AEF 2026: Vietnam must learn from both successes and failures in AI adoption
WVR - To make effective use of artificial intelligence (AI), Vietnam needs to strengthen cooperation between universities, businesses and public authorities, while proactively learning from international experience in urban governance and risk management.
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On the occasion of the Autumn Economic Forum 2026 (AEF 2026), The World and Vietnam Report spoke to university representatives about the application of AI, the promotion of technological innovation and stronger cooperation between universities, businesses and public authorities.
University - business cooperation drives technological innovation
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| Professor Park Suhyun, Head of the Department of Computer Science at Dongseo University (Republic of Korea), highlighted the role of cooperation between universities, businesses and public authorities in promoting technological innovation and developing Vietnam’s workforce. (Photo: Thanh Long) |
From the Korean perspective, Professor Park Suhyun, Head of the Department of Computer Science at Dongseo University in the Republic of Korea, said Vietnam should focus on strengthening its technological capabilities in manufacturing and promoting innovation to reduce its dependence on foreign companies.
Speaking after a session on AI in manufacturing, Professor Park noted that, alongside technological improvements, changing mindsets and encouraging innovation were also essential.
According to a representative from Dongseo University, businesses should invest in technological innovation and workforce development by cooperating with universities.
From a policy perspective, Professor Park said public authorities should support joint research between universities and businesses, implement government-supported training programmes and establish mechanisms to encourage domestic innovation.
Drawing on the Republic of Korea’s development experience, the Dongseo University representative emphasised the importance of cooperation between Vietnam and the Republic of Korea, particularly in AI and education.
Professor Park said that, as Vietnam pursues its development strategies, exchanging experience and strengthening bilateral cooperation would help enhance technological capabilities and improve workforce quality.
Learning from both success and failure
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| Associate Professor Dr Nguyen Quang Trung, Head of the Department of Management at The Business School, RMIT University Vietnam, said Vietnam could draw on international experience in applying AI to urban governance. (Photo: Thanh Long) |
From the Vietnamese perspective, Associate Professor Dr Nguyen Quang Trung, Head of the Department of Management at The Business School, RMIT University Vietnam, said international experience could offer practical insights for Vietnam and Ho Chi Minh City in applying AI to urban governance.
He stressed that such assessments should take into account both successful models and cases that had failed to deliver the expected results.
Among the experiences worth examining is Singapore’s Smart Nation initiative, launched more than a decade ago, alongside GovTech’s role in implementing technology programmes.
Associate Professor Dr Nguyen Quang Trung also cited the City Brain model in Hangzhou, China, an AI initiative involving coordination among multiple stakeholders.
Regarding Seoul, Republic of Korea, the RMIT University Vietnam representative highlighted an approach that clarifies data sources, who provides the data and the scope of its use.
However, international experience also highlights the risks of automation without adequate human oversight.
According to Associate Professor Dr Nguyen Quang Trung, Australia’s Robodebt scheme is a notable example of the risks associated with AI and automation.
Specifically, automated systems that lack adequate human checks can produce errors, make it difficult to establish accountability and result in substantial losses.
Drawing on these experiences, Associate Professor Dr Nguyen Quang Trung stressed that Vietnam should approach AI with an open mind and proactively learn from both successes and failures.
Alongside selecting appropriate models, establishing oversight mechanisms and clearly defining accountability will be essential to improving the effectiveness of AI applications in urban governance.
