Between the promise of hyper-personalization, the automation of certain pedagogical activities and the redefinition of roles, generative artificial intelligence is profoundly transforming the vocational training sector. It's not just adding to existing tools: it's reshuffling the deck in terms of training practices, postures and strategies.

But what is its real impact on training systems? What new balances are emerging for L&D teams?

1. Personalize the learner experience at scale

One of the first benefits of generative AI is its ability to adapt learning paths and content to individual needs. Thanks to the analysis of learning data (results, pathways, interactions), it enables the design of ultra-personalized experiences - on a massive scale.

What it changes:

• Content can be reformulated according to the learner's level (beginner/advanced),
• The pace of learning is adapted to each student's actual progress,
• A variety of formats are available, depending on preferences (quizzes, videos, text summaries),
• Feedback is immediate, targeted and contextualized.

This personalization paves the way for training that is more engaging, more relevant, and better aligned with business needs.

2. Automate certain teaching activities

Generative AI also saves time on low-value-added tasks, while opening up new possibilities for designing and evolving educational content.

Some common uses :

• Turn an internal article into a microlearning module,
• Generate situation scenarios based on realistic scenarios,
• Create quizzes on the fly from a corpus of documents,
• Summarize long documents to extract key points.

Tools such as ChatGPT, Synthesia and HeyGen are increasingly used in L&D departments to speed up content production and rapidly test formats. The aim: to devote more time to needs analysis, pedagogical design, animation... in short, to the human value of the job.

A notable example: at Doctolib, Jordan Defas, Learning & Development Director, shares how AI has become a strategic transformation lever, including in training paths. The company has embarked on a vast project to train its teams in the use of generative AI, while supporting managers in changing their postures.

"What we want to develop is a culture of AI-enhanced autonomy. To achieve this, we need to train people, but also create the conditions for testing, experimenting and learning together." - Jordan Defas, Doctolib

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The aim is twofold:

• Make employees aware of the responsible use of AI,
• And acculturate training teams and managers to these new tools to rethink learning methods.

Doctolib demonstrates here that the impact of AI is not just on content creation, but on learning culture and posture towards change.

To find out more about the exploitation of AI in HR and Learning at Doctolib, check outThe FORWARD Retrospective, which looks back at this theme in more detail. 

3. Redefining the role of trainers and L&D teams

With AI, the trainer's role changes profoundly: he or she is no longer the sole holder of knowledge, but becomes a facilitator, a community leader, a learning regulator. What this means:

• Less time spent passing on information, more time spent leading, regulating and coaching,
• A more individualized approach to support,
• The ability to use learning data to adjust course management,
• Increased skills in AI tools, content curation and scripting.

On the L&D side, this also means developing new expertise:

• Orchestration of hybrid courses, combining generated modules, group time and customized content,
• AI literacy skills: knowing how to use and frame generative AI,
• Analyze pedagogical data: identify trends, gaps and levers for improvement.

Eventually, training teams will increasingly be called upon to play the role of conductor between humans, machines, content and business objectives.

4. Making training more accessible and engaging

One of the positive side-effects of generative AI is that it reduces barriers to entry into learning. These include: 

• By automatically adapting content to disabilities or cognitive preferences,
• By offering a variety of formats (text, audio, video, image), accessible on the move,
• By translating or reformulating messages for more diverse audiences,
• By creating more fluid and engaging conversational interfaces.

These advances encourage more inclusive, flexible and less top-down training. They also encourage us to rethink the learning experience: less linear, more modular, and more connected to real-life uses.

And if you'd like to find out more about how to get people involved in your training projects, discover the best Sales & Marketing practices for convincing sponsors and participants. 

5. Ethical, human and strategic issues

Behind the power of these tools lie fundamental questions. The impact of AI on training is not limited to time savings or technical prowess.

What training managers need to ask themselves:

• What framework should be put in place to manage the use of these tools internally?
• How can you avoid bias or factual errors in the content you generate?
• How can employees be made aware of the critical use of AI?
• What happens to the data generated by learning interactions?

These issues are not just the responsibility of CIOs or compliance officers. They need to be addressed by training managers, in conjunction with HR, communications and governance. 

Adopting AI in training isn't just about "testing new tools": it's about setting out a vision of learning, based on trust, autonomy, adaptability and responsibility.

Generative AI is not a threat to training. It is a lever for profound transformation that can amplify what L&D teams do best : creating links, giving meaning, supporting the progress of individuals and groups. Provided we don't regard it as a simple miracle solution, but as a powerful teammate that we must learn to frame, guide and integrate. Transformation is already underway. It's up to us to decide how to write it.

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