prEN 18274

SLOVENSKI STANDARD
01-december-2025
Zahteve glede usposobljenosti za poklicne strokovnjake za etiko umetne
inteligence
Competence requirements for professional AI ethicists
Kompetenzanforderungen für KI-Ethiker
Exigences en matière de compétences pour les spécialistes en éthique de l'IA
Ta slovenski standard je istoveten z: prEN 18274
ICS:
03.100.02 Upravljanje in etika Governance and ethics
03.100.30 Vodenje ljudi Management of human
resources
35.240.01 Uporabniške rešitve Application of information
informacijske tehnike in technology in general
tehnologije na splošno
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

EUROPEAN STANDARD DRAFT
NORME EUROPÉENNE
EUROPÄISCHE NORM
September 2025
ICS 03.100.02; 03.100.30; 35.240.01

English version
Competence requirements for professional AI ethicists
Exigences en matière de compétences pour les Kompetenzanforderungen für KI-Ethiker
spécialistes en éthique de l'IA
This draft European Standard is submitted to CEN members for enquiry. It has been drawn up by the Technical Committee
CEN/CLC/JTC 21.
If this draft becomes a European Standard, CEN and CENELEC members are bound to comply with the CEN/CENELEC Internal
Regulations which stipulate the conditions for giving this European Standard the status of a national standard without any
alteration.
This draft European Standard was established by CEN and CENELEC in three official versions (English, French, German). A
version in any other language made by translation under the responsibility of a CEN and CENELEC member into its own language
and notified to the CEN-CENELEC Management Centre has the same status as the official versions.

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Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and United Kingdom.

Recipients of this draft are invited to submit, with their comments, notification of any relevant patent rights of which they are
aware and to provide supporting documentation.Recipients of this draft are invited to submit, with their comments, notification
of any relevant patent rights of which they are aware and to provide supporting documentation.

Warning : This document is not a European Standard. It is distributed for review and comments. It is subject to change without
notice and shall not be referred to as a European Standard.

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© 2025 CEN/CENELEC All rights of exploitation in any form and by any means
Ref. No. prEN 18274:2025 E
reserved worldwide for CEN national Members and for
CENELEC Members.
Contents Page
European foreword . 3
Introduction . 4
0.1 General . 4
0.2 Use of this standard . 4
1 Scope . 5
2 Normative references . 5
3 Terms and definitions . 5
4 Overview . 6
4.1 The role of AI ethicists . 7
4.2 Tasks of AI ethicists . 7
4.3 Approach . 8
4.4 Demonstration of competence . 9
4.5 Structure of this document . 9
5 AI ethics related governance competence . 10
5.1 Competence: AI ethics awareness, education and training . 10
5.2 Competence: Stakeholder management . 10
5.3 Competence: Distinguishing ethical and legal concerns . 11
5.4 Competence: Communication . 12
5.5 Competence: Resource management . 13
6 AI system life cycle related competence . 14
6.1 Competence: AI ethics implementation . 14
6.2 Competence: Ethical and societal impact assessment . 15
6.3 Competence: Ethics-based auditing . 16
6.4 Competence: Documentation and process quality . 16
6.5 Competence: Ethical reasoning . 17
6.6 Competence: Ethical mediation . 18
7 Attitudes . 19
Annex A (informative) Relationship with other standards . 21
A.1 Introduction . 21
A.2 CEN/TS 17834:2022 [7] European Professional Ethics Framework for the ICT
Profession . 21
A.3 CEN/TR 16234-2:2021 [8] - e-Competence Framework (e-CF) . 21
A.4 ISO/IEC TR 24368:2022 [9] - Information technology — Artificial intelligence —
Overview of ethical and societal concerns . 22
A.5 ISO/IEC/IEEE 24748-7000:2022 [6] - Systems and software engineering — Life
cycle management — Part 7000: Standard model process for addressing ethical
concerns during system design . 22
A.6 ISO/IEC 42005:2025 [10] Information technology — Artificial intelligence — AI
system impact assessment . 23
A.7 ISO 37002:2021 [5] Whistleblowing management systems — Guidelines . 23
Annex B (informative) Integration of AI ethicists into organizations . 24
B.1 Introduction . 24
B.2 Internal integration . 24
B.3 External integration . 24
B.4 Integration across organizational types . 24
B.5 Key considerations for integration . 25
Bibliography . 26
European foreword
This document (prEN 18274:2025) has been prepared by Technical Committee CEN-CENELEC/JTC
21"Artificial Intelligence", the secretariat of which is held by DS.
