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Tuesday, September 9, 2025
In recent years, the rise of generative AI has profoundly transformed—and continues to transform—our way of thinking about productivity, learning, and the future of work. While countries such as the United States, India, China, and the United Arab Emirates seem to be embracing this wave with speed and ambition, others are wondering: are we moving fast enough to remain competitive?
This article builds on the analysis of Salime Nassur, published on BFM Business, to reflect on a France–U.S. comparison. But beyond that lens, the issues raised concern businesses everywhere: leveraging AI should not stem from fear or constraint, but through awareness, training, and empowerment.
As Gregory Renard, an AI pioneer who has worked in both France and Silicon Valley, reminds us, the issue is not so much about measuring delay as it is about assessing how quickly we are ready to adopt and integrate these tools into our professional lives. The challenge is not only technological; it concerns the ability of organizations and individuals to experiment, take ownership, and fully benefit from AI.
In just one year, the use of generative AI by French small and medium-sized businesses has doubled—an encouraging sign. Yet, according to BPI, only 3% of executives use it regularly, and 12% occasionally. This gap shows that curiosity is present, but action is still limited.
We also operate in what Salime Nassur describes as a VUCA world: Volatile, Uncertain, Complex, and Ambiguous. In such an environment, linear progress is no longer enough. It is no longer just about moving forward, but about accelerating the pace and developing the capacity to adapt quickly, so that AI becomes a true lever for resilience and competitiveness.
Contrary to common belief, the biggest obstacles do not come from technology, financing, or even regulation. They come from us: from our fears, our habits, and a lack of concrete understanding of what AI can bring. As Gregory Renard, a global AI thought leader based in Silicon Valley, observes, these hesitations are often more tied to identity than to technology, and rest on three recurring fears: being replaced, not understanding, and losing one’s place or status.
Many employees have not yet had the opportunity to experiment with AI in their work and therefore struggle to imagine the benefits it could bring. The main barriers identified are:
In short, it is not only about teaching machines to learn. Humans must also learn to unlearn outdated processes, relearn new practices, and evolve with methods suited to an environment where AI becomes a true work partner.
In the United States—and particularly in Silicon Valley—AI is seen as a lever, not a threat. The local culture values:
The motto there is “done is better than perfect.” And if it doesn’t work? Adjust, learn, and move on. In France, perfectionism, risk aversion, and long decision cycles still slow down experimentation. Encouraging evolution requires a gradual cultural shift that extends far beyond technical departments.
Gregory Renard now proposes five levers to move from hesitation to action:
1. Raise awareness and shift mindsets
Explain what generative AI is (and is not). Organize workshops, show concrete demonstrations, and share feedback.
“If you don’t experience it, you don’t understand it. It remains entertainment, not an opportunity.”
2. Build a culture of continuous learning
Go beyond one-off training. Set up:
- short microlearning modules,
- regular monitoring via newsletters,
- experimentation sessions,
- peer-to-peer knowledge sharing.
3.Start with simple, repetitive tasks—identify quick wins
- drafting reports,
- preparing emails,
- writing meeting minutes,
- managing calendars.
4. Promote human–AI collaboration
AI should augment humans, not replace them. It frees up time for intuition, creativity, and client relationships, while handling repetitive work. This complementarity leverages both sides: the speed and analytical power of AI on one hand, and human contextual understanding, sensitivity, and judgment on the other.
5. Rethink processes, not just add tools
Introducing AI is not about “plugging in” a new tool to existing methods. It is often an opportunity to question whether certain tasks should even exist: must they always be done? Could they be simplified or rethought for efficiency?
AI also opens the door to radically new approaches—intelligent automation, need anticipation, large-scale personalization—that improve performance while reimagining the way we work.
The future of work in the age of generative AI will not depend on those who move fastest, but on those who move most intelligently. France is not condemned to lag behind—it simply needs to change pace.
AI adoption is first and foremost a human movement: openness, willingness to experiment, continuous learning.
As Alvin Toffler (cited in Talents Augmentés) nce said:
“The illiterate of the 21st century will not be those who cannot read or write, but those who cannot learn, unlearn, and relearn.”
Awareness must be lived, not just transmitted. This is why learning expeditions, such as those led by RealChange in Silicon Valley, are so valuable: they allow participants to see, test, and feel what AI can truly bring—transforming fear into clarity and confidence.
By cultivating curiosity, humility, and the desire to learn, we can turn this period of uncertainty into a genuine opportunity. The goal is not to be the fastest or the flashiest, but the most adaptable, the most mindful… and the most human.
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