The Complete Guide to Using AI in the Education Industry in Viet Nam in 2025

As Việt Nam moves into 2025 the education sector is at an inflection point - national reforms, a push to finalise the Teacher Law and a new curriculum cycle are creating space for AI to amplify learning outcomes, teacher training and school management rather than replace them; detailed coverage from Vietnam News analysis of Vietnam's 2025 education priorities lays out the government's priorities, UNICEF's summary of MOET's 2025 National Plan highlights teacher and manager upskilling and pilots of AI tools (even VR glasses) in classrooms (UNICEF press release on the MOET–UNICEF forum about AI in education), and Decision Lab's survey shows rapid consumer uptake - 78% of online Vietnamese have used AI - making digital literacy urgent for students and staff (Decision Lab 2025 survey on AI adoption in Vietnam).

Practical upskilling options, such as a 15‑week AI Essentials for Work bootcamp that teaches prompt writing and workplace AI use, can help schools and educators move from pilot projects to classroom impact.

“We should use AI in a proactive, independent, and intelligent manner - without dependency - and with a strong sense of ethicality.”

The Vietnam AI economy report 2025 - launched by the National Innovation Centre in collaboration with JICA and BCG - maps the country's AI potential, emerging trends and strategic directions and is a clear signal that digital policy momentum now includes education: the June 12 ceremony gathered roughly 100 delegates from ministries, universities, startups and international partners and even featured an exhibition of real-world AI solutions across sectors including education, showing how tools from diagnostics to adaptive learning are moving from lab to classroom (Vietnam AI Economy Report 2025 from NIC–JICA–BCG).

For educators and EdTech founders the report matters because it aligns with broader market and policy levers - national funds, PPP frameworks and incentives - that are driving rapid AI adoption and scale in Vietnam's booming digital economy and higher‑education expansion (targeting over 3 million university students by 2030), creating concrete pathways for funding teacher upskilling, localized Vietnamese models and school pilots (Vietnam AI market projections and policy instruments (2025)); the report's mix of strategy, case studies and stakeholder convening makes the “so what?” obvious: AI is moving from promise to procurement in Vietnam's classrooms and campuses, and educators who plan now can shape curriculum, data use and procurement rather than be swept along by it.

“This makes Vietnam the second-largest supplier of software engineers in the world – a fact that few people know about. With this potential, we believe that Vietnam is an ideal place for NVIDIA to develop R&D centers and build a strong AI ecosystem here.”

Vietnam's National Digital Transformation Plan through 2025 is turning policy into practical pressure points for classrooms: the programme pushes for government services and national databases to be online and connected, expands digital infrastructure and data governance, and explicitly lists education as a priority sector - moves that open procurement, interoperability and teacher‑training windows for AI tools and EdTech platforms.

Coupled with the Politburo's recent Resolution 71 and MOET's implementation measures (which even saw the national school opening link 52,000 schools online), the result is a faster path from isolated pilots to systemwide adoption, but one that demands clear plans for data systems, procurement rules and upskilling (see the Vietnam National Digital Transformation Programme summary on Vietnam Briefing).

For edtech founders and school leaders the upside is tangible: a growing market, rising public funding and explicit targets for digitisation that Austrade and GlobalCIO note are fueling investor and startup activity in AI‑driven learning solutions; the practical “so what?” is this - schools that align procurement, teacher development and data governance with the Plan will be best placed to roll out localized AI content and adaptive platforms at scale.

“Education is a long-term cause that demands vision, perseverance and responsibility. I call on managers, teachers, staff and students to unite, prepare well and make this school year successful.”

What will happen with AI in Việt Nam in 2025 is less sci‑fi and more system build‑out: expect AI to move from isolated pilots into everyday classroom workflows as policy, funding and local models converge - Vietnam ranks 6th on the WIN World AI Index and already shows strong public trust, the domestic AI market (USD 753.4M in 2024) is growing fast, and education demand is soaring with higher‑education expansion targets pushing capacity needs through 2030; these dynamics are why schools and EdTechs are racing to adopt Vietnamese‑language LLMs and adaptive platforms rather than one‑size‑fits‑all foreign models.

