Potential applications of AI in education and e-learning
Currently, we actively use AI in eLearning, but mainly develop educational content development, image creation, image generation, error text checking, exercise design, and more. However, the main possibility of AI in learning lies in integration into educational materials. This article explains examples of AI integration applications. What’s very important is that almost every example on this list can be implemented by an in-house e-learning team. No advanced programming skills and large budgets are required.
6AI application in learning
1. Check free answers
One of the basic applications of AI in learning is to check answers to open-ended questions, analyze texts, and evaluate case studies. Take a smart course as an example (honestly, everyone probably developed it dozens of times). Currently, I am assessing my knowledge through quizzes. The four tasks developed are as follows: Which matches Smart? Or: Here’s the description of a particular task – what’s wrong with that? There may be matching and drag and drop tasks, but in the end it’s just a quiz with different mechanisms.
Example 1
Here is an example of a typical smart exercise:
For example, users have a question. “Check your goal setting for smart standards compliance and determine which criteria are missing. Increase your level of customer satisfaction with your support services in 2025.” Then there are several answer options available.
A. Specificity
B. Measurability
C. Achievability
D. Timebound
Using AI, you can transform quizzes into exercises that help learners understand the material and develop their skills, as well as not only test their knowledge.
Example 2
Here is an example of a smart goal setting exercise using AI:
The user receives the task. “You are the manager and you will be attending the meeting on July 5th to give a speech. You will need to assign a task to designer Alex and create a presentation on the topic “Smart Learning.” You already have the script. “The user then enters a response at will and explains how to assign tasks.
“Alex gives a presentation on the topic of “smart learning.” “The AI then provides feedback on this response, highlighting all the pros and cons. The manager enters the method for setting up the task in the text field. Next, AI points out the mistake. At the same time, you can customize how AI responds. Do you want AI to simply provide correct answers and highlight errors? no problem. Do you want AI to ask guide questions so that employees can correctly redefine their tasks? easy. Do you want employees to get a new practice scenario each time? AI can generate fresh cases on the spot.
Similar exercises can be performed to review case studies. This can be done whether you are interested in employee thought processes and reasoning or if you don’t have a clear “correct” answer.
Incidentally, how long does this particular exercise take to the market? 10 minutes. This includes three minutes to upload your bot and three minutes to spend on avatar selection.
2. Course Q&A Support
I use this myself a lot. If you read something and don’t fully understand it, “interrogate” the AI to get a clearer explanation. For general topics (such as smart goals), ChatGpt works well. Handle them completely. However, ChatGPT is lacking when it comes to internal company content (policies, regulations) or niche subjects (AML/CFT, specialized software). I just don’t know the answer to a particular question.
So, why are you worried about integrating AI into your course when you can ask ChatGpt?
ChatGpt doesn’t know internal policy
However, the AI linked to the course is preloaded with course material, so it is based on that answer. Seamless integration
Building this feature directly into the course is very useful.
How employees currently search for explanations in AI
If employees don’t understand something in the corporate course, here are some things they have to do:
Get your smartphone (usually because work computers block ChatGPT and other AI tools). Open the AI platform. Enter your question (which may be long) on a small screen. Read the response on the same small display. Ask follow-up questions if necessary.
And it assumes they are already comfortable using AI. What if they’re not regular users? They don’t care. Even so, the process is too tedious. The more steps required, the fewer people will complete the action. However, they want employees to independently clarify misunderstandings. Simplifying this path dramatically increases engagement.
Moreover, AI can do more than simply answer:
Leads learners to relevant course sections. Save and analyze data.
Collect and analyze user questions by embedding AI directly into the course. This shows precisely what is unclear and can improve future iterations.
3. Conversation Simulator
Three years ago I built an MVP for a mobile service sales simulator. Speak loudly with AI that plays the role of a customer. The dialogue is non-linear. You will pilot the conversation and finally get feedback. The results were fascinating. The simulator really improves your sales skills as AI behaves like a real customer.
4. Specialized narrow tasks
AI is not limited to text or speech checking (like the Dialogue Simulator example) – you can analyze anything.
Excel report accuracy. Code quality. Public speaking recording. Tone of expression and voice.
Technically, this is more complicated than the previous example (although Excel reports are relatively simple), but it is completely feasible. Tools for this already exist.
5. AI-powered knowledge base search
Every large company has a vast knowledge base filled with essential information: files, forms and documents. The only drawback? Try to find something there. Even if you find the right documentation, you will still need to skim the pages to get answers.
AI can solve this. Find the correct file and extract the exact answer to the query. This is technically challenging. Implementation can require IT support and a significant budget.
6. AI Mentor
These are bots that employees know everything they need for their job. They help with tasks and learning. Instead of passively waiting for questions, tweak employees quickly.
It sounds amazing, but now it feels like a utopia. why?
The system is overly complex and most processes are uncontrollable. Development and updates require a lot of resources (it requires daily adjustments as the system “knows everything”). There is a high risk of malfunction.
Conclusion
AI unlocks the whole new possibilities of e-learning. It’s an application that goes far beyond content generation. key? Don’t wait for the “perfect” moment. Start the experiment now. As the example of smart exercises shows, some solutions take just 10 minutes to implement. The sooner you start, the faster the results will be. The technology is already here. All that remains is to start using it.
Editor’s Note: The views expressed in this article reflect the author’s personal opinions and are not intended to represent Eli’s perspective. If you want to learn more about AI integration, check out our list of top LMS platforms with the best AI tools for training and education.