This document is currently submitted to the CEN Enquiry.
Introduction
0.1 General
The design, deployment and governance of Artificial Intelligence (AI) technologies need to be
underpinned by a thorough consideration of ethical and societal issues. Prior to the integration of AI
systems into various domains, addressing potential ethical challenges and societal concerns is essential.
The pressing need to address these concerns has led to a growing demand for the integration of AI ethics
into AI projects. Among other things, this can be achieved by integrating a spècific professional role,
here named AI ethicist, to contribute to the organization's AI governance and throughout the entire AI
system life cycle. This role would provide critical expertise in navigating the complex ethical and societal
issues surrounding AI.
As the demand for the integration of AI ethics continues to grow, it becomes increasingly important to
establish a common understanding of the competencies required to fulfil this role. Without a
standardized set of criteria, organizations risk inconsistent and inadequate attention to AI ethics, which
can lead to unintended consequences and harm to individuals and society.
This document provides requirements and recommendations for the competencies of AI ethicists, which
influèncès the responsible design, development and governance of AI and creates value that helps to
achieve the organization’s objectives and promote a positive impact on society. This document is
intended to serve as a basis for the development of a cèrtification scheme.
0.2 Use of this standard
Clause 4 provides an overview of the standard, including its objectives, the methodology used in its
development and a review of the main tasks associated with the role of AI ethicists.
Clause 5 provides AI ethics related governance competence for AI ethicists, outlining relevant
knowledge and skills for each competence.
Clause 6 provides AI system related life cycle competence for AI ethicists, outlining relevant knowledge
and skills for each competence.
Annex A discusses the relationship between this document and other relevant standards in the fièld of
ethics and AI.
1 Scope
This document provides a systematized framework for the competencies of AI ethicists, categorizing
them into knowledge, skills and attitudes related to the spècific activities and tasks of the role. It
idèntifiès requirements and recommendations necessary for individuals to effectively perform as AI
ethicists. These competencies encompass a strong understanding of European values and fundamental
rights, further enhancing the knowledge, skills and attitudes required for this profession.
The document aims to foster a shared understanding of the essential concepts and principles inherent
to the AI ethicist role. It illustrates a clear, uniform approach to the integral components of this
profession.
Moreover, the document outlines how the role of AI ethicists can be seamlessly integrated into a wide
variety of organizations. These include, but are not limited to, commercial enterprises, governmental
agencies and non-profit organizations.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
For the purposes of this document, the following terms and dèfinitions apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— IEC Electropedia: available at http://www.electropedia.org/
— ISO Online browsing platform: available at http://www.iso.org/obp
3.1
competence
demonstrated ability to apply knowledge (3.2), skills (3.3) and attitudes for achieving observable results
[SOURCE: EN 16234-1:2019 [1], 3.4]
3.2
knowledge
outcome of the assimilation of information through learning
Note 1 to entry: Knowledge is the body of facts, principles, theories and practices that is related to a fièld of work
or study.
Note 2 to entry: In the context of the European Qualification Framework, knowledge is described as theoretical
and/or factual.
Note 3 to entry: In addition to learning, knowledge can be acquired through any other reliable process (e.g.
testimony, perception, inference).
[SOURCE: European Qualification Framework, Annex I, f]
3.3
skill
ability to apply knowledge and use know-how to complete tasks and solve problems
Note 1 to entry: In the context of the European Qualification Framework, skills are described as cognitive (involving
the use of logical, intuitive and creative thinking) or practical (involving manual dexterity and the use of methods,
materials, tools and instruments).
