Assessing Artificial intelligence (AI) readiness using UNESCO's RAM tool and policy implications for Vietnam

Authors

  • Quynh Trang Trinh*

Keywords:

Artificial intelligence, artificial intelligence governance, temporary memory, UNESCO

Abstract

This article analyses the Artificial Intelligence Readiness Assessment Methodology (RAM) developed by the United Nations Educational, Scientific and Cultural Organisation (UNESCO) as a normative and policy-oriented tool to support countries in assessing their institutional readiness for the development and governance of responsible artificial intelligence (AI). Built upon the Recommendation on the Ethics of Artificial Intelligence adopted in 2021 by all 193 UNESCO Member States, RAM approaches AI as a public policy issue closely linked to human rights and sustainable development. By examining the underlying logic, the five-pillar structure of RAM, and its position within the global ecosystem of AI governance and assessment tools, the article clarifies the normative value and distinctive approach of RAM in comparison with other international frameworks. Drawing on an analysis of the Viet Nam case based on the national RAM Report published in October 2025, the article assesses the role of RAM in supporting the development of Viet Nam’s national AI policy framework and promoting its integration into international standards. On this basis, the article proposes several policy implications aimed at strengthening Viet Nam’s capacity for responsible AI governance in the coming period.

DOI:

https://doi.org/10.31276/VJST.2026.3788

Classification number

1.2, 1.9, 5.13

Author Biography

Quynh Trang Trinh

Ministry of Science and Technology, 18 Nguyen Du Street, Cua Nam Ward, Hanoi, Vietnam

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Published

2026-03-05

Received 7 January 2026; revised 14 January 2026; accepted 28 January 2026

How to Cite

Trinh Quynh Trang. (2026). Assessing Artificial intelligence (AI) readiness using UNESCO’s RAM tool and policy implications for Vietnam. Version B of Vietnam Journal of Science and Technology. https://doi.org/10.31276/VJST.2026.3788

Issue

Section

Natural Sciences