AI is only as good as the data behind it
René Dalsgaard
Interest in AI is growing among businesses. But the projects that succeed have one thing in common: they are built on structured data. Here is why the data foundation determines whether AI becomes an asset or an expensive detour.
Everyone is talking about AI. Few are talking about data
Since 2023, interest in AI among Danish businesses has grown from 15 to 59 percent in 2026. That makes sense in a world where streamlining time-consuming tasks can be the path to growth. Expectations are therefore high: AI should free up time, reduce manual work and provide a better basis for decision-making.
But interest alone does not move the needle. According to Dansk Erhverv, “a lack of employee competencies, knowledge and time are the biggest barriers to realising the potential of the technology.” And even when the competencies are in place, many run into the same wall: data is scattered across folders, emails and systems that do not communicate with each other. In that way, AI risks becoming a significant investment of both time and money that never delivers the expected return.
The decisive question is therefore not whether you should use AI. It is whether your data is ready for it.
Structured data is the foundation
The potential already exists within your organisation. Project experience, documents, customer data, and sales and production data contain precisely the knowledge an AI tool needs to provide a qualified basis for decision-making, but only if the data is consolidated, structured and accessible across departments.
“Structured data is so important because AI is only as good as the data behind it. The AI projects we see succeed are the ones where the data is in order.”
That said, technology cannot stand alone. It is still the employees who must understand, use and evaluate what the AI delivers. When data and people work together, you get a more efficient workflow, and employees gain more time for what they do best.
How to get your data ready for AI
Three principles will give your data a solid foundation for AI:
- One platform, one structure: When documents, sales and production data are all stored in one place with a consistent structure, AI tools have an overview they can work with from day one.
- The right data for the right tool: Data must be able to be passed automatically to AI tools without losing its structure. You should be able to decide what is shared, for example, only proposal files, regardless of file type.
- Your data is yours: Choose solutions that do not lock you in, so you can build freely with the partners you choose. Ensure that data is stored securely in the EU and that the supplier can document this, for example with ISAE 3402 and 3000 certifications.
From three days to 10 minutes at VAM
What this means in practice can be seen at VAM. Together with Fruity, they have developed TenderCore, an AI tool that reviews tender documentation and flags potential red flags, with data from Orbit as the foundation.
Previously, it took three days to gather the material, set it up and assess whether VAM should submit a bid. Today it takes 10 minutes. Read the full story about TenderCore on Building Supply.
When a customer succeeds with an AI project based on data from Orbit, all other customers benefit. Everyone runs on the same version, so the structure built up along the way is available to all.
Data first, AI second
AI can take the heavy, repetitive tasks out of everyday working life. But the tool will never be better than what it is built on. Scattered data produces uncertain answers, whilst structured data provides a basis for decision-making you can rely on.
That is why a sound AI investment does not start with the choice of tool. It starts with a look at your own data: where does it live? How does it connect? And can it be shared with the systems you want to build on? Because the organisations that get the most out of AI are not necessarily the ones that got started first. They are the ones that had their data in order when they did.
Recommended articles for you
