The desire to learn is growing fast, but time is short. Autonomy is what people want, but structure remains essential. These are the key findings from our 2026 study, conducted with Sociovision among 2,500 working professionals and students. But beyond the figures, what do these tensions tell us about the world we live in?
Maryline Nguyen, Head of Expertise at Sociovision Groupe Ifop and co-lead of the study, shares her analysis. For over forty years, the company has been tracking sociocultural shifts in France, giving it the perspective needed to tell passing trends from deep-rooted change, and to understand what this means in practice for L&D teams.
What explains the particular enthusiasm for learning and development today?
Because for many people, it has become one of the few areas of their lives where they can still make a difference. The French are navigating a world of uncertainty – climate change, economic instability, geopolitics, but also the changing nature of their jobs, their pensions, their healthcare system. Nothing feels particularly reassuring any more. At Sociovision, we have been measuring for years the proportion of French people who feel that “the world is changing, but making less and less sense.” Over forty years, that figure has risen from roughly one in two (51%) to nearly three-quarters (74%)!
In response to this sense of losing control, a pattern is emerging: people are looking for areas of their lives where they can still be active agents, even on a small scale. Private life is one. Work – and training in particular – is another. In that sense, training has become one of the tools people use to stay in control of their lives and, ultimately, their future. The thinking goes: “The world is changing, but if I’m better prepared, I’ll be able to adapt.”
That is why I am not surprised by the 91% of working professionals and students who say they are comfortable with the idea of lifelong learning in this study. It is not just an enthusiasm for professional development – it is a response to a deeper anxiety: the fear of losing control over one’s own path.
Is this climate of uncertainty specific to France, or is it found elsewhere in Europe?
The uncertainty itself is shared across Europe. What differs is how well each country has prepared – or not – its people to deal with it. In France, people have long lived in a world with strong safety nets: a good pension, a good healthcare system, a strong state. Today, trust in these institutions is eroding, and the French have not been raised with the idea of managing on their own.
This is not an isolated trait – it comes through elsewhere in the study too, particularly in the way younger generations turn to AI rather than a trainer, which I will come back to. A culture in which collective institutions have traditionally protected the individual tends to build less capacity for self-reliant resilience.
There is, however, an interesting counterpoint: this distrust does not extend to local institutions. Where trust still exists, it is at a local level – community associations, the local mayor, local bodies. For L&D teams, I see a fairly direct lesson here: in a climate of distrust towards large organisations, the credibility of a training programme is built first at the human, local level – the manager, the trainer, the peer community – rather than through top-down institutional messaging.
The study reveals a paradox: a strong desire for autonomy, but an equally strong need for structure. How do you interpret this?
This is, I think, the most revealing finding in the study. Our data shows it clearly: 90% of respondents enjoy learning on their own, yet 79% still prefer a structured framework. This combination of strong autonomy and a need to be supported – not managed or constrained – really defines our times. People think: I need this to fit around my schedule, I need the content to match my needs. But I also need a framework, even a time-based one, with sessions that are not left to chance. It is a combination of expectations we are seeing more and more, and one that is harder than it looks to put in place in a way that really works.
It is important not to misread the nature of this structure: what reassures people is not oversight, but the commitment it creates. A scheduled session with a trainer, or in a set format, turns a vague intention – “I really should do some training” – into a concrete moment that cannot be put off indefinitely, unlike a module available on demand at any time. I think this also explains why trainer quality and practical exercises come out on top when people choose a training programme in our study, well ahead of AI (13%) or gamification (11%): they represent the kind of structure that reassures without becoming a constraint.
For L&D teams, I do not think this paradox is a problem to be solved by choosing between autonomy and structure. It is a design challenge to accept: building programmes that are flexible in pace, but punctuated by non-negotiable milestones.
In practice, how do you strike the right balance between human involvement and increasingly autonomous digital tools?
I like to compare digital learning tools to Aesop’s tongue: at once “the best and the worst of things.” There is a real tension between their enormous potential and their equally significant limitations. You need the human element at certain moments, but it does not need to be present at every stage.
