Implementing AI in Learning – 3 Low-hanging Fruits to Start with
Artificial intelligence (AI) is one of the technologies that is going to fundamentally change learning. With applications from content curation to predictive analytics, AI applications provide powerful tools for making learning more efficient. However, with such a wide range of applications and use cases comes ambiguity. For many L&D and HR professionals who are not domain experts in AI, it may be hard to grasp all the potential. Furthermore, figuring out whether and how to get started with AI can be troublesome. Hence, we’ve compiled 3 different value-add cases for AI in learning.
1. Using AI in learning management to eliminate manual work
When delivering digital learning, one of the least productive and most menial of tasks is the learning management. Professionals use the digital learning environment, or an older LMS, to manage and assign courses, materials and produce reports. Naturally, this is work that needs to be done, but is very menial and repetitive in nature. In terms of productivity, the work is low value-add.
Luckily, machine learning and artificial intelligence can and will eventually take over practically all of this work. This will free the learning professionals from a time-consuming but unproductive load of work. Hence, they are able to focus on designing and delivering the learning, which is the true value-add part. Furthermore, AI is also very likely to outperform people in tasks like this – there’s less room for human error and the computer doesn’t forget. Such using of technology to automate repetitive tasks should be the first application of AI in learning for every organisation.
2. AI in Learning and performance support chatbots
Many organisations have embraced AI when it comes to chatbot applications. Smart chatbots based on AI can provide personalised and customised suggestions to user inquiries. These form an easy tool for on-demand learning and performance support. The users can get answers to their queries quickly, resulting in minimal downtime and better productivity. Think of it as an advanced interactive search engine. There’s no need to go through lengthy documents, manuals or guidebooks. The chatbot is able to pool from the organisation’s knowledge, the previous users and best practices to provide answers in a blink of an eye. Whatever the problem, the machine can likely provide good suggestions as long as it has been exposed to relevant data.
Read more about using chats and chatbots in learning here.
3. Using AI to personalise learning for every employee
Finally, a third use case of AI in learning is to provide personalised learning experiences, as well as designing adaptive learning. AI can collect data, analyse and learn from human behaviour far beyond the human ability. If our learners are having problems with the content, AI detects it, and offers them another set of material with different modalities or difficulty. Furthermore, the AI can suggest additional resources complementing the learner’s existing skill-set. Delivery of content will then be in formats that the AI has detected to be most efficient for the learner (videos, simulations etc.). This improves learning engagement and yields better learning results.
Naturally, AI will have many more applications as the technology develops. However, you can already take advantage of it to eliminate manual work and provide better learning experiences.
Do you want to understand the functionality of AI in learning better? Are you looking to implement AI in your organisation’s L&D? We can help you get started, just contact us here.