UNESCO’s AI Competency Frameworks
We have contributed to the UNESCO Digital Week (1, 2) and its open call for the input: AI competency for students and AI competency for teachers (released on September 3-4, 2024), aligned with UNESCO’s work on the “Recommendation on the Ethics of Artificial Intelligence“. Current analysis indicates a critical policy gap: as of 2022, only 7 countries (representing <4% of UN member states) had implemented government-endorsed AI teacher training programs, demonstrating significant under-preparation in global education systems for AI integration.
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AI Competency Framework for Teachers (AI CFT)
The UNESCO AI Competency Framework for Teachers comprises a total of 15 defined competencies, categorized into five primary dimensions. These are structured hierarchically across three progression levels—Acquire, Deepen, and Create—which support a tiered developmental model to guide teacher education and capacity-building.
The five dimensions cover key areas required for AI fluency in educational contexts. Approximately 20% of the competencies fall under the Human-Centred Mindset, which emphasizes teacher agency and digital responsibility. The Ethics of AI serves as the regulatory backbone, focusing on privacy, accountability, and ethical alignment. The AI Foundations and Applications dimension provides the technical grounding essential for understanding AI systems and their operational mechanisms. AI Pedagogy addresses the application of AI tools within teaching methodologies, while AI for Professional Development supports ongoing educator learning, upskilling, and reflective practice.
Progression is mapped through three competency levels. At Level 1 (Acquire), educators are expected to achieve foundational understanding. Level 2 (Deepen) requires the ability to integrate AI into teaching and learning practices. Level 3 (Create) encompasses leadership roles, curriculum innovation, and the ability to contribute to systemic educational change through AI.
AI Competency Framework for Students
The student framework, developed in parallel with the teacher framework, contains 12 measurable competencies divided across four primary dimensions: Human-Centred Mindset, Ethics of AI, AI Techniques and Applications, and AI System Design. These are uniformly distributed, each constituting 25% of the total competency structure. This symmetry supports balanced competency development across ethical reasoning, technical literacy, design capability, and agency in AI interactions.
The student competencies are developed along three phases. The Understand stage establishes conceptual foundations; the Apply stage introduces operational proficiency through hands-on experience; and the Create stage fosters innovation, including the ability to design and evaluate AI systems. The framework is scalable across multiple educational levels and adaptable to age-specific learning outcomes.
Statistical Context and Implementation Data
As of 2022, only 7 out of 193 UN member states (approximately 3.6%) had implemented an AI competency framework or teacher training programme, highlighting a significant global preparedness gap. Furthermore, fewer than 15 countries had integrated AI-related learning objectives into their national curricula for students. These figures indicate that over 95% of global education systems lack formal AI integration mechanisms.
Both frameworks are scheduled for phased deployment beginning in September 2024, with the aim of supporting international policy harmonization in AI literacy and digital education.
Competency Assessment Metrics
The AI CFT for teachers defines 15 measurable competencies across five dimensions, each evaluated at three progression levels, resulting in 45 distinct assessment criteria. The student framework mirrors this structure with a 4×3 matrix, yielding 36 measurable indicators. Collectively, the two frameworks present 81 standardized parameters for evaluating AI-related competencies in educational contexts.
These metrics enable quantitative tracking of competency acquisition, support cross-national comparability, and facilitate educational research into AI integration outcomes.
Implementation Variables and Outcomes
Quantitative benefits include projected time savings of 30–50% in administrative processes through automation, as well as enhanced capacity for personalized learning via AI-driven analytics. AI tools can also support scalable assessment and provide accommodations for learners with special needs through assistive technologies.
In terms of risk management, both frameworks incorporate guidelines aligned with GDPR and equivalent data protection standards, with an emphasis on algorithmic transparency and bias mitigation. Human oversight is mandated across implementation phases to ensure accountability and trustworthiness in educational AI systems.
Projected Implementation Timeline
Deployment is envisioned in three stages:
Phase 1 (2024–2025): Global dissemination and initial policy adoption.
Phase 2 (2025–2027): Integration into national curricula and teacher training rollouts.
Phase 3 (2027–2030): Full-scale implementation and monitoring through formal assessment mechanisms.
The frameworks represent the first globally standardized instruments for defining and measuring AI competencies in education. With applicability across all 193+ UN member states, they are poised to impact approximately 1.5 billion students and over 75 million educators worldwide. Current global readiness, estimated at less than 4%, indicates a potential for over 96% improvement in institutional preparedness.
By establishing evidence-based metrics for both learning and teaching AI competencies, UNESCO’s frameworks offer a foundation for empirical research, cross-national benchmarking, and longitudinal policy analysis in the field of digital education and AI literacy.
Updated: This work parallels the ongoing cooperation between the European Commission and OECD on the Draft AI Literacy Framework” (1) (scheduled for release in 2025-2026) and supports compliance with the EU AI Act's Article 4 requirements for AI literacy (implementation 2025-2027).
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References
¹ UNESCO. "AI competency framework for teachers." UNESCO. August 2024.
² UNESCO. "AI competency framework for students." UNESCO. October 2024.
³ UNESCO. "What you need to know about UNESCO's new AI competency frameworks for students and teachers." September 18, 2024.
⁴ UNESCO. "Digital Learning Week 2024." UNESCO Headquarters, Paris. September 2-5, 2024.
⁵ CEDEFOP (European Centre for the Development of Vocational Training). "UNESCO AI competency framework for teachers." November 14, 2024.
⁶ CEDEFOP (European Centre for the Development of Vocational Training). "UNESCO AI competency framework for students." November 14, 2024.
⁷ INEE (Inter-agency Network for Education in Emergencies). "AI competency framework for students." 2024.
⁸ Teacher Task Force. "UNESCO Digital Learning Week 2024." September 2024.
⁹ UNESCO. "Digital Learning Week 2024 - Speakers' biographies." September 2, 2024.
¹⁰ United Nations. "Digital Learning Week 2024 / La Semaine de l'apprentissage numérique 2024." Indico.UN. September 2-5, 2024.