AI Education
Standard

AIRI's AI Education Standard is grounded in UNESCO's globally recognised AI Competency Frameworks, defining the knowledge, skills, and values required for responsible engagement with artificial intelligence in educational contexts.

Status: Published

Grounded in
UNESCO's Global Frameworks

AIRI's AI Education Standard is directly aligned with the two landmark AI Competency Frameworks published by UNESCO in August 2024: the AI Competency Framework for Students and the AI Competency Framework for Teachers. These frameworks represent the most comprehensive and internationally recognised guidance on AI literacy in education.

UNESCO's frameworks take a human-centred approach to AI in education, emphasising the enhancement of human capabilities, the promotion of social justice, sustainability, and human dignity. They are grounded in the 2021 UNESCO Recommendation on the Ethics of Artificial Intelligence and the 2019 Beijing Consensus on Artificial Intelligence and Education.

AIRI adopts these frameworks as the authoritative basis for its AI Education Standard, ensuring that our assessments are internationally credible, ethically grounded, and applicable across diverse national and institutional contexts.

Reference Framework

AI Competency Framework for Students

UNESCO, 2024 — Miao, Fengchun; Shiohira, Kelly; Lao, Natalie

12 competencies across 4 dimensions, 3 progression levels

Reference Framework

AI Competency Framework for Teachers

UNESCO, 2024 — Miao, Fengchun; Cukurova, Mutlu

15 competencies across 5 dimensions, 3 progression levels

UNESCO's Broader Policy Context

  • — Guidance for Generative AI in Education (2023)
  • — Recommendation on the Ethics of AI (2021)
  • — Beijing Consensus on AI and Education (2019)

Four Dimensions of
Student AI Competency

The UNESCO AI Competency Framework for Students outlines 12 competencies across four core dimensions. AIRI's AI Education Standard adopts this structure as the basis for student-level assessment, spanning three progression levels: Understand, Apply, and Create.

01

Human-Centred Mindset

Students develop the capacity to understand and assert their agency in relation to AI systems. This dimension emphasises the primacy of human rights, human flourishing, and the critical evaluation of AI's benefits and risks. Students learn to recognise AI as a tool that should serve human values, not replace human judgement.

Understanding the role of human agency in AI interactions
Critical evaluation of AI-generated content and decisions
Awareness of AI's societal impacts and power dynamics
02

Ethics of AI

Students acquire the knowledge and skills to engage with AI in a responsible, ethical manner. This dimension covers responsible use of AI, ethics-by-design principles, and safe practices. It addresses issues of fairness, transparency, privacy, accountability, and the potential for algorithmic bias.

Responsible and safe use of AI tools and platforms
Understanding of AI ethics principles (fairness, transparency, privacy)
Ethics-by-design thinking in AI applications
03

AI Techniques and Applications

Students build foundational knowledge of how AI systems work and how they are applied across domains. This dimension provides the technical literacy required to understand AI capabilities and limitations, including machine learning, natural language processing, computer vision, and other core AI techniques.

Foundational understanding of machine learning and AI algorithms
Knowledge of AI applications across sectors (healthcare, education, industry)
Understanding of data, its role in AI, and associated limitations
04

AI System Design

Students develop problem-solving, creativity, and design thinking skills in the context of AI. This dimension fosters the capacity to conceive, design, and evaluate AI-based solutions to real-world problems, with an emphasis on inclusive and sustainable design principles.

Problem-solving and design thinking applied to AI contexts
Prototyping and evaluating simple AI-enabled solutions
Inclusive and sustainable AI design principles

Five Competency Areas
for Educators

The UNESCO AI Competency Framework for Teachers outlines 15 competencies across five key areas. AIRI's standard adopts this framework to define what educators must know, be able to do, and value in the age of AI — across three progression levels: Acquire, Deepen, and Create.

01

Human-Centred Mindset

Teachers develop a mindset that prioritises human agency, accountability, and social responsibility in all AI-related educational activities. This area emphasises the teacher's role in modelling critical, reflective engagement with AI technologies.

02

Ethics of AI

Teachers acquire the capacity to promote ethical principles and responsible AI use within their classrooms and institutions. This includes understanding regulatory frameworks, institutional policies, and the practical ethical rules governing AI in educational settings.

03

AI Foundations and Applications

Teachers develop the knowledge, understanding, and skills needed to engage with and teach about AI technologies. This area covers the technical foundations of AI, its applications across disciplines, and the ability to evaluate AI tools for educational use.

04

AI Pedagogy

Teachers learn to leverage AI for innovative, effective teaching methods. This area addresses the integration of AI tools into pedagogical practice, the redesign of learning activities in light of AI capabilities, and the assessment of AI-assisted learning.

05

AI for Professional Development

Teachers develop the capacity to use AI as a tool for their own ongoing professional growth. This area covers the use of AI for reflective practice, personalised professional learning, research, and collaboration with peers.

Assessment Progression

Both frameworks define three progression levels that describe increasing depth of competency, from foundational understanding through to advanced creation and leadership.

Student Progression Levels

1

Understand

Students demonstrate foundational knowledge and conceptual understanding of AI across the four dimensions. They can explain key concepts, identify examples, and articulate the significance of AI in society.

2

Apply

Students demonstrate the ability to apply their AI knowledge and skills in practical contexts. They can use AI tools responsibly, evaluate AI outputs critically, and apply ethical reasoning to AI-related situations.

3

Create

Students demonstrate the capacity to design, develop, and evaluate AI-enabled solutions. They can engage as co-creators of AI systems, applying design thinking and ethical principles to produce innovative, responsible outcomes.

Teacher Progression Levels

1

Acquire

Teachers develop foundational knowledge and awareness across the five competency areas. They can identify AI tools relevant to their practice and articulate basic ethical and pedagogical considerations.

2

Deepen

Teachers demonstrate the ability to integrate AI competencies into their professional practice. They can design AI-enhanced learning experiences, apply ethical frameworks, and support student AI literacy.

3

Create

Teachers demonstrate leadership in AI education. They can develop innovative AI-integrated curricula, contribute to institutional AI strategy, and mentor colleagues in developing AI competencies.

Why AI is Distinct
from Other Digital
Technologies

UNESCO's frameworks — and by extension AIRI's standard — recognise that AI is fundamentally different from conventional information and communication technologies. AI poses unique ethical and social challenges, including issues of fairness, transparency, privacy, and accountability.

AI's unique ability to mimic human behaviour directly impacts human agency in ways that require dedicated competencies beyond the scope of traditional digital literacy. This is why AIRI treats AI education as a distinct and critical domain of standardization.

UNESCO's Policy Recommendations

Comprehensive Strategy: Integrate AI competency frameworks into a comprehensive national strategy for AI capacity building across all educational levels.
Universal Access: Ensure universal access to the internet and digital infrastructure as a prerequisite for meaningful AI education.
Ethical Design: Enforce ethical design principles for AI tools used in educational settings, protecting student rights and data.
Environmental Responsibility: Promote environmentally-friendly AI practices and raise awareness of AI's environmental footprint.
Systemic Investment: Avoid over-reliance on AI for systemic education challenges; sustained policy attention and investment remain essential.