My suggestion is to think in terms of “moments that matter” rather than a volume of human hours to be preserved at all costs. In practice, this means identifying the stages of a programme where having a trainer really changes the outcome: the start, when the learner needs someone to set a rhythm and provide reference points; the difficult plateaus, such as reaching B2 level, where intensity alone is no longer enough and personalised support becomes key; and high-stakes professional simulations, where human interaction remains, structurally, richer than any automated scenario.
Everywhere else, digital can handle repetition, personalisation at scale, and access on its own. The key is to put people where they are needed – and to tell learners why. This is a point that is often overlooked: a learner who understands why one stage is automated and another is not will accept it far more readily than a mix that seems arbitrary.
Among students, AI has already become a default learning reflex. Is this a generational shift, or the continuation of a longer-standing trend?
Both, I think, but not quite in the proportions people imagine. The technological reflex and the taste for autonomy are real and well-documented: a study recently conducted by the Ifop group for CIVICA, an alliance of 10 leading European universities in the social sciences, shows that among their students, AI is already the second most used source of information, partly due to significant time pressure. Because of that pressure, students no longer read entire books – they read summaries, made very accessible by AI. When they have a question, the instinct is also to turn to AI, even if the level of trust they place in it remains fairly limited.
A cultural factor reinforces this reflex, and it is worth naming: the relationship with the teacher or trainer. Asking a human a question often means exposing yourself to judgement; asking AI does not. In a country where the educational relationship has historically been built around assessment rather than support, this cultural trait directly contributes to the rise of AI as a first instinct rather than a complement.
But the most useful nuance for L&D teams relates to a self-report bias. What younger generations will not say out loud – and probably underestimate themselves – is their real need to have people to talk to. The fact that a generation says it prefers autonomy and technology does not mean it no longer needs human interaction; it means it is less aware of that need, or less in the habit of expressing it. This is a direct point of caution when designing programmes for younger professionals: do not take their stated preference as the whole picture.
A lack of time remains the biggest barrier to training, and it weighs more heavily on women. What does this tell us about working life today?
It points, first of all, to a contradiction I observe across society as a whole: we have less and less time. We sleep less and less. We are supposed to have every means of saving time at our disposal, yet time feels increasingly scarce. Perhaps because we are pulled in so many directions. For working professionals, the rise of remote meetings has had a paradoxical effect: it creates the feeling of fitting real work into already busy slots, rather than freeing up time.
In the study, 38% of respondents cite lack of time as their main barrier to training (63% overall), and the solutions they expect are concrete: financial support (37%) and training during working hours (29%). But this constraint is not evenly distributed. 47% of women aged 35 to 44 cite a compatible schedule as their primary selection criterion, compared with 35% on average. Despite how much has changed, responsibility for the home, housework and children still falls largely to women.
For L&D teams, this shifts the question. It is not just about offering short formats for pedagogical convenience, but about recognising that available time is not a neutral variable: it varies significantly depending on each person’s mental and domestic load, and a programme that ignores this reality structurally disadvantages certain groups, without that always being visible in enrolment statistics.
If you could take just one lesson from this study for organisations, what would it be?
In my view, the way we combine digital and human elements needs to be reinvented – and in a truly innovative way. I really believe that the two, combined intelligently, can produce new solutions that neither could achieve on its own. The question to ask is not “do we need more digital or more human?” but rather: at what precise point does human involvement change the outcome, and at what point is remote delivery enough. You need to know how to calibrate it, and where to draw the line.
This is a very concrete invitation for training managers: rather than choosing between an all-digital approach that looks attractive on paper (scalable, measurable, cost-effective) and an all-human approach that feels reassuring but is hard to roll out at scale, the exercise is to map your own training programme to identify its moments that matter, and to focus available human resources precisely there.
This conviction – combining digital and human intelligently rather than setting them against each other – is also what shapes 7Speaking’s programmes: real flexibility in pace and access, combined with human touchpoints positioned where they make the real difference: at the start, at difficult plateaus, and in professional simulations.
