Generative AI makes it faster, easier, more productive. But to delegate without discernment is to risk losing what is the basis of any organization: the ability to reason and decide for oneself.
The adoption of Artificial Intelligence technologies is rapid and the enthusiasm is real. In 2025, almost 20% of companies in the European Union report using generative AI technologies. As for large companies, 55% of them use it. On the individual side, nearly 33% of Europeans aged 16 to 74 have already used content generation tools, including 15% in a professional context. However, behind this acceleration lies an invisible cost: by dint of delegating to AI, the company risks displacing, or even weakening, its own cognitive core.
75% of employees use AI. How many still master their reasoning?
Write a report, write code, produce an analysis or simulate a strategic scenario: with AI, everything now seems accessible in just a few prompts. The Work Trend Index 2024 reveals that 75% of knowledge workers say they use AI at work, and 78% bring their own tools into the company. Gradually, the use of generative AI even goes beyond official frameworks to gradually become established in daily practices. However, producing a deliverable does not mean understanding the reasoning that generated it. The illusion of immediate competence often masks a growing dependence on systems whose internal logic often remains opaque. Operational delegation can quickly become an intellectual delegation.
The hidden cost of automation: an organization that no longer knows how to explain its choices
Technical debt is well-known: it results from rapid choices that compromise future robustness. Cognitive debt is more insidious. It appears when the organization is no longer fully capable of explaining how it constructs its decisions: what data was used, what trade-offs were made and what hypotheses were integrated. What about trust in this case? The OECD observes that the use of AI will reach 20% of companies in countries for which data is available in 2025. This rapid diffusion is superimposed on existing architectures and heterogeneous systems. Above all, it compensates for unevenly distributed skills. As tools produce analysis, code, or recommendations, there is a strong temptation to reduce internal understanding effort. However, an organization that does not maintain its capacity to analyze, verify and reproduce reasoning is exposed to a progressive loss of control.
The real danger isn’t that AI replaces your teams — it’s that they trust it blindly
A company is not defined only by its material or financial assets. It is based on essential intangible capital: the collective capacity to structure a problem, formulate hypotheses, arbitrate and decide. But when AI is involved in strategy writing, model design, risk analysis or talent assessment, it doesn’t just deliver faster resolution. It fits into the chain of reasoning. The question then becomes strategic: if the tool structures thought, who retains the capacity to question it? By delegating, certain skills can atrophy. Just as the calculator changed the relationship to mental arithmetic, AI can transform the relationship to analysis and writing. The risk is not that AI “replaces” teams. It is because teams become dependent on reasoning that they no longer fully control.
From tool to infrastructure: what COMEXes should demand from their AI
Treating AI as a simple tool leads to a multiplication of dispersed uses. How to get out of this trap? Generative AI should be considered as decision-making infrastructure. As such, it imposes a new discipline: traceability of data, explainability of models, auditability of production chains and maintenance of critical internal skills. Trust cannot be a starting point. It must be the result of an architecture designed to preserve human understanding. The challenge for COMEX, IT departments, data departments, HR departments and regulators is not to hinder innovation. It is to ensure that the company retains its intellectual center of gravity.
Generative AI promises speed and intellectual abundance. But speed is not mastery, and access to knowledge is not knowledge itself. An organization that relies on its tools without cultivating its own judgment does not gain power, it silently transfers its capacity to think. The real question is no longer what AI can do. It’s about measuring what the company is still capable of doing on its own. Because an organization that has lost the thread of its own reasoning does not only suffer from a loss of performance. She gradually renounces what forms the basis of her identity: making informed decisions.
