7 key uses of AI in digital learning

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Rachel Sweeney, Marketing Executive

Mention Artificial Intelligence (AI) and we tend to think of robots or giant computers. AI, though, is a feature in many of the apps and devices we use every day and it’s making an impact on the way we learn.

AI is all around us

Receive an email recommending something you’d like to watch on Netflix. See a list of things you might also like to buy on Amazon. Use the chat on a website to get help. Search Google. Ask Alexa. Book an Uber. All these actions rely on AI. It’s been estimated that 80% of emerging technology will be founded on AI.

A quick guide to how AI works

AI works by gathering and interpreting data. It recognizes natural language requests, so you don’t need to program it.  It’s good at identifying patterns in that data and based on algorithms it makes recommendations and takes actions.

Digital learning is increasingly harnessing the power of AI to make training more efficient and effective. Let’s see how.

7 key uses of AI in digital learning

1. Personalized recommendations: AI can analyze employees’ profiles and experiences based on their choices and interactions with learning content.  From that data, the system can derive their preferred style of learning, their learning behavior, and their learning trajectory. It can then make recommendations about future choices and behaviors: which courses to do next, which resources are suitable, whether and when to refresh their knowledge, and when to do an assessment or go for an award.

2. Adaptive content: The personalization that AI allows it to deliver content directly tailored to an individual learner’s needs. In adaptive learning systems that use AI, personalized content is delivered dynamically and in real-time. AI-based analysis into the experience, prior knowledge, and skills gaps of learners are used to build individualized learning pathways and make learning more relevant.

3. Microlearning: AI can be used to break up content into smaller chunks. It can then deliver these microlearning resources based on its understanding of learning needs and learner requests. This means learning resources can be delivered in a timelier way at the point they’re required. It gives greater flexibility to your learning program and creates a bank of helpful resources.

4. Advanced analytics: AI gathers and devours huge amounts of data. This gives L&D a far more granular view of learner behavior and needs. This data can be easily queried, aggregated, outputted in reports, and displayed on dashboards.  Analytics allows for more informed decisions on what’s working and what isn’t, where skills gaps lie, and where intervention is required, either at a group or individual level. This saves L&D time, gives it greater focus, and shows where it can add the greatest value.

5. Automation: AI enables the automation of routine L&D tasks.  These include the enrolment of learners, the grading of assessments, document management, accreditation, and certification.  Automatically generated notifications and reminders keep learners on track to ensure engagement and compliance.  AI can automate admin tasks in online onboarding.  Increased automation frees up L&D to work on higher-order tasks.

6. Chatbots: Learning platforms increasingly include chatbots, a virtual assistant that responds to requests through either text or speech.  At their simplest chatbots offer an enhanced search function to allow learners to find learning content and information directly without navigating through pages of material or whole courses. But AI-powered virtual assistants can do more because they learn from each interaction and build a profile of the learner by detecting preferences.

With this knowledge, they can make personalized recommendations and fulfill the role of a guide or mentor offering instant, real-time interaction. Virtual assistance is accessible across devices, removing the need for learners to take time out to contact an instructor and wait for a response.

7. Enhanced learning platforms: New-generation LMSs and LXPs use these AI features to create adaptive and dynamic learning. AI gives learners the tools to create their own learning paths and programs that better reflect their needs and are more relevant to their experience, role, and development. Using AI to surface content and resources more efficiently, these learning platforms deliver a more learner-centric, responsive, and engaging learner experience.

AI keeps working

Using AI in digital learning changes the dynamic of learning.  It puts learners in control and brings learning closer to work.  It frees up time for better L&D.  It provides better insight into skills gaps and increases your options on how to fill them.  It gives you the data to know what works and what doesn’t.

What’s more, AI systems learn and get more efficient with each interaction. AI creates a virtuous circle: the more you use it, the better the results.