He hovers a sweet illusion on the executive committees: that which artificial intelligence is already transforming the organization. However, behind the Slides varnish, a figure disturbs: Only 11 % of use cases reaches a real level of productionAccording to Quantumblack (McKinsey). In other words, 89 % of projects fail. Not for lack of artificial intelligence but for lack of organizational intelligence.
The structural failure of IA projects
Why do they fail?
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- Because you are asking rupture technologies to adapt to broken processes.
- We expect a language model that it fluidifies an already failing customer relationship.
- We want to accelerate a supply chain whose data is fragmented.
- We entrust a strategic project to a task force without being able or vision.
In reality, AI highlights what does not work in organizations : silos, technical debt, control culture, king’s obsession at three months. In this context, AI becomes a gadget or a fantasy.
AI is not a tool, it is a transformation
It must be said clearly: AI is not an overlay. It is a refoundation.
It is not an “experimentation” in a corner of the IS. It is a questioning of the foundations:
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- Data architectures.
- Operational systems.
- The way of deciding, delegating, learning.
And it is not a chief data officer isolated to carry it. Like all transformative subjects, if the CEO or the president does not personally get involvedno need to start. It will be one more POC, then one more failure.
The trap of the “good model, bad target”
We often hear: “We have the best models, but the project does not take off.” Is that Most AI projects are brilliant answers to poorly asked questions. The problem is not the model, it’s the target:
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- At what time of the process is the value really created?
- Who will use this model? And how?
- What are the irritants, not technical fantasies?
The answer does not come from an open source model. It comes from a capacity to Rethinking uses, decisions, workflows.
How to reverse the curve?
Getting out of 89 % failures is not a matter of technology. It is a case of strategic execution. This presupposes:
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- A strong executive sponsorwho assumes that AI is a transformation project, not a digital gadget.
- A product approach, not projectoriented towards user impact, not technical success.
- A scaling of conditions, not ambitions : No IA model without robust data pipeline, no industrialization without integration into the existing system.
- A tireless pedagogyto avoid the technological elitism which isolates the AI of the social body of the company.
The starting decade will not be that of AI.
She will be that of those who will know operationalize. The others will have the best powerpoint in the board, but the lowest production rate.
