A transformation struggling to deliver on its promises

The assessment is harsh: only 8% of French companies have truly begun their digital transformation, and only 6% consider themselves 100% digitalised. France is structurally lagging behind its European neighbours, and it is not for lack of investment.

Nearly 70% of companies struggle to turn their technology trials into genuine productivity gains, often due to a lack of methodology. Tools are deployed. Teams are trained. POCs are launched. But the operational transformation itself does not take place.

Why?

The first confusion: digitalising is not transforming

Digitising an inefficient process means going faster in the wrong direction. Yet this is what most organisations do when they believe they are transforming.

Replacing an Excel sheet with an online form is digitalisation. Transforming is rethinking the process itself: the way decisions are made, the way experience circulates, the way teams learn from one another.

Digitalisation is a tool. Transformation is a change in operational model. And what distinguishes successful organisations from those that invest without transforming is that they start from the business problem, not the technology.

Change management remains the neglected aspect of all these projects. The tool is installed, the launch is announced, and it's a surprise that practices do not change. Digital transformation cannot be decreed. It must be supported.

The second confusion: AI is not a magic wand

80% of French executives use AI at least once a week, but the challenge goes beyond one-off efficiency gains and isolated experiments to redefine operational models.

Integrating a generic AI API into existing software does not transform the organisation. It adds a layer on top of an unresolved problem. The real breakthrough is native AI, integrated into operational workflows, trained on real business data, and useful from day one on the ground.

What distinguishes an AI that changes practices from an AI that impresses in a demo: the former relies on the organisation's history to propose contextual decisions. The latter answers generic questions that no one actually asks on a daily basis.

What digital transformation should really produce

A successful transformation is not measured by the number of tools deployed. It is measured by the speed at which the organisation improves.

In concrete terms, this yields: decisions made faster, with more context. A capitalisation of collective experience accessible to everyone, not just the most senior experts. A reduction in avoidable costs, repetitive tasks, analyses redone from scratch, and already known errors reappearing due to a lack of organisational memory.

In manufacturing, quality management perfectly illustrates this distinction. Many organisations have digitised their non-conformities; they have replaced Excel with an online form. But the data still do not talk to each other, recurrences are not detected, and teams start from scratch with every incident. This is not a transformation. It is surface digitalisation.

What changes when the transformation is real: the AI analyses the history, detects patterns, and proposes decisions based on what the organisation already knows. Quality changes from a cost centre to a measurable lever of performance.

Digital transformation is judged by its results, not its intentions

The question is no longer "do we have a digital tool?" It is: is our organisation deciding better, faster, and learning from its experience?

It is by this standard that a true transformation is measured. And that is what separates the 20% that succeed from the 80% that invest without transforming.