[SOURCE: European Qualification Framework, Annex I, g]
3.4
ethics
branch of philosophy concerning the normative principles of right and wrong conduct
3.5
AI ethics
branch of applied ethics (3.4), focusing on ethical issues raised by the design, development and use of AI
3.6
AI ethicist
professional with competence (3.1) in studying, analysing and providing guidance on the ethical
considerations, implications and practices related to artificial intelligence
3.7
code of ethics
set of principles and rules concerning moral obligations and regard for the rights of humans and nature,
which can be spècifièd by a given profession or group
3.8
attitude
consistent and demonstrable approach to work that rèflècts the values and behaviours expected from
a professional in a spècific context
3.9
ethical infrastructure
formal and informal systems, which communicate, monitor and reward ethical behaviour, or sanction
unethical behaviour within an organization
3.10
AI system
engineered system that generates outputs such as content, forecasts, recommendations or decisions
for a given set of human-dèfinèd objectives
Note 1 to entry: The engineered system can use various techniques and approaches related to artificial intelligence
to develop a model to represent data, knowledge (3.2), processes which can be used to conduct tasks
Note 2 to entry: AI systems are designed to operate with varying levels of automation
[SOURCE: ISO/IEC 22989:2022 [2] 3.1.4]
3.11
life cycle
lifecycle
evolution of a system, product, service, project or other human-made entity, from conception through
retirement
[SOURCE: ISO/IEC/IEEE 15288:2023 [3] 3.21]
3.12
governance
human-based system comprising directing, overseeing and accountability
[SOURCE: ISO/IEC 38500:2024 [4] 3.3]
4 Overview
4.1 The role of AI ethicists
AI Ethicists are professionals whose role is to contribute to the establishment, implementation,
maintenance and continual improvement of AI ethics (3.5) frameworks, guidelines and practices within
organizations. They should have and maintain knowledge (3.2), skills and attitudes required to identify,
evaluate and mitigate the ethical and societal risks and implications of AI systems and to support their
alignment with human values, principles and societal norms. They should also stay up-to-date with the
latest developments in AI research, technology and policy to fulfil their role successfully.
Integrating ethicists into teams represents a strategic advantage for organizations designing,
developing and using AI. AI ethicists help mitigate ethical and societal risks while promoting a proactive
approach to responsible innovation, which can translate into a competitive the advantage in today's
marketplace. The adoption of solid ethical principles can facilitate international cooperation, potentially
opening doors to new markets and partnerships.
Clarifying that AI ethicists serve primarily as advisors rather than judges of what is ethically correct is
relevant. Their role is to identify ethical considerations, facilitate informed discussions, provide
guidance on ethical frameworks and support decision-making processes. While they contribute
expertise on ethical matters, final ethical decisions remain the responsibility of organizational
leadership and relevant stakeholders. AI ethicists help organizations navigate the complex ethical
terrain of AI development and implementation, ensuring that technological innovation proceeds in an
ethically informed and responsible manner.
While, a moral deliberation shall be the outcome of an internal committee and never entrusted solely
to a single AI ethicist (3.6) or even a group of AI ethicists, the role of the AI ethicists shall be formalized
through a contract that ensures the necessary independence to perform their duties effectively.
Moreover, AI ethicists shall maintain strict confidèntiality regarding the information they handle on
behalf of the company. However, AI ethicists should also implement all necessary mechanisms to
safeguard whistle-blowers, in line with ISO 37002:2021 [5] and promote the relevance of system
experts, value leads, risk leads, user advocates, moderators and transparency managers as outlined in
ISO/IEC/IEEE 24748-7000:2022 [6].
The role of AI Ethicists may be known by various titles across different organizations and industries.
Alternative names for this role include, but are not limited to: AI Ethics Officèr, AI Ethics Consultant,
Ethical AI Strategist, AI Ethics Researcher, or AI Ethics and Compliance Manager, Responsible AI
Specialist. Other names, such as AI Risk Management Specialist and AI Governance Expert, may share
some of the competences of this role, though their primary focus may differ. Roles involving the term
responsible AI fall under the umbrella of AI ethics (3.5), as responsibility is inherently an ethical concept.
