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Vietnam’s business AI adoption estimate rose from 18% in 2025 to 26% in 2026, according to an AWS-commissioned study conducted by Strand Partners. But adoption does not mean AI is fully deployed: 61% of businesses already using AI said they were still experimenting. The 26% figure refers to businesses, not Vietnamese people as a whole.
What Vietnam’s 26% AI adoption figure measures
The Unlocking Vietnam’s AI Potential 2026 study estimates that about 245,000 Vietnamese businesses have adopted AI. Strand Partners conducted the study for AWS, which says it surveyed 1,000 business leaders and 1,000 members of the public across Vietnam. The comparable business-adoption estimate was 18% in 2025. AWS’s study summary describes the findings.
This is a business estimate, not a measure of how many people use AI. A separate figure reported by Vietnam’s Government News, citing Microsoft’s Global AI Diffusion Report, put adoption among people aged 15–64 at 26.5% in Q1 2026. That population measure has a different denominator and methodology, so it should not be treated as confirmation of the business figure. Government News’ report covers the working-age population statistic.
Why most adopters are still experimenting
Adopting AI can mean anything from a pilot to routine use across an organization. In the AWS-commissioned survey, 61% of AI-adopting businesses said they were still experimenting, while 23% of adopters reported having a formal, comprehensive AI strategy. The figures indicate a gap between trying AI and embedding it systematically; they do not mean all adopters are at the same stage.
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Measurement is another sign of that gap. Across businesses polled, 13% said they had a clearly defined and consistently applied framework for measuring AI return on investment, while 46% said they lacked reliable ways to measure ROI. Without a consistent baseline and tracking method, businesses may find it difficult to tell whether an AI tool improves a process enough to justify its cost and operational risks.
What businesses report gaining from AI
Among AI adopters, 72% reported productivity gains, up from 66% in the previous year. The study also says 64% reported that AI had increased revenue by an average of 15%, and 71% said their AI investment had broken even or delivered a positive return. These are self-reported survey results, not independent causal evidence: they do not establish that AI alone produced the reported gains.
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Expectations and priorities are distinct from realized results. AWS says 78% of adopters expected AI-driven growth in the coming year, and 69% of businesses described AI adoption as a top or high priority. Those responses show stated outlook and intent, not outcomes already achieved.
Adoption and reported gains vary by sector
The study reported a 41% AI adoption rate among financial-services businesses, compared with 26% across businesses overall. Among financial-services adopters, 79% reported productivity gains. Healthcare businesses had a 23% adoption rate, and 69% of healthcare adopters reported productivity gains. Adoption rates describe the share of businesses using AI in each sector; productivity figures describe a share of adopters, so the measures should not be conflated.
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What is holding implementation back?
Skills are a commonly cited obstacle: 54% of businesses recognized a shortage of digital and AI skills as a barrier to adopting or expanding AI. At the same time, 87% of employers considered reskilling current employees important to their AI strategy. The study says 26% of employees had participated in some form of training in the previous year, compared with 19% in 2025.
The survey’s implementation picture also points to strategy, governance and measurement. In practical terms, a business moving beyond pilots needs to decide who can use AI, which information may be entered into a tool, how outputs will be checked, where the tool fits into an existing workflow, and what measure would demonstrate value. Sector-specific compliance, data-handling and infrastructure needs can affect those choices.
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AWS also emphasizes cloud and managed infrastructure in its discussion. That is the research sponsor’s perspective, not a neutral comparison of infrastructure providers; the study summary does not establish which vendor or deployment model is best for a particular business.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the survey says about agentic AI
AWS reports that 38% of surveyed businesses had heard of agentic AI. Among that subset—not among all businesses—8% had embedded agents in core workflows, while 19% were experimenting with or piloting them. The conditional denominator matters: the latter figures cannot be read as shares of all Vietnamese businesses.
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How much weight to give the company examples
AWS’s summary profiles examples from its own customers, which can illustrate particular uses but should not be treated as representative results for Vietnam’s businesses. It says more than 460 TCBS staff use the Kiro software-development environment, development time fell by nearly 25%, and 70% of AI-generated code passed first reviews. These are figures in AWS’s company example, not findings from a controlled, sector-wide comparison.
The same summary describes OmiGroup’s OmiKG research tool and says it identified 15 of 17 molecular mechanisms for Type 2 Diabetes in a controlled research evaluation. That specific evaluation does not establish clinical effectiveness or show that the tool can diagnose or treat patients.
What the 2026 findings do—and do not—show
The study presents a picture of rising business adoption alongside uneven organizational maturity. Its figures suggest many adopters are testing AI while relatively few report comprehensive strategy or consistent ROI measurement. Reported gains are encouraging signals from respondents, but they are not proof that AI caused revenue or productivity improvements. For businesses, the central question is therefore not only whether to try AI, but how to govern, measure and integrate it well enough to determine whether it works in their own setting.
Eric Yeo, AWS Country General Manager for Vietnam, said: “Every organization is at a different point in its AI journey, but the direction is clear. Businesses that move thoughtfully from experimentation to implementation, supported with cloud infrastructure, regulatory clarity, and skills will be best positioned to compete and grow.” This is an AWS executive’s view, and AWS commissioned the study.
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