EU Industrial Data Regulation: From a Legal Obstacle to the Key to Digital Transformation

The European Union is known for introducing restrictive regulations that often complicate life for businesses. This time, however, the situation is different — new rules concerning access to industrial data address a problem that has for years slowed down the digitalization of factories.

The problem that blocked transformation

Manufacturers of MES (Manufacturing Execution System) software know this scenario all too well: a company buys a machine worth millions, yet cannot freely retrieve data from it. The equipment manufacturer either technically blocks access to protect its know-how, or enforces additional fees, and often imposes its own MES system.

This is not merely a technical issue. The lack of standardization of communication protocols is one thing, but legal barriers to accessing data from machines a company already owns are a completely different matter. For companies developing AI-based solutions, this problem is fundamental — without data there are no algorithms, and without algorithms there are no intelligent factories.

Nvidia and the data problem at a broader scale

Large technology corporations such as Nvidia, which are currently attempting to digitize factories using their solutions, quickly discover that the data problem is not only a technical challenge. In Europe, they encounter a legal barrier — closed ecosystems of equipment vendors who treat data as a source of additional revenue.

For future factories operating on AI, access to machine data is critical. Machine learning algorithms require gigabytes of operational information: operating parameters, fault states, performance metrics, energy consumption. Without this, intelligent production optimization remains a theory.

Particularly painful for operating factories

The problem becomes even more significant in the context of existing production plants. A new factory can plan its digital infrastructure from the very beginning. But what about the thousands of operating factories that want to digitize their machine parks?

They cannot afford sudden production stoppages — downtime costs are counted in hundreds of thousands of euros per hour. Modernization must take place while the production line is running. And when it turns out that, legally, they do not have full access to data from the machines they already own, the digital transformation project comes into question.

Regulation as a reset of the balance of power

EU regulations on industrial data structurally change this situation. Machine manufacturers and operators receive legally guaranteed access to data generated by their own equipment. This is no longer a matter of commercial negotiations or the supplier’s goodwill — it is a regulatory right.

For the ecosystem, this means:

• Reduced dependence on closed platforms of equipment manufacturers

• Lower entry barriers for MES software vendors

• The ability to build analytical solutions independently of machine manufacturers

• A real foundation for AI projects in production

The trap of internal over-interpretation

Paradoxically, one of the biggest obstacles is not the regulations themselves, but how they are interpreted within organizations. Legal and compliance departments often adopt the most restrictive interpretation of regulations, even when the rules allow for greater flexibility.

A key distinction: regulations clearly separate consumer data from industrial operational data. The latter is treated far more liberally. However, in internal discussions this distinction often becomes blurred, leading to initiatives being blocked based on presumed rather than actual constraints.

Enforced transparency as added value

Regulations force answers to questions that were previously postponed:

• What data do our machines generate?

• Where is it stored and processed?

• Who has access to it?

• Under what conditions can it be shared?

The answers improve internal data structures even before any external sharing occurs. Regulations become a catalyst for better data discipline and transparency.

The risk of waiting for “complete clarity”

Regulatory frameworks evolve, guidelines mature, interpretations are refined. Companies waiting for absolute certainty before acting risk falling behind competitors who engage earlier and adapt along the way.

Progress does not require ignoring regulations — it requires working with them through industry groups, dialogue with regulators, and practical experimentation within defined boundaries. Digital transformation and regulation progress in parallel, not sequentially.

From constraint to advantage

Instead of viewing EU regulations as another bureaucratic obstacle, it is worth seeing them as an enabling factor for:

• Clearer access to machine data

• More transparent relationships with equipment suppliers

• Fairer industrial data ecosystems

For MES software vendors, system integrators, and technology companies, this represents a market opening. For factories pursuing digital transformation, it removes a key legal barrier.

The main question is not “how to avoid regulations,” but “how to use them to regain control over one’s own industrial data” — and thereby accelerate the creation of digital value whose foundation is the data generated by machines operating on production floors.