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How to use Artificial Intelligence to improve your training

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Find out how ReFrame Learning incorporates elements of artificial intelligence into corporate learning processes.

Now that we have a comprehensive understanding of the impact of Artificial Intelligence on the L&D market and corporate learning programs, it’s time to dive to learn how ReFrame Learning does this in practice, making AI a faithful ally of the strategy of organizational and people development programs, and not a mere element to support communication and offer content to participants.

Renato Gangoni, CEO of ReFrame, says that, although the recent advances in tools such as ChatGPT and Bard are admirable and can offer support to L&D and education professionals in general in the elaboration of contents, programs, scripts, and much more, what is most fascinating about the application of AI in L&D are the countless possibilities for using algorithms in the design of strategies for learning processes.

“I was recently in a meeting with a company that cannot visualize people’s performance level at a granular level. It can visualize macro indexes, such as billing, for example. However, it cannot visualize product sales by region. But I can have access to enough data to say the following: ‘In such a city (or region of the city), you may train or may not train because the data shows me a causal relationship between the performance of that unit and the performance of the people'”, tells Renato.

Does training solve this exact problem?

As we also discussed in the article “The right time to invest in training”, we can now say that Artificial Intelligence can help us answer one of the fundamental questions of all L&D diagnosis planning: is this a challenge that can be solved with training?

This happens because all the work of processing data and establishing correlations between the available indicators and information (data from the training area, performance data, and business KPIs) can be carried out with a high degree of accuracy using the right AI tools. That is, as we saw at the beginning of our entire journey to understand how ReFrame Learning plans its training using the Learning Analytics methodology, now it’s time to validate the established assumptions and understand whether it is worth investing in training, who should be trained and which skills should be improved.

All this data crossing is done with the help of AI, which offers us the possibility of predicting the impact of training actions on that specific audience within that given context. All this with statistical models and probabilities that offer a high level of assertiveness, in terms of the allocation of resources and investments.

Another very promising possibility of AI applied to training plans and strategies lies in the case of running virtual A-B tests, without the need to mobilize personnel to validate assumptions. Thus, you can generate fictitious scenarios and possibilities before you even start producing any type of content.

And none of this is part of a science fiction story.

ReFrame Learning already has projects running within these mathematical models and with the use of Artificial Intelligence during training planning (and delivery).

Of course, there are still challenges to overcome, especially when we talk about the handling and traffic of the necessary data so that the full potential of AI applied to learning processes is achieved, but it is undeniable that everything that is already happening will change the landscape of the L&D market.



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