How Prepared Are ASEAN’s Education Systems for an AI-Driven Future?

Southeast Asia is home to a population of over 661 million people. Approximately half are in their productive years, while one-third are under the age of twenty, positioning ASEAN as one of the youngest and most dynamic regions globally. The digital economy is projected to grow from US$300 billion to US$1 trillion by 2030, presenting substantial opportunities alongside increasingly complex risks. As the adoption of artificial intelligence (AI) accelerates across various sectors, the need for inclusive, responsible, and well-governed AI has become ever more urgent.

Education plays a central role in this transition, as it supports skills development, employment opportunities, and long-term social inclusion. The region’s capacity to responsibly integrate AI into educational frameworks will influence not only workforce preparedness but also the inclusivity and resilience of ASEAN’s digital transformation.

These themes framed the fireside discussion at the AI Ready ASEAN Research Dissemination: Advancing ASEAN Digital’s Future – Driving Digitalisation and AI Readiness for an Inclusive and Sustainable ASEAN, held in Manila on 9 February 2026. Policymakers, AI practitioners, and representatives from ASEAN Member States convened to examine how prepared the region’s education systems are for an AI-driven future.

The discussion drew on new research conducted under the AI Ready ASEAN programme, implemented by the ASEAN Foundation with support from Google.org. The study “Assessing Artificial Intelligence Readiness in ASEAN Educational Contexts”, to be published at the end of February, evaluates engagement with AI across three interrelated dimensions: personal readiness, institutional readiness, and ethical readiness.

Moderator and Speakers

• Citra Nasruddin, Programme Director at Tech For Good Institute,
• Pattarat Phantprasit, Researcher at the Science, Technology and Innovation Policy Institute (STIPI), King Mongkut’s University of Technology Thonburi
• Piyakul Somsiriwong, Researcher and Capacity Building and Training Specialist of the Science, Technology and Innovation Policy Institute (STIPI) at King Mongkut’s University of Technology Thonburi,
• Bank Ngamarunchot, Director of the Science, Technology, and Innovation Policy Institute (STIPI) at King Mongkut’s University of Technology Thonburi (KMUTT).

Key Takeaways

1. AI Readiness Is Already Emerging.
Across ASEAN countries, practical implementation of AI readiness is already taking shape. Preliminary findings from the AI Ready ASEAN study presented at the session reveal significant engagement with AI tools among students, educators, and parents, with students at the forefront of this adoption: 87% utilise AI for information searches, 75% for writing support. The attitudes toward AI are generally favourable among all three groups, reflecting a sense of openness rather than opposition.

Notably, the study indicates that a majority of respondents live outside capital cities and represent diverse income backgrounds, suggesting that engagement with AI extends beyond metropolitan and higher-income populations. However, uptake is progressing faster than institutional alignment.. While personal readiness scores are consistently high across countries, institutional readiness receives the lowest ratings. Fewer than half of educators report having adequate training, governance frameworks, or infrastructure. These findings underscore a growing gap between grassroots adoption and systemic readiness.

2. Confidence Must Be Matched by Capability.
Favourable attitudes toward AI across various stakeholder groups indicate increasing confidence in the utilisation of these tools. However, confidence alone does not translate to preparedness. A significant majority acknowledge academic misuse, such as submitting AI-generated essays as assignments. Meanwhile, broader risks including misinformation, manipulation, overreliance, and the ability to recognise AI-generated content receive comparatively less attention.Disparities in AI literacy exacerbate these risks: parents consistently score the lowest, and performance fluctuates across age groups and countries, with students often surpassing their educators. In a landscape where AI systems have the capability to produce convincing yet flawed or biased results, insufficient skills and critical judgement can lead to significant repercussions. Empowerment requires more than mere access and enthusiasm; it depends on structured guidance, enhanced critical thinking, and ongoing institutional support.

3. Ethics Are Foundational, Not Optional.
Ethical readiness is essential to integrating AI in education. Current considerations are often disproportionate, focusing narrowly on plagiarism while neglecting critical issues such as bias, misinformation, accessibility, and equitable participation. Institutional readiness is frequently assessed as the weakest area, with many educators reporting insufficient support in training, governance frameworks, and infrastructure.

Without intentionally integrating ethical principles into policy design, curriculum development, and capacity-building initiatives, AI adoption may exacerbate existing disparities across age groups, income levels, and national contexts. To ensure that AI produces fair and inclusive outcomes, ethics must be integrated from the start, not treated as an afterthought, but as a fundamental component of the education system’s architecture.

4. Progress Depends on Coordinated Action.
The research identified four critical gaps that require deliberate and coordinated responses:

(i) Agility gap: AI innovation is outpacing policy adaptation and educational reform.
(ii) Agency gap: Rising reliance on AI erodes independent judgment and the ability to discern reliable information from AI-generated content.(iii) Capability gap: There is insufficient tailored training, advanced skills, and critical evaluation.

Given these gaps, the discussion highlighted that progress will be dependent on intentional collaboration across governments, education authorities, schools, technological partners, and communities. Adaptive governance should evolve alongside technological progress. Structured supervision and extensive capability-building environments are required to empower educators and students beyond basic functionality. Inclusive infrastructure and accessible design are critical to ensure that AI-enabled learning does not exacerbate existing disparities. System-wide collaboration is essential to build adaptable institutions, strengthen scaled capacities, and ensure equitable outcomes.