With the introduction of AI technologies, learning management systems will be able to provide feedback on each learner’s individual needs along with the collective needs of the organization. This essentially means AI can help with training needs analysis across the company, a process that a business goes through in order to determine all the training that needs to be accomplished in a given period to allow them to complete the job as effectively as possible, while growing continuously.
Imagine a large machine churning data at a macro level about employee skills and goals of the organization. Based on the analysis of this highly dynamic and detailed data, the skills gap can be addressed by the company to reach from where it is to where it wants to be. If a company wants to increase its turnover by 30%, what levels of training is required to increase productivity, can be recommended with AI-powered, data-driven solutions.
AI-backed solutions are quietly crunching data in the background to provide insights on improving productivity. They also help to create smart content required for training needs, based on employee demographics, preferences and characteristics. An employee can experience customized learning content, and depending on his/her interaction with it, AI will help adjust future content as well. It will make suggestions for additional training or how existing programs can be altered for greater usage and applicability.
Moreover, AI simplifies the complex task of creating meaningful lessons for instructional designers and trainers who can now focus on progression through a streamlined learning map and can design content accordingly for optimal impact. Content development / ID tools such as Articulate, Captivate, Camtasia, etc. can be integrated with AI modules or plugins that assist an ID developer with creating better content. AI can suggest relevant content like templates, storyboards, graphic elements, text arrangements and more.
Additionally, Machine learning (a subset of AI) can help training programs assess which type of content each student responds to the best. If a student learns best from video content, they will have more video-based content. If they respond better to text, they’ll see more related articles. If they absorb information from audio files, they will get those. This can lead to stronger content creation and improved outcomes, thanks to the AI-based, data-driven approach to learn what content elements are most effective.
- Posted Date: 04-MAR-2020