Artificial intelligence is everywhere. According to McKinsey, between 65% and 71% of companies have already adopted generative AI in at least one function – compared with just 33% a year earlier. Gartner even predicts that over 80% of enterprise software will incorporate AI functionality by 2027.
The figures are impressive, but they mask a reality: in the majority of cases, AI is still perceived as a tactical lever, confined to automating certain tasks. Yet, on closer inspection, AI acts above all as an organizational mirror. It reveals inertia, unquestioned managerial routines and governance flaws.
So the question is not just “what tools should we adopt?” but “what is AI forcing us to rethink in the way we run and organize the company?”.
In most organizations, AI is being adopted in a scattered way. Human resources, marketing or customer services are testing use cases such as content authoring, lead pre-qualification or document automation.
But according to one expert interviewed, “most customers are not integrating AI at a strategic level. Its use remains mainly operational”.
The result: AI speeds up tasks… without transforming the structure that decides on those tasks. An extra layer of efficiency, but no reflection on meaning, governance oroverall impact.
Many executives admit they don’t know what strategic issue AI is supposed to solve. Enthusiastic about the tools, they often lack a compass.
Major obstacles :
persistent silos,
fragmented decision-making circuits,
a lack of alignment between AI, corporate vision and key skills projection.
As Maximilien Brabec points out in Harvard Business Review:
When each silo develops “its own AI”, existing silos are exacerbated.
Applying AI to an already complex and inefficient organization prevents any real value creation.
An MIT study shows that 95% of generative AI projects fail to deliver any return on investment.
You can’t put an intelligent tool on top of a poorly thought-out process. The first step is to carry out an “organizational weeding “: simplifying, clarifying what really creates value and removing what gets in the way.
In the short term, AI often brings productivity gains. Automate, simplify, streamline: yes, but for what?
Many companies have yet to redefine :
functions,
roles,
and key skills.
As a result, AI becomes a high-performance but non-transformative patch. Surface economies, with no business overhaul or strategic vision.
As one manager pointed out:
“AI advances differently in different sectors, but it can’t be used well if you haven’t mastered the initial task.”
The real question is not “which AI should I adopt?”, but “what does AI force me to rethink in order to create a new form of value?”.
This implies a paradigm shift, not a simple update of tools.
Governance must evolve so that AI becomes a strategic amplifier, not a technical patch.
AI is not just a tool for automation. It’s a life-size test for corporate governance. It reveals blind spots, silos and areas of inaction.
To get real value out of it:
simplify your processes,
align your strategic decisions,
and dare to question your managerial routines.