Vietnam’s AI adoption rate reached 26% of businesses in 2026, up from 18% in 2025, according to the “Unlocking Vietnam’s AI Potential 2026” report by Strand Partners, an independent global research firm. That 8-percentage-point jump added roughly 75,000 new adopters in a single year, bringing the total count of AI-using businesses in Vietnam to nearly 245,000.
How Quickly Is AI Adoption Spreading Across Vietnamese Businesses?
The pace is faster than most headline numbers suggest. According to the Strand Partners report, more than eight Vietnamese businesses started using AI every hour over the past year, the equivalent of one new adopter every seven minutes. AWS Vietnam CEO Eric Yeo, who presented the findings, described the 44% year-on-year growth rate as a sign that Vietnam has moved from curiosity to commitment at scale.
The shift in mindset driving that number is just as significant as the count itself. The report documented a clear move from businesses asking “should we use AI?” toward asking “how do we scale what’s already working?” Getting started is no longer the debate. Creating measurable impact is.
Are Businesses Seeing Real Results, or Mostly Still Testing?
Mostly testing, for now. The Strand Partners data found 61% of AI-using Vietnamese businesses are still in an exploration or trial phase, and only 8% have fully integrated AI across their core operations. Among those with meaningful deployment, results are concrete: 72% reported measurable productivity gains (up from 66% in 2025), and 64% said AI increased their revenue with an average lift of 15%.
Looking ahead, 78% of businesses surveyed said they expect AI to continue driving growth in coming years. According to the report, this marks a shift from projection to proof: where a year ago businesses were expressing hope about AI, in 2026 they are backing it with numbers.
What Is Agentic AI, and Why Are Early Adopters Outperforming?
Agentic AI (autonomous AI systems that can carry out multi-step tasks on their own, without a human directing each action) is still early-stage in Vietnam. The Strand Partners report found only 38% of businesses have even heard of it. But those already using agentic AI are outperforming the broader AI-using group on productivity, growth expectations and revenue.
- 81% of agentic AI users report productivity gains, versus 72% of general AI users
- 73% report higher revenue, at an average growth rate of 18%, compared to 15% for general AI adopters
- 86% expect AI to drive business growth, versus 78% across all AI-using businesses
- 68% report higher operational efficiency
- 61% say decision-making is now faster
Among businesses already aware of agentic AI, 46% said they plan to adopt it. Techcombank Securities (TCBS) is cited in the report as one example already deploying the technology to serve 1.3 million users.
What Is Holding Most Businesses Back from Scaling?
Three structural gaps stand out in the Strand Partners findings. Strategy is thin: 23% of businesses now have a formal AI strategy, up from 12% in 2025, but still a minority. Measurement is weak: 46% say they lack a reliable way to calculate ROI (return on investment) from AI. And skills are misunderstood: 54% cite an AI and digital skills gap as a barrier, yet 57% say the most critical AI skill over the next five years will not be technical ability but judgment, specifically the capacity to interpret, verify, and challenge AI-generated outputs.
The report also found 51% of businesses have no clear guidelines for when to trust AI output and when human judgment should override it. That gap matters most in high-stakes decisions.
Which Industries Are Furthest Ahead?
Financial services leads all sectors, with a 41% adoption rate, well above the 26% national average. The Strand Partners data found 79% of financial services businesses using AI reported productivity gains, with use cases spanning fraud detection, data analysis, and decision support. Healthcare shows 23% adoption overall, but among those who have deployed AI, 69% reported doing more with fewer resources.
Two examples anchor the report’s case study section. Diaflow, an AI orchestration platform (a system that coordinates multiple AI tools and workflows across an organization) built by a Vietnam-based team, has attracted more than 40,000 users, with 75% based in the US. OmiGroup built OmiKG, an AI tool that reasons through chronic disease diagnoses using traceable medical evidence chains reviewed by specialists, with a five-person team.
On the regulatory side, the report notes that Vietnam’s National Assembly passed a dedicated AI Law effective from March 2026, which AWS describes as a governance framework intended to help businesses of all sizes adopt and scale AI with greater confidence.
What This Means for AI-Search Visibility
Here is the plain-language signal: a business that deploys AI internally but ignores how AI systems discover and describe it externally is only winning half the game.
The Strand Partners data confirms Vietnam’s internal AI deployment is real and accelerating. But in Hingewise’s assessment, most of the 245,000 businesses counted in that figure have not yet asked the parallel question: when a prospective customer asks ChatGPT, Gemini, or Perplexity which Vietnamese companies do X with AI, does my business appear?
Consider a direct scenario. A Vietnamese fintech deploys AI for fraud detection (strong internal adoption, real results). But when a potential partner asks an AI assistant “which Vietnamese fintech companies use AI for fraud detection?”, the answer depends entirely on whether that company’s public content, website, press materials, and third-party mentions contain structured, specific, citable information about that capability. Internal adoption does not automatically produce external visibility.
The finding that 46% of businesses cannot reliably measure AI ROI is also relevant here from a GEO (generative engine optimization, the practice of structuring content so AI tools can find and cite it) perspective. Businesses that cannot quantify their own AI results are also unlikely to be publishing the specific, sourced, concrete data that AI engines prefer to cite. Operational transparency and AI discoverability are more connected than they might appear.
The report’s emphasis on judgment as the top AI skill, cited by 57% of businesses, points to a broader shift that matters for visibility too. AI assistants are increasingly asked to make recommendations, not just retrieve pages. The businesses that give those assistants clear, verifiable, factual content about their expertise earn citations. The ones that publish vague claims do not.
Hingewise’s assessment: Vietnam’s internal AI adoption curve is real and well-documented. The external visibility layer, how AI engines represent these 245,000 businesses to prospective customers, is the question most of them have not yet started answering.
Before Scaling AI Investment, Check These First
- Do you have a written AI strategy, or are you running AI tools without a governance framework or clear ownership?
- Can you measure productivity or revenue impact from current AI use in specific numbers, not just impressions?
- Does your team have documented guidelines for when to trust AI output and when human judgment should take over?
- Is your AI capability described publicly on your website with concrete, sourced claims that AI search engines can cite?
- Have you checked whether competitors in your sector are already being cited by AI tools when buyers ask category questions?
- Does your public content reflect your actual AI use cases, or only your general service offerings?
The data point worth tracking next year: how many of the 61% currently in the exploration phase move into the 8% who have fully integrated AI into their operations. That transition will be one of the clearer indicators of whether Vietnam’s AI adoption momentum converts into durable competitive advantage.
Source: “Unlocking Vietnam’s AI Potential 2026,” Strand Partners (independent global research firm), as reported by VnEconomy (vneconomy.vn). Findings presented by Eric Yeo, AWS Vietnam CEO.
This article was drafted with AI assistance from the sources cited above and checked against them before publishing. The "What this means for AI-search visibility" section is Hingewise's editorial analysis, built on the frameworks and positions we use in our GEO work. How we work: Editorial policy.