Generative AI at the service of training: opportunities and limits

The emergence of generative AI in the world of training marks a decisive turning point: instant generation of content, personalization of courses, interaction with learners... The promise is as attractive as it is ambitious, hinting at a radical transformation of our teaching practices.

However, this technological revolution requires lucid analysis. Between fascinating potentialities and intrinsic limits, how can generative AI in training truly transform corporate learning? That's what we're going to see.

Generative AI: a response to current training challenges

In a world where increasing skills is becoming a strategic issue, generative AI provides an unprecedented response to the challenges of training: the creation of large-scale educational content to support change and continuing education.

Where it used to take several weeks to design an hour of training, AI now makes it possible to drastically speed up this process, freeing up experts to focus on validating and enriching content rather than on its initial production.

Even more fundamentally, generative AI opens the way to personalization that was previously inaccessible. It does not just adapt the pace or the course: it can generate tailor-made examples, offer contextualized exercises and offer detailed feedback that fits the profile of each learner.

This ability to create personalized interactions on a large scale represents a major advance in the democratization of truly effective learning.
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The intrinsic limits of “raw” generative AI

The enthusiasm generated by generative AI should not overshadow its fundamental limitations.

First of these: the reliability of the content produced. While AI excels at reformulating and generating fluid texts, it has no real understanding of the concepts it manipulates. This reality requires constant human supervision, which is particularly critical in a training context where the precision of the information transmitted is crucial.

And so, in most cases, AI is often solved by a waste of time where it was expected to be effective and time-saving (proofreading, looking for errors, etc.)

Even more problematic: the lack of intrinsic pedagogical expertise. A conversation with a language model, no matter how sophisticated, is not structured learning. Without a precise pedagogical framework, without thoughtful progression, without adapted exercises, interaction risks creating a dangerous illusion of control. Effective learning requires much more than simple access to information: it requires a pedagogical architecture designed and validated by experts.

Towards a truly educational AI

Faced with these limitations, the obvious is obvious: “raw” generative AI is not enough. The real revolution lies in the emergence of artificial intelligence specifically designed for learning, a Educational AI which integrates the achievements of cognitive science and the best practices ofeducational engineering.

This is precisely the approach developed by Didask, which designed an educational AI that went beyond the simple generation of content to orchestrate real learning experiences. This innovative technology structures the courses according to a scientifically validated progression, offers educational activities adapted to the objectives, and generates feedback that stimulates reflection rather than simply providing answers.

Didask educational AI thus transforms each raw content into an interactive and personalized learning experience, guided by the proven principles of cognitive science.

The emergence of AI in training is drawing a new horizon. That of an apprenticeship that could meet the current challenges of training: create more training courses, more quickly, to support the evolving dimension of companies in a world in continuous change. But this quest for agility and speed will not be a real revolution if it does not address the issue of educational effectiveness. It is in this synergy that lies the promise of a profound transformation of our learning practices, where AI no longer becomes a simple production tool, but a real catalyst for skills.

To discover how this convergence is concretely redefining corporate learning and to explore the concept of educational assistant that is emerging from it, we invite you to deepen these reflections in our white paper.
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