National professional development programme led by the UAE Ministry of Education and delivered in partnership with the Emirates College for Advanced Education to equip teachers and school leaders to integrate AI into teaching, assessment and school practice. It builds practical capability across seven curriculum-aligned AI areas, including AI foundations, data and algorithms, ethical use, classroom applications and innovation. Launched at GITEX Global 2025, scaling to train 5,000 educators.
Initiative overview
The Horizons Program addresses a system-level challenge arising from the rapid integration of artificial intelligence (AI) into education without a structured framework to guide safe and effective adoption. As AI tools become increasingly accessible, many educators currently lack clear national guidance on how to use AI safely and effectively in teaching, assessment, and school operations. Without a coordinated national approach, AI use in schools risks becoming fragmented, inconsistent, and uneven in quality. The programme therefore establishes a shared national framework that promotes equitable access, common standards, and responsible innovation, while strengthening digital readiness and positioning schools within a data-informed education system.
The programme’s primary objectives are to build practical AI competencies among teachers and school leaders, improve instructional quality and assessment design, and strengthen data-informed decision-making at school level. It prioritises applied classroom integration over theoretical awareness, enabling educators to design AI-supported lessons, enhance differentiation, streamline assessment processes, and embed ethical and responsible technology practices. It also strengthens leadership capacity to govern AI implementation in alignment with national professional standards and digital transformation priorities.
Implementation follows a phased national model supported by certified trainers, structured pre–post evaluation mechanisms, and continuous quality assurance monitoring. This approach ensures consistency across regions while enabling evidence-based refinement. Over time, the programme is designed to be embedded within formal professional development systems and institutional training frameworks, supported by policy guidance and competency standards. As it scales, the initiative will expand to additional educator groups, introduce differentiated specialisation pathways, and establish communities of practice to sustain impact. Future development will deepen integration with curriculum implementation, school improvement planning, and advanced data use. Through structured institutionalisation and sustained capacity building, the programme moves beyond isolated training towards coherent, responsible, and system-wide AI integration that strengthens learning outcomes and long-term education resilience.
Other relevant details
Results, outcomes and impacts: Batch 1 evaluation (October 2025, ECAE) showed measurable learning gains: average pre-assessment scores increased from 6.3/10 to 8.8/10 (+2.5 points), with proficiency defined at ≥80%. Participants reported very high satisfaction with knowledge gained, trainer performance and learning materials, and most recommended the programme (9–10/10). Results were measured using standardised pre/post assessments, attendance and completion records, participant surveys and quality assurance observations. The programme is scaling nationally to reach 5,000 educators by end-2026.
Challenges and lessons learned: Delivering AI professional development at national scale required deliberate alignment between instructional quality, infrastructure readiness, and consistent facilitation standards across regions. Variations in internet connectivity, access to licensed AI tools, and differing levels of digital maturity at school level affected the continuity of post-training implementation. Scaling delivery also required continuous calibration of trainer performance and refinement of AI tool integration depth to ensure consistent learning experiences and outcomes. The initiative addressed these challenges through phased implementation, unified delivery standards led by certified trainers, structured pre–post assessment mechanisms, and strengthened quality assurance monitoring. Early cohorts showed different levels of digital and teaching readiness, highlighting the need for structured, practice-based learning and tailored support to build authentic applied capability rather than theoretical awareness.
Additional insight: The Horizons Program represents a structured national model for governing artificial intelligence adoption within the education sector. It integrates professional capacity building with quality assurance systems, defined proficiency benchmarks, ethical safeguards, and regional performance monitoring into a coherent and scalable implementation framework. Rather than operating as a standalone training initiative, the programme embeds structured pre–post measurement, comparative regional analytics, and forward-looking risk assessment to inform strategic decision-making and continuous refinement. This evidence-based approach enables policymakers to monitor impact, identify targeted improvement areas, and ensure consistency of delivery across multiple regions and cohorts. The initiative demonstrates how governments can transition from exploratory AI adoption towards structured, standards-aligned, and accountable implementation within a core public function. By aligning competency development with governance oversight, ethical principles, and institutional quality controls, Horizons moves beyond experimentation and establishes measurable performance benchmarks linked to system-level objectives.
