Over the last few months, the idea that AI will enable us to produce more and do without many human skills has spread with astonishing speed. It's a cultural narrative, a form of progressive contagion that extends well beyond the IT framework to permeate all professional conversations, internal arbitrations and sometimes even hiring policies.
When AI feeds the fantasy of replacement
On LinkedIn, one example follows another. The same demonstrations, the same chains of automation, the same exaltation around content multiplied at high speed without human intervention.
It took me hours, but I've automated everything: my content creation chain, from text to carousel! No need for a graphic designer, freelancer or copywriter... Comment on «carousel» to get my method.
This type of publication - which has become almost a genre in itself - is a perfect illustration of the shift at work. As for the figures relayed in the public debate, they do nothing but fuel this imagination. As we were recently reminded Yann Ferguson, sociologist specialising in employment and AI, One analysis estimates that one in two jobs could be profoundly transformed by artificial intelligence, and that one in ten jobs could see its share of tasks significantly reduced.
And this is where the real misunderstanding arises: transformation has never meant replacement, reducing tasks has never meant losing value. It only says that the nature of work is changing, not evaporating.
Faster automation does not mean better production
In some demonstrations, the fascination with the speed of AI takes on the appearance of a technological cult. A few months ago, during a presentation, I was shown how to generate a complete PowerPoint in just a few clicks. The «wow» factor was undeniable, but the content was much less so. One slide followed another: clean, aligned... but with no real intention. The whole thing looked more like a rapid assembly than a constructed thought. The visuals inserted automatically had no graphic coherence, and some were even distorted. A perfect example of what the AI was optimising: speed but not quality.
Yet this confusion between speed and quality is everywhere: automation means improvement, fast production means better production. This misunderstanding boils down to very little: a simple, seductive, almost intuitive idea. If AI makes it possible to go faster, then it would make it possible to do better, and if it makes it possible to produce more, then it could replace. But speed says nothing about accuracy, and quantity says nothing about value. What we are seeing today, in both speeches and demonstrations, is an imaginary performance that is far removed from reality. An imagination in which productivity becomes an argument in itself, almost detached from what is really being produced.
What AI does well...and what it can't do
However, this does not seem to be AI's true potential: AI is a tool for productivity and exacting standards that excels when it is asked to explore avenues, open up alternatives, deploy variations and enrich a thought process. It becomes fragile when entrusted with nuance, coherence, meaning, intention or the automated whole. Because AI is, after all, just a statistical model and a probabilistic mechanism, not real intelligence.
When AI becomes an argument for waiting
This misunderstanding of AI has spread far beyond the web for some time and now permeates all levels of French and global organisations. There's a discourse that runs from the basement to the top: since AI means we can produce more, does it mean we can reduce human labour? It gives rise to the idea that technological acceleration could almost naturally reduce the number of human resources in companies.
The temptation is great to bring AI into the conversation as a final argument: «Let's wait and see what AI will replace». We can see this in the recruitment that freezes, the job descriptions that are redefined ad infinitum, the decisions that are put off.
What is perhaps most disconcerting is that some organisations genuinely seem to believe it. They don't take up this narrative just to pretend: they adopt it as a credible prospect, and unease sets in. Not in AI itself, but in the ease with which we imagine that a technology could absorb the complexity of human work.
The replacement story as a strategic alibi
This climate of ambiguity is further fuelled by the fact that some major groups have already begun to use AI as a reason for reorganisation. In recent months, several companies - Amazon, Goldman Sachs, Microsoft - have announced waves of redundancies, explaining that the automation made possible by artificial intelligence would make it possible to reduce certain jobs or restructure entire departments. These high-profile announcements reinforce the idea that the transformation will be primarily quantitative. That it would consist of «doing more with less», even if it means suggesting that technology would mechanically absorb human functions.
However, these decisions have less to do with a real demonstration of capacity than with strategic positioning: to demonstrate rapid modernisation, to reassure the markets or to prepare for internal trade-offs that have already begun. In other words, these announcements do not validate the disappearance of business lines. They merely validate the narrative power of AI in a tense economic context.
What AI really reveals about organisations
The effect produced by AI is very real: it sustains the belief that the movement is irreversible, that organisations that do not adapt will fall behind, and that AI will establish a new standard of efficiency based above all on human reduction.
So, is it really AI that is holding organisations back at the moment? In this landscape of budgetary and political uncertainty in France, doesn't AI provide a convenient narrative: a way of dressing up a hesitation, justifying a slowdown, masking a postponed decision? A screen that is perhaps much more comfortable than reality.
The real transformation will not be quantitative
Faced with the spectacular promises of AI, there is a great temptation to see it as a substitute, a shortcut, a way of lightening the load on human labour. On the surface, this is attractive, but it obscures the real challenge facing companies in the future: that of quality. Because tomorrow the question will not be who produces «the most» but who produces «the most just», and it is in this requirement that the real transformation will take place.