AI in Digital Asset Management: facial recognition, security and privacy

AI facial recognition in Digital Asset Management?

AI in Digital Asset Management (DAM) makes it possible to automatically analyse, structure and make large volumes of visual content searchable. One of the most valuable applications within this is facial recognition.

This technology detects and recognises people in images, and groups images based on visual characteristics. This makes it possible not only to find content more quickly, but also to organise it more consistently — without manual tagging.

In practice, this means that users can retrieve all images of a specific person in a matter of seconds, even within archives containing thousands or millions of assets. What used to be a time-consuming and error-prone process is thus transformed into an automated and scalable workflow.

For marketing, communications and content teams, this translates into greater efficiency, better structure and, above all, immediate access to relevant content when it is needed.

But that speed is only one side of the story.

Why this is a sensitive technology

Facial recognition involves personal data. And therefore concerns privacy, consent and trust.

This means that this technology is not simply ‘just another feature’. It requires clear decisions regarding:

• What data you process
• How long you retain data
• Who has access to what information
• How transparent you are about processing
• How you comply with relevant legislation and guidelines (GDPR, EU AI Act, etc.)

AI is capable of a great deal, but that does not mean that everything is automatically desirable.

Security & data protection by design – approach

Within our DAM platform, AI is not a standalone feature, but part of a security-first architecture.

In concrete terms, this means:

1. Data minimisation: We process only the data necessary for the functionality.

2. Secure processing: All data is processed within controlled and secure environments.

3. Access control: Not everyone has access to the same information. Roles and permissions determine what is visible.

4. Transparency: We make it clear how AI functionalities work and what data is involved.

5. Control for customers: Organisations retain control over how and whether AI functionalities are used.

AI, privacy policy en compliance

When developing AI functionalities, we look beyond technology alone. That is why we also embed these features within our broader governance structure, including:

• AI policy
• Data processing agreements
• Privacy policy
• Security and compliance frameworks

Because a feature that is not secure, transparent and legally compliant is not a sustainable feature.

Responsible innovation with AI

The power of AI lies not only in what the technology can do, but above all in how it is applied.

Within Digital Asset Management solutions, AI facial recognition opens the door to huge efficiency gains. Content becomes searchable more quickly, workflows are simplified and large image libraries are finally organised.

But precisely because this technology is so powerful, it demands a well-considered approach.

That is why we consciously opt for an approach that puts innovation at the centre, but never separates it from responsibility. Privacy and security are not an afterthought or a final check in the process, but a starting point. From the very first design, we take into account how data is processed, who has access and how transparency is guaranteed.

Because the true value of AI lies not only in speed or automation. It arises when technology is built with a focus on security, compliance and trust.

In enterprise software, this is not a nuance, but a fundamental principle: