Vietnam approved a national artificial intelligence workforce programme on 11 August under Decision 1528/QĐ-TTg, signed for the prime minister by Deputy Prime Minister Lê Tiến Châu. By 2030, it targets at least 50,000 university-level personnel able to apply AI in priority sectors, 10,000 high-level AI personnel and, within that group, 1,500 core-technology experts.
The 50,000 target covers new training, career conversion and advanced training for people who can apply AI, rather than 50,000 AI engineers. The 10,000-person group covers researchers, engineers and specialists able to develop, deploy, operate and govern advanced systems.
The programme also calls for at least 10 advanced AI training and research centres, 25 higher-education hubs and 35 vocational institutions, with 30% of enterprises in priority sectors participating in training. Five to seven of the centres are meant to reach an advanced regional level and gradually approach international standards. Appendix I sets a cumulative pathway for high-level personnel: 500 in 2026, 2,500 in 2027, 5,000 in 2028, 7,500 in 2029 and 10,000 in 2030.
The wider skills plan would train or update at least 10 million workers in basic AI use, while every higher-education institution would have to set rules for AI in teaching, research and assessment. Other targets cover 80% of school students, all higher-education learners, at least 80% of vocational learners, 90% of officials, civil servants and employees in public-service units, and all education and training personnel; 100,000 teachers, lecturers and education managers would receive advanced training.
Vietnam’s AI Law, in force since 1 March, requires such a programme and assigns responsibility for it to the education ministry. The Ministry of Education and Training will coordinate implementation, build an AI-workforce database, set criteria for selecting the 25 higher-education hubs and lead annual evaluation. The Ministry of Science and Technology will guide access to shared computing infrastructure, data and platforms, and develop programmes and policies for experts and researchers. Ministries and provinces must report by 30 November each year, with reviews in 2028 and 2030. The Ministry of Finance is to propose tax and financial incentives for companies investing in university AI laboratories, and to compile and submit the programme’s state-budget funding proposals.
But Decision 1528 does not set a total budget. Part IV lists annual central and local state budgets, lawful income from training institutions, enterprise resources, social funding, sponsorship, aid, public-private cooperation and other lawful sources. The decision separately instructs officials to study financial support for workers affected by AI, automation and digitalisation, prioritising possible coordination with vocational-skills policies, existing retraining programmes and the Unemployment Insurance Fund. That is an instruction to study a mechanism, not an allocation from the fund. The decision also says a specialised fund model or financial mechanism may be proposed if necessary; it does not create one. The AI Law separately establishes a national AI development fund, but Decision 1528 does not allocate money from it.
The decision does not name any of the 25 higher-education hubs or 10 centres, leaving the selection criteria to the education ministry. By comparison, the body of Vietnam’s 2024 semiconductor workforce plan named locations for four national shared laboratories, while its Appendix II separately listed 18 public universities as priorities for smaller laboratories.
A 2025 UNESCO assessment said more than 50 Vietnamese universities offered AI-related courses and an estimated 50,000 to 70,000 IT graduates entered the labour market each year. Those figures describe IT graduates, not AI engineers, and are not equivalent to the programme’s 50,000-person application target.
The next disclosed steps will be the education ministry’s selection criteria for the 25 higher-education hubs and any proposal to establish the specialised fund model or financial mechanism mentioned in the decision.
