Limitations of the tiered risk-classification approach in AI regulation: International experience and implications for Vietnam
Published: August 10, 2026
Abstract
The rapid development of artificial intelligence is transforming service delivery in the digital economy while challenging traditional regulatory models. Many jurisdictions have adopted tiered risk-classification approaches to AI governance, most notably the European Union’s AI Act. However, this model has significant limitations because AI risks are dynamic, nonlinear, and continuously influenced by data, deployment contexts, system interactions, and adaptive learning. Static classification may therefore result in disproportionate regulatory obligations or fail to capture emerging and cumulative risks. This study examines these limitations and analyzes the international shift toward dynamic, context-based, and lifecycle-oriented AI governance. Based on international experience, it proposes recommendations for Vietnam to introduce continuous risk assessment, strengthen post-deployment monitoring, clarify accountability, and develop adaptive regulatory mechanisms suitable for evolving AI systems.
Bullock, J. B., Chen, Y.-C., et al. (2024). The Oxford Handbook of AI Governance. Oxford University Press, pp. 441–460.
5.
Barfield, W. (2020). The Cambridge Handbook of the Law of Algorithms. Cambridge University Press, p. 224.
6.
Corrales, M., Fenwick, M., & Forgó, N. (2018). Robot, AI and Future Law. Springer, p. 89.
7.
Chesterman, S. (2021). We, the Robots? Regulating Artificial Intelligence and the Limits of the Law. Cambridge University Press, p. 183.
8.
Nikolinakos, N. T. (2023). EU Policy and Legal Framework for Artificial Intelligence, Robotics and Related Technologies: The AI Act. Springer, p. 275.
9.
Mathis, K., & Tor, A. (2023). Law and Economics of the Digital Transformation. Springer, p. 364.
10.
Kovač, M. (2024). Generative Artificial Intelligence: A Law and Economics Approach to Optimal Regulation and Governance. Springer, pp. 113-114.
11.
Nikolinakos, N. T. (2023). EU Policy and Legal Framework for Artificial Intelligence, Robotics and Related Technologies: The AI Act. Springer, pp. 352-353.
12.
Nikolinakos, N. T. (2023). EU Policy and Legal Framework for Artificial Intelligence, Robotics and Related Technologies: The AI Act. Springer, pp. 43-44.
13.
Antunes, H. S., Freitas, P. M., Oliveira, A. L., Pereira, C. M., Sequeira, E. V., & Xavier, L. B. (2024). Multidisciplinary Perspectives on Artificial Intelligence and the Law. Springer, pp. 419-421.
14.
Smuha, N. A. (2025). The Cambridge Handbook of the Law, Ethics and Policy of Artificial Intelligence. Cambridge University Press, pp. 243–244.
15.
Bullock, J. B., Chen, Y.-C., et al. (2024). The Oxford Handbook of AI Governance. Oxford University Press, pp. 183-197.
16.
Nikolinakos, N. T. (2023). EU Policy and Legal Framework for Artificial Intelligence, Robotics and Related Technologies: The AI Act. Springer, pp. 435-436.
17.
Nikolinakos, N. T. (2023). EU Policy and Legal Framework for Artificial Intelligence, Robotics and Related Technologies: The AI Act. Springer, pp. 508-509.
18.
Antunes, H. S., Freitas, P. M., Oliveira, A. L., Pereira, C. M., Sequeira, E. V., & Xavier, L. B. (2024). Multidisciplinary Perspectives on Artificial Intelligence and the Law. Springer, p. 421.
19.
Organisation for Economic Co-operation and Development (OECD). (2022). OECD Framework for the Classification of AI Systems.
20.
Bullock, J. B., Chen, Y.-C., et al. (2024). The Oxford Handbook of AI Governance. Oxford University Press, pp. 253-275.
21.
Organisation for Economic Co-operation and Development (OECD). (2022). OECD Framework for the Classification of AI Systems.
22.
Singh, T. (2024). Artificial Intelligence and Ethics: A Field Guide for Stakeholders. CRC Press, pp. 189-190.
23.
Corrales, M., Fenwick, M., & Forgó, N. (2018). Robot, AI and Future Law. Springer, pp. 89-90.
24.
Antunes, H. S., Freitas, P. M., Oliveira, A. L., Pereira, C. M., Sequeira, E. V., & Xavier, L. B. (2024). Multidisciplinary perspectives on artificial intelligence and the law. Springer.
25.
Barfield, W. (2020). The Cambridge handbook of the law of algorithms. Cambridge University Press.
26.
Bullock, J. B., Chen, Y.-C., et al. (2024). The Oxford handbook of AI governance. Oxford University Press.
27.
Chesterman, S. (2021). We, the robots? Regulating artificial intelligence and the limits of the law. Cambridge University Press.
28.
Corrales, M., Fenwick, M., & Forgó, N. (2018). Robot, AI and future law. Springer.
29.
European Union. (2025). Artificial Intelligence Act.
30.
Kellmeyer, P., Mueller, O., Burgard, W., & Voeneky, S. (Eds.). (2022). The Cambridge handbook of responsible artificial intelligence: Interdisciplinary perspectives. Cambridge University Press.
31.
Kovač, M. (2024). Generative artificial intelligence: A law and economics approach to optimal regulation and governance. Springer.
32.
Mathis, K., & Tor, A. (2023). Law and economics of the digital transformation. Springer.
33.
National Institute of Standards and Technology. (2023). Artificial intelligence risk management framework (AI RMF 1.0).
34.
Nikolinakos, N. T. (2023). EU policy and legal framework for artificial intelligence, robotics and related technologies: The AI Act. Springer.
35.
Organisation for Economic Co-operation and Development. (2022). OECD framework for the classification of AI systems. OECD Publishing.
36.
Singh, T. (2024). Artificial intelligence and ethics: A field guide for stakeholders. CRC Press.
37.
Smuha, N. A. (2025). The Cambridge handbook of the law, ethics and policy of artificial intelligence. Cambridge University Press.
