AI shifts from competitive edge to key competence for researchers

ResearchComp update highlights the need for researchers across all fields to understand the uses, limitations, and risks of the technology

Daniel Dieb

A person sits in front of two computer screens in an indoor environment, with their back to the camera. The image shows the use of digital technologies for professional or research activities.

The European Commission recently updated ResearchComp, its standardized competence framework for understanding, assessing, and developing the transversal skills needed by researchers in academia, industry, and the public sector. The framework now includes artificial intelligence (AI) as one of its 39 core competences.

The update, part of the European Commission’s Strategy for AI in Science, was published on the institution’s official research and jobs portal.

With this change, the ability to leverage AI is no longer just a technical advantage—it is now part of the skillset expected of all scientists, from early-career researchers to scientific and institutional leaders.

Institutions and funding agencies adopting the ResearchComp framework (which is voluntary) may apply it to activities ranging from the selection of fellowship recipients to the evaluation of research groups.

Four levels of proficiency

ResearchComp lists four progressive levels of AI competence: foundational, intermediate, advanced, and expert. Within these levels, skills range from a conceptual understanding of the technology’s applications and limitations to the ability to formulate institutional policies governing its use.

ResearchComp’s four levels of AI competence

Foundational: Understands what AI is and its applications in research. Recognizes its benefits, limitations, and ethical implications, and shows a willingness to learn more about the technology.
Intermediate: Can assess which AI tool is best suited to a given research task and uses existing solutions to support tasks such as data visualization, predictive analytics, and literature reviews.
Advanced: Develops customized AI solutions for complex challenges (such as advanced simulations, automated experimentation, and data collection). Sets guidelines for responsible use of AI and collaborates with experts in the field.
Expert: Formulates ethics policies and guidelines for AI use. Mentors other researchers and identifies innovative solutions with the potential to transform research practices.

Ethics as a guiding principle

Ethical issues surrounding the use of AI are relevant across all four proficiency levels. At a foundational level, researchers are expected to recognize the ethical implications and challenges of using the technology; at expert level, they are challenged with creating and applying guidelines to ensure responsible and equitable practices. Progression through the framework therefore requires not only technical expertise, but also institutional responsibility.

In addition to AI, ResearchComp groups other competencies into seven major areas: cognitive abilities, conducting research, managing research, managing research tools, making an impact, working with others, and self-management.

The framework’s 39 competences include data management, open science, citizen science, and scientific integrity.

Any researcher, including Brazilians, can access ResearchComp’s online self-assessment tool, also developed by the European Commission.

The tool allows users to identify their own level in each of the seven areas of competence by answering a multiple-choice questionnaire. The results can then be used to identify training gaps and guide professional development.

ResearchComp and the self-assessment tool are available free of charge on the European Commission’s website: ResearchComp — European Competence Framework for Researchers.

A direct link to the tool is also available on the website.

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