Understanding the Limitations of AI for L&D Professionals

According to research highlighted in MIT Sloan Management Review, 85% of executives believe that artificial intelligence (AI) will help them sustain or obtain a competitive advantage. But, less than 39% of companies have an AI strategy in place, including AI for learning and development (L&D) platforms.


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Can this be due to some of the limitations that AI poses for L&D professionals and initiatives? The answer is yes. While AI can propel an organization’s L&D department forward and make it more competitive, it does have limitations that need to be weighed before it’s implemented. Below are a couple of them.

AI L&D Strategies and Systems Are Still Initiated by Humans

While learning management systems (LMS) are now being powered by machine learning and AI, they still need to be managed and initiated by real-life humans. L&D professionals are still responsible for acquiring the appropriate tools and systems for their organizations, understanding their different machine learning options, and understanding how they want these AI-powered systems and platforms to be programmed and managed. And they can still initiate systems that aren’t built with their specific users or organizations in mind, making them more trouble than they’re worth.
In addition, L&D professionals will still be responsible for developing and deploying different types of content and content flows via their AI-powered systems. So, even if they acquire the right systems and implement them properly, the systems themselves may still not do much if the learning content available in them isn’t relevant, high quality, and readily available.
Read “How to Use AI to Drive a Great Experience for Your Learners,” Part 1 and Part 2, for more information.  

AI Systems Still Need to Be Continually Monitored by Humans

L&D professionals still need to ensure their AI systems continue to function as they should and must constantly monitor them. Essentially, they need to continually work to train their AI-powered systems to train their employees.
AI-powered systems should still be flexible and should be properly programmed to understand natural language and queries and adapt accordingly. And they should always be utilizing machine learning to better their system performance, as well as the performance of the employees who are using them.
Read “What You Need to Know to Train Your AI to Train Your Employees” for more information.
Overall, while AI-powered systems can help L&D professionals propel their organizations forward, they also need to be properly implemented and continually managed if they’re to truly have a positive impact.

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