Concrete signals include rapid local LLM progress on the VMLU leaderboard (for example KiLM‑13b's high VMLU scores) that make Vietnamese‑tailored tutoring and instant, culturally accurate assessments feasible, an EdTech boom that can scale personalized learning, and government resources for cloud, data centers and national datasets to support safe deployments (see the State of AI in Vietnam 2025 and reporting on Vietnamese LLM breakthroughs).

The practical “so what?” is clear: schools that plan for teacher upskilling, data governance and procurement now will unlock AI tools that save teachers hours through localized content generation and deliver targeted support to students across urban and rural classrooms - turning model wins on benchmarks into real learning gains.

“If Vietnam does not take control of its core AI technologies, it risks becoming a digital colony, dependent on foreign innovations.”

Localized AI for learning Vietnamese is rapidly shifting from a research curiosity to practical classroom tools: domestic teams and universities are training LLMs against the VMLU benchmark (which spans primary to postgraduate questions), submitting 45 models from more than 155 groups and running thousands of evaluations that show Vietnamese‑trained systems can now compete with global brands - Zalo's KiLM‑13b, for example, scored ~66.07 on VMLU (above GPT‑4's 65.53), making Vietnamese‑language tutoring, instant culturally accurate assessment and curriculum‑aligned content generation realistic possibilities for schools (VMLU progress report on Vietnamese LLM benchmark).

At the same time, national efforts like the ViGen dataset initiative (NIC + Meta + AI for Vietnam) are tackling a core bottleneck - less than 1% of training data today is Vietnamese - by building open, high‑quality corpora so models better capture local vocabulary, history and regional culture, which directly improves lesson plans, formative assessments and inclusive language support for students across urban and rural classrooms (ViGen open-source Vietnamese dataset initiative).

The practical upshot for educators: tools fine‑tuned on Vietnamese datasets and benchmarks can save teachers hours by generating localized exercises, grading rubrics and readable feedback in Vietnamese, while research teams stress careful evaluation and fine‑tuning to avoid bias and maintain safety as models scale.

“The increase in the number of LLMs in Vietnam indicates significant interest from numerous companies and individuals in enhancing the applications of GenAI.”

Across Vietnamese schools and colleges AI is already shifting daily practice from slogging through paperwork to more personalised teaching: districts from Hanoi to Quang Tri have run large-scale teacher training (4,000 Quang Tri teachers completed an “AI in Education” Khan Academy course) and pilots that pair human-led instruction with intelligent tutors and assistants such as Khanmigo - a tutoring and lesson‑planning assistant that can generate lesson plans, assessments and personalised feedback and offers 25 tools to help teachers save hours in preparation (Khanmigo AI tutoring and lesson‑planning assistant in Vietnam).

At the same time, university‑led pilots are proving inclusive rollout models: international teams working with urban and rural schools in co‑design projects are trialling AIEd tools to personalise formative feedback and bridge the urban–rural digital divide (inclusive AI in-education pilot projects in Vietnam).

Practical vendor approaches - white‑label integrations for EdTech and localized content generation in Vietnamese - let schools deploy adaptive quizzes, automated grading and culturally accurate exercises without heavy CAPEX, turning model accuracy into classroom minutes saved (localized AI content generation for Vietnamese classrooms).

These examples show a clear pattern: teacher assistants, personalised diagnostics and targeted upskilling are the real, near‑term wins for education in Viet Nam in 2025.

“We should use AI in a proactive, independent, and intelligent manner - without dependency - and with a strong sense of ethicality.”

Building teacher and student capacity is now the practical heart of Vietnam's AI-in-education push: MOET and partners have rolled out national digital competency frameworks and large-scale workshops so teachers move from curiosity to classroom practice, while pilot programmes and community initiatives give schools real paths to adopt tools safely; UNICEF's National Forum framed this roadmap and the need for ethical, supervised use (UNICEF National Forum on AI in Education).

On the ground, Cambodia‑style hype is nowhere to be seen - districts and foundations are training teachers at scale (4,000 Quang Tri teachers finished Khan Academy's “AI in Education” course) and institutional partners are preparing to deploy Khanmigo as a teaching assistant that can free teachers from routine prep with 25 specialised tools, personalise feedback, and help monitor student conversations (Vietnam Foundation on Khanmigo and teacher training).

