducting recommendations. More info on the different models here: https://totara.help/docs/how-does-the-recommendations-engine-work