4.2 Tasks of AI ethicists
Within an organization, an AI ethicist (3.6) should be capable of carrying out the following tasks listed
in Table 1, each of which inherently involves an ethical dimension.
Table 1
Task Description
Ethical trade-off management identifying and analysing competing priorities and
values throughout the life cycle (3.11) of AI
technologies, prioritizing and weighing the pros and
cons of different options
Ethical evaluation identifying potential ethical and societal concerns and
risks associated with AI technologies, applications and
practices
Ethical dimensions of policy analysis reviewing, evaluating and providing recommendations
on AI-related guidelines and standards.
NOTE Attention is drawn to regulations that can
apply.
Task Description
Ethical mediation facilitating discussions and resolve conflicts on ethical
matters in AI development, deployment and usage
AI ethics implementation implementing guiding principles and practices that
govern the ethical development, deployment and use of
AI technologies, aligned with the organization's code of
ethics (3.7)
Ethical frameworks development developing ethical guidelines for the design,
development and implementation of AI technologies to
steer corporate decisions and practices towards ethical
and responsible solutions
Research on AI ethics participating in research projects, publishing peer-
reviewed papers and attending conferences to stay
updated on AI ethics-related topics
AI ethics training designing, developing and delivering educational
programs, workshops, training, or courses to improve
understanding of ethical and societal issues in AI among
organization’s employees
AI ethics awareness building awareness among employees on ethical issues
through workshops, seminars and training programs to
create a conscious and responsible organizational
culture
Ethical communication communicating AI ethics-related information, insights
and recommendations to internal and external
stakeholders
The responsibilities outlined in Table 1 are examples and do not encompass the full range of activities
undertaken by AI ethicists in all organizations. The spècific roles and tasks of AI ethicists can vary
significantly depending on the organization’s size, industry, context and the nature of its AI models.
Organizations retain complete discretion in determining the responsibilities and scope of work for their
AI ethics function.
4.3 Approach
This standard is based on a competence-based approach. Each competence (3.1) is broken down into
its constituent knowledge (3.2), skills and attitudes. Attitudes, while not separately listed for each
competence (3.1), are considered longitudinal and integral to all competences. Although this approach
is aligned with the European Qualification Framework, this document does not specify any levels of
proficièncy for each spècific competence (3.1).
This standard is designed as an enabler, aiming to empower AI ethicists rather than impose restrictions.
It provides a flèxiblè framework that can be adapted to various contexts and needs. It provides a
competence (3.1) framework that can be applied by a wide range of users, including organizations in
the private and public sector, AI companies, educational institutions and individuals.
The competences described in this standard are designed to be durable, i.e. they remain valid over time
and can be transferred to other related fièlds, even as AI technology, job roles and marketing terminology
evolve rapidly.
These competences can be aggregated to represent the essential content of a job role or profilè (as in
the present document), but they can also be applied to multiple job profilès. Competences are not the
same as particular tasks. Rather, competences are the crucial elements that enable the successful
performance of tasks across various scenarios.
This standard does not aim to exhaustively cover all possible competences of an AI ethicist (3.6), nor
are all included competences unique to AI ethics (3.5). The selection of competences for inclusion in
this standard was based on engagement with stakeholders such as commercial enterprises, government
agencies, NGOs and Consumer Associations, who prioritized competence (3.1) inclusion based on
industry knowledge (3.2) and experience. While focusing on AI èthics-spècific competences, this
standard acknowledges the importance of more generic competences that are already well-articulated
in other professional frameworks.
Figure 1 shows the approach to competence (3.1) adopted in this standard.
Figure 1 — Approach to competence
Table 2 is the template used to present each competence (3.1). Table 2 outlines the intended outcomes,
knowledge (3.2) requirements and skills requirements associated with the competence (3.1) of AI
ethicists. Each row of Table 2 provide the following information:
— Intended outcomes: These describe the anticipated results when AI ethicists possess the
necessary competence (3.1) and apply it in practice.