Higher‑ed and NGO programs - from RMIT's national training reach to grassroots VAIEP classrooms - are aligning teacher roles toward facilitation, project‑based learning and ethical oversight so students gain AI skills without losing human guidance; the vivid payoff is simple: well‑trained teachers turn model accuracy into minutes saved and learning that actually reaches rural as well as urban classrooms.

“We should use AI in a proactive, independent, and intelligent manner - without dependency - and with a strong sense of ethicality.”

Safe, scalable AI in Viet Nam's schools depends less on flashy models and more on three practical ingredients: clean data and interoperability, reliable infrastructure, and procurement rules that reward quality not just price.

Accreditation findings show why this matters - libraries and learning resources scored lowest in program reviews (criterion 9.2 averaged 3.32), and professional development gaps (criterion 6.5) leave staff underprepared for new tools, so any AI rollout must pair platforms with concrete investments in content, connectivity and teacher training (see the program accreditation analysis on program accreditation in Vietnam higher education quality management study).

Procurement strategies can bridge shortfalls: white-label AI integrations allow schools to adopt adaptive quizzes and grading without heavy CAPEX, while locally tuned models and content generation save teachers hours by producing culturally accurate lesson plans and assessments in Vietnamese - practical levers for districts that need fast wins (localized Vietnamese content generation for education, white-label AI integrations for schools adaptive quizzes and grading).

The vivid payoff: fixing library and training gaps means an AI tutor generates lesson sets that teachers can trust and local procurement can actually deliver to remote classrooms, not just pilot schools.

Ethics, safety and compliance in Viet Nam's AI-in-education rollout mean pairing inclusive teacher training and classroom co‑design with clear legal guardrails: projects that co-develop pedagogical practices across urban and rural schools show why educators must be part of rulemaking from day one (see the Birmingham City University inclusive AI teacher training work), while national rules are filling in fast - Vietnam already has Decree No.13/2023 on personal data, MoST's responsible‑AI principles and draft laws that introduce labeling, prohibited practices and a regulatory sandbox to test innovations for up to two years; these changes demand practical steps for schools such as transparent student consent, regular impact assessments, appointing data‑protection leads and choosing vendors that meet local privacy standards (overview of Vietnam's 2025 regulatory landscape).

Best practices include building teacher capacity to evaluate bias and safety, using sandboxes to trial tools with real students under supervision, and linking procurement to legal compliance and inclusive outcomes so rural learners aren't left behind - a timely mix of pedagogy, process and law that turns abstract ethics into classroom-safe practice.

“This makes Vietnam the second-largest supplier of software engineers in the world – a fact that few people know about. With this potential, we believe that Vietnam is an ideal place for NVIDIA to develop R&D centers and build a strong AI ecosystem here.”

Educators and EdTech startups ready to turn 2025 momentum into classroom results should act on three clear, practical fronts: first, prioritise teacher and staff upskilling so instructional teams can evaluate bias, design local prompts and integrate AI into lesson workflows - practical courses and short bootcamps (for example AI Essentials for Work 15‑week bootcamp syllabus | Nucamp) give schools a fast route to usable skills (AI Essentials syllabus); second, align procurement and pilots with Vietnam's evolving legal and funding landscape - use the regulatory sandbox, follow DTI and PDP developments, and structure procurements for interoperability and data governance as described in Vietnam Briefing 2025 AI regulatory overview and sandbox; and third, tap national datasets, funds and partnerships - Project ViGen, public–private grants and the National Data Development Fund (NDDF) offer scale (the State of AI in Vietnam 2025 notes an NDDF with large initial capitalization), so co‑design pilots with universities or NIC partners to access data, compute and research expertise (State of AI in Vietnam 2025 report).

Start with small, measurable pilots that save teacher time (automated assessments, localized exercises), document learning impact, and use sandboxes or phased contracts to manage privacy and safety; the fastest wins come from combining well‑trained staff, local language models and procurement that rewards quality, not just price.

“This makes Vietnam the second-largest supplier of software engineers in the world – a fact that few people know about. With this potential, we believe that Vietnam is an ideal place for NVIDIA to develop R&D centers and build a strong AI ecosystem here.”