Everyone is talking about artificial intelligence – but most companies simply aren't ready for it. Why clean processes and data must come before any AI project, and the order in which digitalization actually works.
Everyone is talking about artificial intelligence. At conferences, in strategy meetings, on LinkedIn. AI sounds like the future, speed and competitive advantage.
The uncomfortable truth: most companies simply aren't ready for it.
Because while everyone is discussing machine learning and automation, core processes in many industries still run on Excel lists, email chains and the knowledge inside individual employees' heads. Data does exist — but it's scattered, unstructured and unusable.
AI lives on quality data. If the input is bad, the output is even worse. The result: wasted budget, lost time, frustrated teams — and in the worst case, you're not automating success, you're automating chaos. Just faster.
AI is not a substitute for clean processes. It's the layer that builds on top of them. Ignore this order and you pay twice: first for the failed AI project, then for the digitalization you would have needed to do anyway.
Not because everyone has to sell software. But because sooner or later every company has to operate in a data-driven way: Which customers are profitable? Where do delays occur? Which decisions are based on facts — and which on gut feeling alone?
Especially in conservative industries, stability is easily mistaken for future-readiness. But rising costs, skilled labor shortages and new competitors won't wait until you're ready.
The uncomfortable part: digitalization is not a new topic. We've been talking about its importance for years — in strategy papers, funding programs and Sunday speeches. But in many companies, that's exactly where it stayed: at talking. Processes keep running the way they always have, and people rely on them doing the same tomorrow.
The problem: the AI boom is making everything move much faster than that calculation allows. The gap between those who have done their homework and those who are still talking is widening — and every year the transition gets harder, more expensive and riskier. Anyone who should have started five years ago simply can't afford to keep waiting today.
The path is no rocket science — but it has a clear order. Follow it and you build a foundation. Skip it and you build an expensive pilot project that never makes it to production.
1. Understand your processes before you touch them. Sit down with the people who actually do the work. How does an order really flow through the company — not how the org chart says it does? Where is data retyped, copied, chased down by phone? Which steps depend on a single person? The result is an honest map of your workflows: roles, systems, interfaces, media breaks.
2. Analyze your data flows. Follow the data along these processes: Where is it created? Which system does it end up in — ERP, email, Excel, nowhere at all? Where is the same information captured multiple times, where does it get lost? Usually it's not the data that's missing. It's the structure.
3. Digitalize the core workflows. Not everything at once — start with the processes that cost the most time and money. Replace manual steps with workflows, connect systems through interfaces, eliminate media breaks. Start small, deliver measurably, then expand. Digitalization is not a big bang — it's iterative work.
4. Build a clean data foundation. Only when processes run digitally do you automatically get structured, connected, analyzable data. Define where which data lives as the single source of truth, who has access to it and how quality is ensured. This is the point where data collection turns into a data-driven business — with reports that are accurate and decisions based on facts.
5. Now — and only now — talk about AI. On this foundation, AI can unfold its real leverage: automatically understanding documents, pre-qualifying inquiries, forecasts based on real process data. Not as a buzzword, but where it measurably reduces work.
The question is not whether you will use AI. The question is whether your processes and data will be ready when you do.
Those who start doing their homework today will have real leverage tomorrow. Those who wait will end up automating their chaos.
So: before we talk about AI — let's talk about your processes.
If you want to apply these ideas to a project in your organisation, let's talk – free and non-binding.