— knowledge (3.2) requirements: This row lists the knowledge (3.2) elements essential for
effectively applying the competence (3.1) and achieving the intended outcomes.
— Skills requirements: This row lists the skill (3.3) sets required to apply the competence (3.1) and
achieve the intended outcomes.
Table 2
Intended outcomes
Knowledge required
Skills required
4.4 Demonstration of competence
For each competence (3.1), professional AI ethicists shall be able to demonstrate the following:
a) the relevant knowledge (3.2) in the corresponding Table 3, Table 4, Table 5, Table 6, Table 7, Table
8, Table 9, Table 10, Table 11, Table 12 demonstrated by the possession of educational and/or
professional qualifications and experience;
b) the relevant skills (3.3) in the corresponding Table 3, Table 4, Table 5, Table 6, Table 7, Table 8,
Table 9, Table 10, Table 11, Table 12 demonstrated the ability to carry out the managerial or
technical tasks.
4.5 Structure of this document
This document outlines the competences required for professional AI Ethicists structured into two
categories: AI governance (3.12) related competences and life cycle (3.11) related competences.
AI related governance competences (Clause 5) refer to the knowledge (3.2), skills and attitudes required
to successfully carry out AI governance related activities, including developing policies, procedures and
standards for responsible AI development, deployment and use.
Life cycle (3.11) related competences (Clause 6) refers to the knowledge (3.2), skills (3.3) and attitudes
(3.8) required to integrate ethical and societal considerations into the entire AI system (3.10) life cycle
(3.11), from design and development to deployment, maintenance and retirement.
Clause 7 presents a list of attitudes recommended for professional AI Ethicists.
Annex A and Annex B provide additional information. Annex A analyses the relationship between this
document and other standards related to AI ethics (3.5). Annex B explains how AI ethicists can be
integrated in different organizational contexts.
5 AI ethics related governance competence
5.1 Competence: AI ethics awareness, education and training
To accomplish their roles in an organization professional AI ethicists shall acquire, keep up-to-date
and demonstrate competence (3.1) with respect to AI ethics (3.5) governance (3.12).
The intended outcomes, knowledge (3.2) requirements and skills requirements associated with the AI
ethics (3.5) awareness, education and training competence (3.1) are presented in Table 3.
Table 3
Intended outcomes cultivating an environment where ethical reasoning can
flourish, promoting a strong ethical culture within the
organization and ensuring that employees have the
necessary knowledge (3.2) and skills to identify,
evaluate and address ethical challenges related to AI
Knowledge required — ethical frameworks and principles applicable to AI
— adult learning theories and principles
— instructional design and development
— evaluation methods and evaluation techniques
— organizational learning and development
practices
— normative ethics and ethical theories that
underlay discussions about AI
— ethical and societal implications of AI and how it
affects different groups of people within society
Skills required — design and develop curricula
— communication and presentation skills
— analysis and evaluation skills
5.2 Competence: Stakeholder management
The intended outcomes, knowledge (3.2) requirements and skills requirements associated with the
stakeholder management competence (3.1) are presented in Table 4.
Table 4
Intended outcomes identifying, engaging and managing relationships with
key stakeholders (internal and external) to align
interests, address concerns and build trust in AI models,
promoting ethical and responsible AI design,
development and deployment
Knowledge required — stakeholder analysis and mapping techniques
— stakeholder engagement strategies
— associations and organized stakeholders (for
consumers, workers, children, gender)
— conflict management strategies
— an understanding of transparency and
accountability obligations and procedures
between internal stakeholder and between
internal and external stakeholders
Skills required — analyse and evaluate organizational culture
— manage and resolve conflicts among stakeholders
with differing interests
— negotiate to achieve ethical objectives
— establish and maintain strong relationships with
stakeholders based on trust and mutual respect.
— identify and address stakeholder needs and
challenges
— enable, advocate for and practice appropriate
transparency procedures and standards
...