AI Regulation: What should you as a company be aware of?
Pay transparency requires a clear structure for jobs, roles, and salaries. In this article, we explore how AI can help HR analyze existing HR data and suggest a structure that makes the work with pay transparency faster and easier to manage.
AI is already finding its place in HR. From recruitment and screening to analysis of employee data and salary structure, technology is becoming a part of everyday life in many organizations.
At the same time, the EU's AI Regulation (AI Act) makes it clear that it is not just about opportunity - it is also about responsibility.
But for many companies, it's not just another requirement. It is also an opportunity to create an overview.
AI is not just AI
An important point of the AI regulation is that not all AI is the same. Instead, the regulation works with a risk-based approach. This means that the requirements depend on how the technology is used and what impact it has on people.
Overall, a distinction is made between:
- Low risk
AI that doesn't significantly affect decisions or people - Limited risk
AI that interacts with users (e.g. chatbots) requiring transparency - High risk
AI, which is used in situations where it has a direct impact on people - for example, in HR.
In particular, it is the last category that is relevant for many companies.
From many guidelines to common rules of the game
Until now, many companies have navigated a landscape of:
- Recommendations
- Best practices
- Internal guidelines
It's made it hard to know what “is good enough.”
With the AI regulation, now comes:
- Common minimum requirements
- A clearer definition of risk
- A common starting point across the EU
It makes it easier to work more structured and gives something concrete to navigate by.
Responsibility is not only yours - but also yours
An important point of the AI regulation is that responsibility is distributed throughout the value chain.
- Vendors (who develop solutions) have the greatest responsibility
- Customers (who use the solutions) still have a responsibility for the use
For you as a company, this means:
Don't build it all yourself. But you need to understand what you are using and how.
It is, for example, about being able to answer:
- How does AI become part of our processes?
- What do we use it for?
- What does it affect?
You already have a good starting point
For many companies, AI regulation will not feel entirely new. If you are already working with:
- GDPR
- Data security
- Kompatija
You have a strong foundation.
Many of the same principles go again:
- Documentation
- Controls
- Transparency
The difference is that the focus is now also on decisions and impact - not just data.
AI requires structure - not just technology
One of the biggest challenges is rarely AI itself. That's the foundation.
Many organizations are still struggling with:
- Unequal Job Titles
- Lack of pay structure
- Data spread across systems
When the structure is not in place, the AI becomes:
- Hard to explain
- Hard to trust
- Difficult to use responsibly
And this is precisely what the AI regulation indirectly focuses on.
It's not about slowing down - but about spending right
AI regulation is not made to stop development.
It is made to:
- Build trust
- Protecting people
- Ensure responsible use
Once the framework is clear, it will be easier to work with AI across organizations and countries as well.
How do you guys get started?
You don't have to start with a big compliance project.
Start with an overview:
1.Where do we use AI today?
2.What HR processes does it affect?
3.Do we manage our data and structure?
And then:
4.Can we explain how AI is used?
5.Do we have the right processes around it?
AI is becoming an increasingly important part of HR.
With the AI regulation, it becomes clear that it is not just about technology, but about responsible use.
For most organizations, it doesn't start with AI. It starts with structure. And once that's in place, AI becomes not just possible - but also value-creating.
If you want to delve more into the rules, you can read more at The Digitalization Authority here
Do you want to put the talk into practice?
We will hold a networking meeting on May 20, where we will delve into how AI can be used in HR setup with a focus on structure, data and responsible use.
Mere fra Mindkey
Where is HR headed?
HR is in the midst of the biggest role change in decades. Not because technology forces it - but because expectations do. Management will have strategic sparring. Employees expect personalized experiences. And legislation requires documentation that manual processes can never provide in sufficient quality. In this post, we look at where HR is going and what it takes from the systems and practices you are building on today.
AI in HR: From Opportunities to Responsible Application
In practice, it is at least as much about data, structure and workflows as it does about the technology itself. Without a clear foundation, AI risks creating more complexity than value. At the same time, it is crucial to choose solutions that work responsibly with data and meet the requirements of the AI Regulation. Only when it all comes together does AI really start freeing up time in a way that lasts in practice.
AI in HR: How to work responsibly with AI
AI is taking up more and more space in HR — but how do we use it responsibly? With the EU's AI Regulation, understanding how AI is applied in practice - from recruitment to salary transparency - becomes crucial.