Since ChatGPT burst onto the scene, AI has become ubiquitous in discussions, to the point where it is sometimes perceived as magical. However, let’s remember one obvious fact: AI is not magic, and it is very important to separate fact from fiction. These are algorithms based on mathematics, statistics, and probabilities. When generative AI produces text, it does not “think”: it simply calculates the most probable sequence of words in an attempt to best respond to your prompt.
The myth of the intelligent agent
In the field of AI development, we often hear: “I built an agent.”
Unfortunately, in 8 out of 10 cases, this boils down to a simple API call and a few lines of code. While useful, this is a far cry from a true agent with memory, orchestration, or complex integrations. This confusion perpetuates a bubble of illusions that serves neither executives nor companies.
The real challenge: adoption in business
The gap between rhetoric and reality is striking. An MIT report (August 2025) indicates that 95% of AI pilot projects do not generate any measurable financial return.
There are many reasons for this:
- Companies are not yet data ready, with siloed systems and poor-quality data.
- Dependence on external solutions raises issues of sovereignty and strategic dependence.
- Isolated use cases unrelated to business objectives.
- Adoption hampered by internal committees, regulations, and/or a culture slow to change.
These obstacles are reminiscent of the adoption cycles of the cloud and the internet: it took 7 to 10 years before they became standard. AI will follow the same path.
Is AI useful today?
Yes, AI is useful right now because it already excels in practical applications:
- Sales tracking
- Detection of anomalies or fraud
- Document sorting
- Image recognition
- Product recommendations
- Predictive maintenance
- Medical monitoring
- …
The applications of these algorithms are already visible in our daily lives: Netflix personalizing our choices, banks blocking suspicious transactions, hospitals detecting certain anomalies earlier.
With reliable and well-structured data, these algorithms become a strategic ally for growth.
A question of strategy
The real challenge for leaders lies here: AI must be integrated into the company’s overall strategy and not limited to a series of isolated projects.
This implies:
- A direct link to business objectives,
- A solid data strategy (quality, security, governance),
- An organizational capacity to absorb change.
AI is not a side experiment. It is a cross-functional tool that must be connected to the company’s vision and priorities.
Patience, ambition, and clarity
Adopting AI is not a sprint, it’s a marathon. Adoption cycles are long, but history shows that they ultimately transform organizations profoundly.
Leaders must keep a cool head: AI will not replace humans, but when properly integrated, it will become one of the most powerful drivers of competitiveness, productivity, and innovation in the coming decade.
See also : 1 in 3 professionals hides their low level of AI skills, according to a LinkedIn study
