AI in Digital Learning: Benefits, Applications and Challenges

29 September

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AI in Digital Learning: Benefits, Applications and Challenges

When considering artificial intelligence being used in a learning context, images of robots teaching a class may come to mind. However, there is no need to worry about robots taking your job anytime soon. In fact, there are actually many ways that artificial intelligence can make your job easier – and also create a better experience for learners.

In this article, we’ll cover what artificial intelligence is, the benefits of artificial intelligence, how it is being used in digital learning and some of the challenges associated with this technology. 

What is artificial intelligence?

Artificial intelligence, or AI, involves using computer systems to mimic tasks that are normally associated with human intelligence. Some examples of these tasks include decision-making, speech recognition, problem-solving, pattern recognition and self-learning. 

One subset of AI that is particularly prevalent within digital learning is called machine learning. This is a concept that describes the ability for computers to learn and improve without programming. One reason machine learning has been so valuable in digital learning is its ability to analyse and make predictions from large sets of data.

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Benefits of AI in digital learning

AI has transformed the world of digital learning and will continue to do so as the technologies further advance. But why exactly is AI such a secret weapon when it comes to eLearning? We dive into five of the top benefits of AI below:

Personalised learning

One of the main advantages of using AI in digital learning is having the ability to more effectively and efficiently personalise learning experiences. AI-powered technology can create tailored learning experiences in a way that an instructor would never have the time to be able to. This technology can create personalised learning paths, curate and recommend content and address knowledge gaps or difficulties. In turn, this personalisation helps create a better learner experience and also improve the learning outcomes.

Save time

A further benefit of AI in digital learning is the amount of time it can save for instructors and other digital learning professionals. In a traditional learning environment, instructors previously had to spend hours arduously grading exams and answering student queries. But with AI, these tedious tasks are able to be automated. AI-powered tools can grade assessments, recognise and intervene if learners are struggling, and answer common learner queries with chatbots.

Greater insights

We’re currently living in the Age of Big Data. And this increased access to extensive data has touched nearly every industry – including digital learning. As we previously mentioned, machine learning has created even further opportunities to benefit from data. This AI-driven data analysis method involves computers essentially learning from data patterns. Because of the ability to make predictions about future learning outcomes and learners’ needs, machine learning has become an invaluable tool within digital learning.


One of the most profound benefits of AI in digital learning is the impact that it has on making learning more accessible. With translation tools, chatbots and tools that provide descriptions of visual content, AI is making learning more accessible for neurodivergent learners, and those with hearing or visual impairments. However, AI isn’t only making learning more accessible for learners with differing needs, but also learners in different locations. AI makes it possible to learn from wherever you are in the world, without having to enter a classroom.

Improved learner experience

It’s well known that emotions play an important role in the ability to learn and retain knowledge. Therefore, it’s vital to ensure that learners are motivated, engaged, and overall have a positive learning experience. And AI-powered tools can contribute greatly to the enhancement of the learning environment. With content personalised to learners’ needs and the ability to get assessment scores and answers to questions quicker than ever, learners benefit from an overall improved experience.

Ways AI is used in digital learning

Now that we’ve covered what AI is and why it is so beneficial in digital learning, you’re probably wondering how you leverage the power of AI in your education or training programs. Below we look at four ways that AI is currently being applied within digital learning:

Knowledge curation

Previously, instructors and other L&D and education professionals had to curate content by hand. However, AI has completely transformed the process of content curation. Depending on the tool, either learning platform administrators or learners themselves can choose topics that they are interested in and let AI-powered tools do the work for them of curating relevant courses, content and knowledge. 

Many tools don’t even require that learners input topics they are interested in. Rather, AI machine learning has the power to predict their interests and create personalised content recommendations based on the data. One example of an AI-powered content curation tool is Anders Pink. This tool uses AI technology to scour the web for the most relevant content based on learners’ interests. This way, L&D teams can save time by letting AI do the work for them.

Natural language processing

Natural language processing, or NLP, is a type of AI technology that uses algorithms to detect, analyse, model and translate human language. Two well-known examples of NLP virtual assistants are Apple’s Siri, and Amazon’s Alexa. However, these types of technologies are not only used to make our lives easier, but also our learning experiences better as well. And NLPs in the form of voice-based virtual assistants are becoming more and more common within the context of digital learning. Some common uses are providing technical or user support, facilitating onboarding, signposting learners, and reinforcing learning.


One of the most popular applications of AI in digital learning is chatbots, which is a type of technology that simulates human conversation through the use of computers. Chatbots have become so advanced that oftentimes users are not even aware they are communicating with a computer and not a real person. One well-known case of this happened at Georgia Tech, when a professor built a chatbot that students believed to be a real teaching assistant. One benefit of using chatbots in digital learning is that students can receive consistent and instantaneous information. This saves time for digital learning professionals as well, as it reduces the amount of queries they have to answer.


Predictive analytics, which are a type of AI, have become hugely valuable in the world of digital learning. One common use of predictive analytics is automating “nudges” to be sent, which are triggered by learner data. This is based on the nudge theory, which proposes that gently encouraging people to make certain decisions will influence their behaviour. And within eLearning, it is used as a tool to motivate learners and improve outcomes. One case study of an initiative involving AI-powered nudging was done at the University of Maryland, Baltimore County. The program, titled “Nudging Students to Success” involved building a predictive analytics model to influence student behaviour.

Challenges of AI in digital learning

Although AI has generally been a positive force within digital learning, there is still a lot unknown about how effective its application is for digital learning. As with many novel technologies, it does come with some challenges and has not escaped some myths being created about its impact. We’ll look at three of the main challenges of AI in digital learning.


One challenge of AI in digital learning revolves around the ethical and transparent use of data. As AI-driven machine learning algorithms operate by using learner data, this has raised concerns around data storage and protection. Another ethical issue associated with AI in digital learning is the fallibility. Since machine learning intelligence is based on pattern recognition, it lacks the discernment of human intelligence. Therefore, there is a risk that AI could unfairly discriminate or make inappropriate recommendations. For this reason, the ethics around accountability and liability are another challenge that must be addressed.

Skills gaps

Although many AI-powered digital learning tools are relatively user-friendly and don’t require specialised skills, they are nevertheless a new type of technology that may require training and onboarding to use. Therefore, one challenge of AI in digital learning is equipping teachers, course facilitators, and L&D teams with the knowledge to leverage the most benefit from AI. 

As some professionals may be apprehensive of these novel types of technologies, an effective approach to change management is helping them to understand the time-saving benefits that can come from tools, such as chatbots and task automation. 

Data system capabilities

L&D teams within corporations may already have access to sufficient employee data for AI processes. However, when it comes to gathering data for public education purposes, this can be much more challenging. Since you’re dealing with larger data sets and inconsistent procurement, this makes it difficult for AI technologies that rely on data to function. So when it comes to reaping the most benefit for decentralised education systems, this is still an ongoing challenge. 

Final thoughts about AI in Digital Learning

AI is the way of the future. This technology has already transformed a wide range of industries, with digital learning included. However, while AI can offer so many benefits for training and education, it does not come without challenges as well. Therefore, it’s important that digital learning professionals inform themselves about both the advantages and pitfalls of AI.

To learn more about how AI is used in digital learning, a Professional Diploma in Digital Learning Design can provide you the fundamental knowledge you need to better understand and leverage this technology in your learning programs.

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