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Mapping Digital Maturity with DigComp 3.0
The strategic evolution of MapUs’ Digital Competence Wheel
The release of the DigComp 3.0 framework in December 2025 marks an important development for digital competence work in modern organisations. This fifth edition of the European Digital Competence Framework offers a common language for digital competence and digital maturity, helping organisations, institutions and businesses connect individual capabilities with strategic development needs.
At MapUs, we have developed a new competence wheel based on DigComp 3.0 to help organisations navigate an increasingly complex technological landscape. The wheel translates the framework into practical competence statements that can be used for mapping, reflection, dialogue and targeted development.
From framework to practice
The competence wheel makes abstract concepts concrete by turning digital competence into visible patterns, shared language and actionable development priorities.
The Competence Wheel made abstract concepts concrete, discovering we are stronger than we thought.
- Library Manager Dorte Rugtved, Bornholm Public Libraries, 2026A competence wheel with integrity
A defining feature of our DigComp 3.0 competence wheel is the integration of artificial intelligence-related questions across the competence model. This reflects the DigComp 3.0 approach, where AI competence is integrated across all twenty-one competences instead of being treated as a separate specialist area.
This also makes the competence wheel relevant in relation to the EU Artificial Intelligence Act. Article 4 requires providers and deployers of AI systems to take measures to ensure, to the best of their ability, a sufficient level of AI literacy among staff and other persons dealing with the operation and use of AI systems on their behalf.
The competence wheel supports this work by making AI literacy part of broader digital maturity. Instead of treating AI as an isolated technical skill, the model connects AI-related questions to information evaluation, communication, content creation, safety, wellbeing and problem solving.
To support validity and meaningful self-reflection, the questions are formulated as concrete competence statements. Many of them use an “I can...” structure, which helps respondents reflect on their perceived ability to solve specific tasks. This approach is useful when the goal is not simply to test knowledge, but to create a shared basis for dialogue, development and prioritisation.
Built on DigComp 3.0
The competence wheel is structured around the official DigComp 3.0 framework and its five competence areas and twenty-one competences.
AI literacy across competences
AI-related competence is integrated across the model instead of being treated as a separate technical skill.
Self-reflection and action
Questions are formulated as concrete competence statements that support reflection, dialogue and targeted competence development.
Collective overview
Results help organisations understand both individual development needs and collective strengths across teams and departments.
Operationalising competence areas and learning outcomes
Translating a theoretical framework into a practical competence wheel requires a detailed approach. DigComp 3.0 provides a more granular view of digital competence through updated competence statements and learning outcomes. These make it possible to describe knowledge, skills and attitudes in ways that can be translated into practical assessment and development tools.
In MapUs, these ideas are transformed into competence statements and survey questions that investigate how people understand, use and reflect on digital technologies in practice. The method is structured around the five DigComp 3.0 competence areas:
Information search, evaluation and management
Finding, evaluating and managing information and data in digital environments.
Communication and collaboration
Interacting, sharing, collaborating and managing digital identity responsibly.
Content creation
Creating, adapting and integrating digital content with attention to rights and licences.
Safety, wellbeing and responsible use
Protecting devices, data, privacy, wellbeing and the environment.
Problem identification and solving
Identifying needs, solving problems, adapting technologies and developing competence.
Partnerships and collaborations
The quality of the competence wheel depends not only on its theoretical foundation, but also on how it works in real organisational contexts. For this reason, the wheel has been developed and tested through partnerships and collaborations.
The English competence wheel was developed in collaboration with partners at ReDI School of Digital Integration, a European organisation dedicated to inclusive digital education. This collaboration helped ensure that the language of the wheel is accessible, inclusive and understandable across different backgrounds.
The Danish version was tested in collaboration with Bornholm Public Libraries to ensure that the content remains relevant to the digital infrastructure, workplace practices and cultural values of a Danish organisational context.
Inclusive language
The English version was developed and tested with attention to accessible and inclusive language.
Workplace relevance
The Danish version was tested in a workplace context to ensure relevance to everyday digital tasks and organisational development.
Shared understanding
The mapping helps move conversations from individual assumptions to a shared picture of collective digital maturity.
The mapping moved the conversation from what we can do as individuals to where we stand as a collective. We have gained a much clearer understanding of where we thrive, where we can support each other, and pinpoint where our colleagues need targeted training to address and solve community challenges.
- Lill Henschen, ReDI School of Digital Integration, 2026Actionable oversight and collective understanding
Management needs clear, action-oriented insight rather than general statements or overly complex technical data. The competence wheel therefore translates mapping results into autonomy profiles that are easier to understand and act upon.
The four profiles are defined by task complexity and the degree of independence required to solve digital tasks:
Beginner
Can perform simple tasks with guidance.
Intermediate
Can handle routine tasks independently.
Advanced
Can solve complex tasks and adapt technology use.
Expert
Acts as a strategic resource who can lead initiatives and guide others.
This hierarchy helps management identify areas in need of training, while also making it possible to identify digital frontrunners who can support internal learning among colleagues. The result is not simply a score, but a shared understanding of where the organisation is strong, where it is vulnerable and where development will create the most value.
Targeted competence development and digital maturity
Understanding the collective strengths and weaknesses of the workforce is the first step towards a successful digital transformation. A DigComp 3.0-based competence wheel gives organisations a structured way to understand digital maturity, prioritise training and connect competence development with strategic goals.
The result is a more precise basis for planning learning initiatives, supporting employees, documenting development needs and strengthening the organisation’s capacity to use digital technologies responsibly and effectively.
Sources
- Cosgrove, J. & Cachia, R. (2025). DigComp 3.0: European Digital Competence Framework. Publications Office of the European Union.
- European Commission, Joint Research Centre. DigComp 3.0 overview.
- European Commission, Joint Research Centre. Digital Competence Framework for Citizens.
- Vuorikari, R., Kluzer, S. & Punie, Y. (2022). DigComp 2.2: The Digital Competence Framework for Citizens. Publications Office of the European Union.
- Clifford, I. et al. (2020). DigCompSAT: A Self-reflection Tool for the European Digital Competence Framework for Citizens. Joint Research Centre.
- Kluzer, S. et al. (2020). DigComp at Work: The EU’s digital competence framework in action on the labour market. Joint Research Centre.
- European Parliament and Council of the European Union (2024). Regulation (EU) 2024/1689, Artificial Intelligence Act.
- European Commission. AI literacy questions and answers.
- European Commission. Digital Education Action Plan 2021-2027.
- Cedefop (2022). Defining, writing and applying learning outcomes: A European handbook.
- International Test Commission and Association of Test Publishers (2022). Guidelines for Technology-Based Assessment.
- UNESCO (2024). AI competency framework for students.