Are Learning Professionals Using Artificial Intelligence to Create Training and eLearning?

Many of my learning colleagues on LinkedIn are posting about how artificial intelligence (AI) is the latest and greatest technology to improve learning and I had a good chuckle, as one bold person put out a contentious statement.  She wrote, “I know all of you are talking about how great AI is for training, but is anyone actually using it to develop eLearning.” What had been a lively set of posts about AI being the next biggest technology for learning, all of a sudden stopped.  Although, many people appear to be talking about AI to develop eLearning, few people actually seem to be using it in practice.

I decided to put this question to the test. I asked some of my colleagues if they were using AI to help improve efficiencies in developing eLearning and only two programmers were able to cite real life examples.  One eLearning developer mentioned that they were using it to cite specific stock imagery, as it significantly reduced the amount it took to find the right graphics for eLearning course. The other programmer mentioned they were taking samples of professional audio talent voices, and were able to completely generate audio for entire eLearning courses, using AI to reduce both time and costs.

The use of AI to improve the development of eLearning is reminding me of the adoption of virtual reality for training. Over 5 years ago virtual reality (VR) was supposed to change the face of corporate learning…however it didn’t.  Employees didn’t want to put on large virtual reality googles in front of their colleagues and bosses, and even though the promise of putting learners into real life setting was supposed to guarantee increased learning, people just didn’t want to use VR. Maybe it was because learning departments didn’t understand how to develop modules, where the learner can go anywhere in training.  Maybe it was because they didn’t know understand how to develop virtual reality modules and the technology, or maybe even a more scary prospect would be how to edit a virtual reality module if content changed.  For whatever reason, virtual reality never took off, despite the fact it was supposed to cause an increase in learning and reduce costs, similar to what we are hearing about AI right now.

Although AI appears to be underutilized by training departments currently, here are several ways in which instructional designers and programmers may use AI in the future to increase learning and reduce time and costs.

1. Personalized Learning Paths: AI algorithms can analyze individual learner data, including performance, preferences, and learning styles, to tailor personalized learning paths. By understanding each employee's strengths, weaknesses, and goals, AI can recommend specific courses, modules, or learning materials to optimize learning outcomes.

1. Adaptive Learning Systems: AI-powered adaptive learning systems dynamically adjust the difficulty level and content of training modules based on the learner's progress and proficiency. This ensures that employees are consistently challenged at an appropriate level and receive targeted support in areas where they may be struggling.

1. Content Curation: AI algorithms can analyze vast amounts of learning content, including text, videos, and interactive materials, to curate relevant and engaging content for employees. By leveraging natural language processing (NLP) and machine learning techniques, AI can identify high-quality resources that align with specific learning objectives or job roles.

1. Virtual Assistants and Chatbots: AI-powered virtual assistants and chatbots provide on-demand support and guidance to employees throughout their learning journey. These intelligent agents can answer questions, provide explanations, offer feedback, and facilitate discussions, enhancing the overall learning experience and accessibility of training resources.

1. Predictive Analytics: AI analytics tools can analyze historical training data and employee performance metrics to identify patterns, trends, and insights. By leveraging predictive analytics, organizations can anticipate future learning needs, identify potential skill gaps, and proactively recommend targeted training interventions to improve employee capabilities and productivity.

1. Assessment and Feedback: AI technologies, such as natural language processing (NLP) and sentiment analysis, can automate the assessment of employee responses to quizzes, assignments, and simulations. Additionally, AI algorithms can provide personalized feedback and recommendations for improvement based on the analysis of learner responses, enabling more efficient and effective learning assessment processes.
   

2. Skills Mapping and Gap Analysis: AI-powered skills mapping tools can analyze employee skills profiles, job descriptions, and organizational goals to identify skill gaps and training needs. By leveraging machine learning algorithms, organizations can develop data-driven insights into the current and future skills required for workforce success and strategically align training initiatives to address critical skill gaps.

Overall, AI is revolutionizing corporate learning by enabling personalized, adaptive, and data-driven training experiences that enhance employee engagement, performance, and skill development. As AI technologies continue to evolve, the potential for innovation and transformation in corporate learning will only continue to grow!