DigComp 3.0: what changes compared to DigComp 2.2

A deep update, not a structural one

Anyone who knows DigComp expects every new version to mean relearning the scaffolding. With DigComp 3.0, published by the Joint Research Centre in 2025, that is not the case: the architecture is the same one that curricula, self-assessment tools and certification schemes across Europe were built on.

The 5 competence areas and 21 competences remain. If you mapped your training offer to DigComp 2.2, you do not have to redo that work from the ground up.

Where the change is

The leap is in granularity. DigComp 3.0 brings the learning outcomes to 523, against the few hundred examples of knowledge, skills and attitudes in the previous version. That changes how the framework is used:

• Course design: finer learning outcomes let you build modules around specific objectives instead of whole competences.
• Assessment: 523 learning outcomes are a solid base for test items traceable to a European reference.
• Comparison: more granularity means more precise mappings onto ESCO and national frameworks.

Artificial intelligence enters the framework

The most visible difference is in the content. DigComp 3.0 fully integrates competences related to artificial intelligence, disinformation and interaction with algorithmic systems.

This is not a bolt-on area: AI competences are distributed across the existing ones. Evaluating the output of a generative system belongs to data and information literacy; recognising synthetic content belongs to digital content creation; understanding how an algorithm profiles a user belongs to safety.

That choice says something important: AI is not a separate competence to acquire after the others, it is a dimension running through every basic digital competence.

What to do in practice

If you work with DigComp, three concrete steps:

1. Do not redo the mapping from scratch. Areas and competences are stable: what you built holds.
2. Reread the learning outcomes. That is where the new material is, and where your learning objectives need realigning.
3. Check your AI coverage. If your pathway does not touch critical evaluation of generative systems and recognition of disinformation, it now has a gap.

Explore the 5 areas and 21 competences of DigComp 3.0, with every learning outcome navigable, on the DigComp portal at ExplorerHub.