What is the myth of digitalisation?

The myth treats digitalisation as an objective, even though it is a tool. It is intended to improve processes, reduce costs and solve problems. When treated as an objective in its own right, it fails to do precisely that.

What has changed in the last five years?

Above all, the vocabulary. Where it used to say ‘we must digitise’, it now says ‘we must do something with AI’. The underlying fallacy remains the same: the tool is being treated as the objective.

Why isn’t ‘doing something with AI’ a goal?

Because it says nothing about which problem is to be solved. Applying AI to a process that nobody has fully understood merely automates the misunderstanding. First, the process must be clarified; then the tool must be chosen.

How do municipal utilities find the right tool?

By first clarifying the problem and then using figures to assess which method is most suitable. This is precisely what underpins the HOIKEI methodology, which can be used to evaluate processes in terms of their potential for optimisation, benefits and suitability for AI.

So does digitalisation actually achieve anything?

Yes. Once the question of the process has been clarified, digitalisation and AI come into their own and solve real problems. What was thought to be an end in itself becomes a tool, and that is precisely when it pays off.

The Myth of Digitalisation: When the Tool Becomes the Goal

Cartoon: A man is using a saw called ‘Digitalisation’ to fit a railing to a wooden bridge that leads across a gorge to a flag bearing the word ‘Goal’. In the foreground on the left is an open toolbox labelled ‘Optimisation’, containing a spanner, cogwheels and an ‘AI’ chip.

Five years ago, every strategy document stated: ‘Our goal is digitalisation.’ I asked my son, who was nine at the time, what he thought that meant. His answer was spot on: all sorts of things. Board games on the computer instead of at the table, writing on the computer – basically, everything you do on a computer instead of in real life.

Five years have passed, and he’s now a teenager. What else has changed?

Our vocabulary has expanded. The magic phrase is now ‘we have to do something with AI’. However, it hasn’t completely replaced the goal from back then. Digitalisation remains a key issue in many sectors, particularly in the energy industry.

The fallacy has remained the same: the tool is declared to be the goal. ‘We’re digitising’ and ‘we’re doing something with AI’ say nothing about which problem is to be solved. A municipal utility that introduces AI today simply because everyone else is doing so is making the same mistake as the municipal utility that built a chatbot five years ago simply because everyone else was doing so. The tool arrives, but the problems remain.

How does this manifest itself? A process that was running poorly before starts to run poorly even faster after digitalisation. An AI system superimposed on a process that nobody has fully understood simply automates the misunderstanding. The tool does not change the core issue. It merely makes more visible what was already there.

I ended the original text with a promise. In the following articles, I wrote about – and demonstrated – how I decide which optimisation method is most suitable. These posts have resulted in five years’ work, culminating in a methodology that structures precisely this choice. With HOIKEI, I now evaluate each process individually to determine how well it can be optimised, what the benefits are, and whether AI is even the right solution for it. The underlying idea has remained the same, only it has become more refined: “First the process, then the tool”. First, we ask what problem we want to solve; then we reach into the toolbox, guided by figures rather than trends.

That’s the good news. Once the question of the process has been clarified, digitalisation and AI come into their own. They save time, reduce costs and solve real problems. The supposed goal becomes a tool, and that is precisely when it becomes worth its weight in gold.