Nearly 75% of Vietnamese businesses have started experimenting with or deploying AI, yet only 6.3% have proven measurable AI ROI at the portfolio level. That is the headline finding from the CIO Vietnam Survey 2026, released jointly by the Vietnam CIO community and EY Vietnam at CIO Summit 2026 in Ho Chi Minh City on October 1, 2026.
What does the CIO Vietnam Survey 2026 show about AI deployment stages?
More than 81% of surveyed businesses say AI saves time and boosts productivity. But the survey maps a steep drop-off as businesses move from early experimentation toward proven economic results, according to data released at CIO Summit 2026.
- Exploration stage: 23.4% of businesses
- Piloting stage: 26.6%
- Production stage: 32.8%
- Scaling stage: 10.9%
- Deep integration with proven economic results: 1.6%
Put differently: roughly 83% of Vietnamese businesses are still at or before the production stage. Only 1 in 60 has reached deep, economically verified AI integration.
Why is there a gap between AI activity and proven AI ROI?
Shashidharan Jagadiswaran, Deputy General Director and Technology Advisor at EY Vietnam and lead researcher of the survey, draws a clear line: wide AI deployment does not automatically generate economic value. AI can help employees work faster or automate one step in a process, but if that speed does not move measurable business metrics, revenue, cost, profit, it has not become financial value at the enterprise level.
His framing at CIO Summit 2026: Are we using tomorrow’s technology to do yesterday’s work? The question is not how much faster AI makes existing work, but whether it actually changes how a business operates, generates revenue, and builds new business models.
The survey’s signal: the question Vietnamese CIOs face is shifting from Where can we apply AI? to What economic value does AI create, and how do we measure it?
What do international case studies reveal about AI and measurable results?
EY Vietnam cited four Asia-Pacific examples at CIO Summit 2026, each illustrating a different lesson.
DBS Bank (Singapore): AI was deployed against specific business problems. In 2024, the bank recorded SGD 750 million in economic value from AI and machine learning, double the prior year, running more than 1,500 AI models across approximately 370 business use cases, as cited by EY Vietnam.
Commonwealth Bank (Australia): A cautionary case. The bank eliminated 45 positions and replaced them with an AI chatbot reportedly reducing around 2,000 calls per week. Call congestion increased afterward, staff worked overtime, and the eliminated positions were eventually restored. The outcome is attributed to automating before redesigning the underlying process.
OCBC Bank (Singapore): Internally developed GenAI (generative AI) tools helped boost staff productivity by up to 50%. OCBC GPT was deployed to approximately 30,000 employees, as cited by EY Vietnam.
Ping An (China): AI Agents (software that executes multi-step tasks with a degree of autonomy) handle roughly 80% of customer service traffic, with more than 1.5 billion interactions. The system auto-underwrites approximately 93% of life insurance contracts. Performance is evaluated on actual business outcomes, not on model count or usage volume.
The common thread across all four: AI is measured by its impact on business operations, not by the number of models deployed or how frequently they are used.
How are Vietnamese businesses planning AI investment through 2027?
Budget appetite is growing. The CIO Vietnam Survey 2026 projects the share of businesses willing to allocate more than 5% of revenue to IT will rise from 22% in 2025 to 32.4% in 2027. More than 67% of CIOs expect technology budgets to grow by more than 10% annually.
Priority is also shifting: 78.4% of CIOs now identify driving revenue and creating new business models as their top technology priority, a move away from pure operational optimization.
On risk governance, the report cites Samsung Electronics temporarily banning GenAI tools on company devices after an employee uploaded internal source code to an AI platform. The case illustrates that defining what AI is permitted to do, who is accountable, and when to shut a system down is part of the same value equation as efficiency gains.
What does the survey show about Agentic AI adoption?
Agentic AI (AI systems capable of relatively autonomous action, such as browsing, executing tasks, and making decisions within set boundaries) is moving from concept toward deployment among Vietnamese businesses, per the CIO Vietnam Survey 2026.
- Applied AI remains the top priority: 81.1% of businesses
- Around 35% of businesses have AI Agents in production
- Only 7.2% allow AI to make decisions autonomously within defined policies
- CIO priority for Agentic AI is projected to jump from 30% in 2026 to 60.4% in 2027
- Demand for staff with GenAI and Agentic AI skills is forecast to grow from 53.1% to 69.4% by 2027
As VnEconomy frames it, the gap between AI application and proven economic value becomes more consequential, not less, as systems gain more autonomy.
What principles and timeline does the report recommend?
The CIO Vietnam Survey 2026 outlines four principles for closing the deployment-to-value gap:
- Do not deploy AI without a clear business objective.
- Do not put AI into operations without a named business owner who is accountable.
- Do not grant AI autonomy without defined risk-control boundaries.
- Do not scale without evidence of financial results.
It also proposes a 90-day roadmap:
- Days 1-30: Audit and eliminate pilot projects that lack clear goals.
- Days 31-60: Define roles, access rights, decision authority, and accountability for each AI initiative.
- Days 61-90: Redesign one critical process and measure net financial value.
What this means for AI-search visibility
The 6.3% figure matters beyond the boardroom. It points to a shift that will shape how businesses appear, or fail to appear, in AI-powered search results.
Here is the practical reality: saying “we use AI” is now a claim almost every competitor can make. What separates a business in AI-powered search, partner evaluations, or procurement decisions is evidence. DBS’s SGD 750 million figure and Ping An’s 93% auto-underwriting rate are the kind of figures that travel because they are specific and verifiable. Vague claims about “leveraging AI to enhance operations” do not travel the same way.
For businesses that publish content, this dynamic applies directly to AI-search visibility. A page that documents a specific, measured result (for example, a stated reduction in claims processing time over a named quarter) is structurally more citable than one that only says we embrace AI innovation.
In Hingewise’s view, the 90-day framework in this report is a content and visibility blueprint as much as a deployment checklist. Businesses that document their AI journey with real metrics, including what failed (see: Commonwealth Bank’s chatbot reversal), create the kind of authoritative, citable content that AI search systems can work with. Specific, verifiable outcomes, whether successes or failures, give AI systems something concrete to reference, unlike generic claims about embracing innovation.
The deeper signal from this survey: Vietnamese businesses are entering the phase where AI literacy shifts from “can we do this?” to “can we prove it?” That transition is also a content strategy transition. Brands that publish quantified AI results will likely build more Share of Model (the rate at which an AI mentions a brand relative to its competitors in relevant queries) than those publishing aspirational statements. The 1.6% at deep integration are the ones worth watching, specifically to see whether they start publishing the numbers.
Source: VnEconomy, “AI và giá trị kinh tế: Những thách thức cho doanh nghiệp Việt”, published October 2, 2026. Based on the CIO Vietnam Survey 2026, presented at CIO Summit 2026, Ho Chi Minh City, October 1, 2026.
Lam Nguyen · Hingewise
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.