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. Yet, less than 39% of companies have an AI strategy in place, including AI for learning and development (L&D) platforms.
Also, according to the same research, there are several misunderstandings regarding how to train AI and what resources and tactics are needed to ensure that it’s properly implemented. Therefore, while it’s evident that AI is important to an organization’s competitive advantage, it isn’t as clear how it (the AI itself) should be executed and trained.
As an L&D professional, you need to train your AI effectively to train your employees with AI-driven technology effectively. And while there aren’t any guidelines set in stone just yet, there are two basic things you need to know right now as you decipher how to train your AI to train your employees.
Your AI Should Be Flexible and Able to Understand Natural Language
A lot of AI algorithms can come pretrained for your L&D platforms with what’s called “supervised learning” so that you can have the AI execute preset outputs and inputs. It will take a lot less time to get up and running and will still give you accurate results and will evolve over time. However, pretrained algorithms aren’t as flexible and may not prove to be ultimately useful.
On the other hand, “unsupervised learning” algorithms can offer a more flexible and customizable learning and training experience for each one of your employees. Because their data sets and classifications aren’t predetermined and fixed, they can mold to the needs and behaviors of your learners.
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It’s also imperative that you search for AI algorithms for your AI-driven learning technology that will be able to execute natural language processing—basically, allowing for it to better understand learners’ search queries and how learners communicate. This way, the AI will better interpret and anticipate each learner’s needs and questions so that it can provide the appropriate answers and resources.
Your AI Should Better Its Own Performance AND the Performance of Its Learners
If you want your AI to train your employees effectively, you’ll need to train it to collect and analyze the right data at the right time for the right reasons on its own. For example, it should know when an employee is not comprehending content within a training module, when certain training materials aren’t resonating with a learner or group of learners and why, when certain training material isn’t yielding positive results, when a learner needs supplemental resources, etc.
You’ll want to train your AI to decipher between a poorly designed course and a learner who isn’t excelling in a course because he or she isn’t engaged with its format or content. This way, you’ll know when you need to redesign a course, distribute content in a different way, or figure out a better way to motivate your learners to engage with the learning content you’ve developed.
Overall, keep this basic information in mind as you dabble in AI-driven learning technology for your organization, and your AI will be set up to effectively train your employees.