Vietnam’s digital economy gains momentum with AI adoption

Vietnam’s digital economy maintained positive growth, increasingly driven by the widespread adoption of artificial intelligence (AI) applications in everyday life and business operations.

Experiencing virtual reality technology at the Nha Trang Centre shopping mall in Khanh Hoa (Photo: VNA)
Experiencing virtual reality technology at the Nha Trang Centre shopping mall in Khanh Hoa (Photo: VNA)

Hanoi (VNA) - Vietnam’s digital economy is expanding beyond high-tech manufacturing into banking, other economic sectors and the public sector.

Vietnam’s digital economy maintained positive growth, increasingly driven by the widespread adoption of artificial intelligence (AI) applications in everyday life and business operations.

According to the 2026 e-Conomy SEA report by Google, Temasek and Bain & Company, Vietnam’s digital economy is projected to reach 49 billion USD in gross merchandise value (GMV) in 2026, up 20% year on year, placing the country among Southeast Asia’s fastest-growing digital economies, alongside Malaysia.

All four core sectors recorded double-digit growth, with e-commerce as the primary growth driver, along with online travel, online media, ride-hailing, and food delivery.

Josh Abbott, Vice President for Asia-Pacific and Japan at US-based technology giant Teradata, expressed his impression of the rapid development of Vietnam’s digital economy.

Abbott told VnEconomy that Vietnam has a highly skilled workforce, while businesses’ understanding of and approach to data, AI and business operations has advanced rapidly. These factors are laying the groundwork for the development of the data and AI market.

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ietnam Post is accelerating digital transformation within the postal sector, proactively integrating science and technology into its production and business operations (Photo: VNA)

However, to turn this potential into tangible economic value, businesses need to overcome challenges related to data quality, governance and technology implementation costs. One key issue is that business data is not yet ready for AI applications, particularly as they move towards agentic AI, in which systems can independently carry out multiple steps and handle more complex tasks.

According to Abbott, one notable shift in business technology infrastructure strategies is the growing trend towards combining public cloud computing with on-premises systems, rather than moving all data and processing workloads to cloud service providers such as AWS or Google Cloud. This approach is attracting greater attention amid increasingly stringent data sovereignty requirements.

This is not a complete retreat from cloud computing, but rather an adjustment in how businesses allocate workloads and manage data, the expert stressed.

Based on his experience in different markets, he noted that businesses are increasingly expected to comply with specific data sovereignty requirements, concerning where information is stored and processed. While not all data needs to be transferred back to on-premises systems, certain types may be mandated to stay within national borders.

In addition to data protection requirements, organisations operating critical infrastructure may also face specific conditions concerning their ability to maintain operations if cloud service providers experience disruptions. For example, some organisations are required to ensure that they can continue operating for around 90 days even if cloud services are interrupted. This requires businesses to operate systems at capacity and independently, with on-premises infrastructure potentially playing an important role.

Meanwhile, costs and demand for graphics processing units (GPUs) are also prompting businesses to consider investing in their own infrastructure. Abbott said that even financially strong companies were choosing to deploy some of their GPU processing capacity on-premises to support AI applications./.

VNA

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