What the First Thailand AI Workforce Readiness Data Tells CEOs and CHROs
By Dr. Nattavut Kulnides, Founder & CEO, ADGES
In June 2026, ADGES surveyed 95 HR and business leaders across Thailand, the first time Thai organizations have been benchmarked against the Asia-Pacific region on AI adoption and workforce capability readiness. The data we presented at Thailand HR Tech 2026, alongside Cornerstone OnDemand’s own Asia-Pacific research covering 3,732 respondents across eight markets, reveals something important: Thailand is moving, but moving is not the same as transforming.
This article is for the CEOs and CHROs who were in the room that day, and for those who were not. It is not a summary of slides. It is an attempt to translate what the data is actually telling you and to put squarely on the table the decision you now need to make.
The Gap No One Wants to Talk About
Start with the headline: 73.7% of Thai organizations describe themselves as actively experimenting with, scaling, or transforming through AI. That sounds encouraging. But then ask the follow-up question: What percentage of your workforce has received meaningful AI upskilling in the past 12 months? And the picture changes.
62.1% of Thai organizations have reached fewer than 30% of their people.
This is not a minor inconsistency. It means that nearly half the organizations that say they are scaling or transforming AI have left the majority of their workforce behind. Deployment is moving fast. Capability is not. And the gap between those two things is precisely where transformation dies.
The Cornerstone OnDemand APJ 2026 research adds critical context: across eight Asia-Pacific markets, the single largest perception gap 24.4 points, sits in the AI and Workforce Planning pillar. HR leaders believe the organization is ready. Employees experience something different. Thailand is not unique in this, but the data suggest we are more exposed to it than most.
Four Gaps. One System Problem.
Our research identified four interlocking gaps. The important word here is “interlocking.” These are not four separate problems to be solved by four separate programmers. They are one system problem. Each gap feeds the next.
Gap 1: Skills Visibility. 82% of Thai organizations do not have complete, data-driven visibility into the skills their workforce holds today, let alone the skills it will need tomorrow. If you cannot see what you have, you cannot target what you build. This is not a technology argument. It is a leadership argument. You cannot make good resourcing decisions without good data. And right now, most Thai organizations are making workforce decisions in partial darkness.
Gap 2: Leadership Capability. The average leadership AI confidence score across our sample was 2.89 out of 5. 64% of organizations rate their senior leaders at 3 or below “aware and developing, but not yet capable of driving transformation at scale.” This matters more than it might appear. There is a meaningful difference between a leader who sponsors AI transformation and a leader who drives it. A sponsor approves budgets and endorses AI in all-hands communications. A driver sets specific capability targets with deadlines, uses AI tools personally and makes that visible, holds business units accountable for outcomes, and makes resourcing decisions using skills data. Thailand has plenty of the former. It does not yet have enough of the latter.
Gap 3: Learning Infrastructure. 71.6% of Thai organizations are operating without the infrastructure to measure whether their learning investments are working. The most common platform type, cited by 51.6% of respondents, is informal tools. Teams, Line, and ad hoc channels. When a full-day training session is logged as a tick in a spreadsheet, you have no way of knowing whether a skill was actually built, whether it changed behavior, or whether it contributed anything to business performance. Yet 70.5% of those same organizations plan to increase their AI and L&D investment in the next 12 months.
These two numbers describe the same group of organizations. The question is not whether to invest. It is what to build before you invest at scale.
Gap 4: Strategic Alignment. 28.4% of organizations describe their L&D strategy as having low or no connection to their AI and business transformation priorities. Training is happening. It is not pointed at the right outcomes. As the Cornerstone APJ research shows, Learning Activation is the single strongest driver of workforce capability maturity, accounting for 24.8% of total index influence. But learning is only a driver when it is aligned to future skill needs. Learning that is disconnected from strategy builds the wrong capabilities for the future.
The organizations closing all four gaps simultaneously are the 14.7% already transforming.
The Investment Paradox
Let me put this as plainly as I can: 70.5% of Thai organizations plan to spend more on AI and learning in the next 12 months. 71.6% of those same organizations cannot tell you what the previous spending produced.
This is not a funding problem. It is an infrastructure problem masquerading as an ambition problem. Increased investment in an unmeasured system produces more of the same fragmented activity at a higher cost. Before you approve another budget cycle, the more important question is: what will you build that makes the spending measurable?
The analogy I used in the keynote was wearable technology. When we only had an annual health check-up, the data arrived too slowly and too infrequently to change behavior. Wearables changed that real-time visibility, real-time feedback and real behavioral change. A well-implemented learning platform is exactly this for organizational health. The value is not in the tool. It is in the data that the tool makes visible.
Thailand’s Real Competitive Advantage and the Risk of Wasting It
Here is the finding that surprised most of the room: 82% of Thai employees describe their attitude toward AI as positive or proactive. Against an APJ average of roughly 52%, and Japan at just 30%, that number is extraordinary.
Thai employees are not resisting AI. They are not afraid of it. They are curious, ready, and willing to be developed. This is not a soft metric. According to the Cornerstone economic model, Culture, Engagement and Trust account for 30% of the total economic value unlocked by workforce capability improvement. The willingness of Thai employees to engage with AI is, right now, the organization’s most commercially valuable and most underutilized asset.
But that willingness is not permanent. 82% positive today does not mean 82% positive in 24 months if organizations continue deploying AI without developing their people. Enthusiasm erodes when it is not met with genuine investment. The window is open. It will not stay open indefinitely.
Three Decisions for the Next 90 Days
The data points toward three sequenced decisions. These are not three programmers or three workstreams. Three decisions change the trajectory and they need to be made this quarter, not next year.
Decision 1: Measure. Before you invest further, create visibility. Run a formal skills assessment. Map current capabilities against your organization’s strategic direction for the next two to three years. Identify which skills are becoming obsolete and which need to be built. This is the data that makes everything else targeted rather than generic.
Decision 2: Build. Create the infrastructure that turns learning investment into a measurable outcome. This means a platform that captures what your people are learning, connects that learning to performance data, and generates the skills visibility your organization currently lacks. Without this, you are spending more to know less.
Decision 3: Develop. Develop leaders who drive transformation, not just endorse it. This is the conversation every CHRO needs to have with their CEO. The question is not whether the CEO supports AI. The question is whether they are willing to set specific capability targets, model AI adoption personally, hold their direct reports accountable for building skilled teams, and make resourcing decisions based on skills data rather than headcount instinct.
Each decision is deliberately sequenced. Measuring creates the data that makes building targeted. Building creates the infrastructure that makes leadership development accountable. Without measurement, you are developing leaders in a vacuum. Without infrastructure, you cannot connect their decisions to outcomes.
The Closing Question
Thailand has the employees. The question the one I left the room with, and the one this article is intended to push further is whether Thai organizations will build the leadership and infrastructure to meet them.
The cost of not acting is not hypothetical. The Cornerstone research estimates that for every 1,000 employees, a 10-point improvement in workforce capability unlocks millions in economic value annually through reduced attrition, reduced absenteeism, and improved hiring efficiency. Across comparable regional markets, the dominant share of that cost 85% comes from people already inside the organization. Not from hiring.
The talent you need is largely already in the building. The capability gap is real but closeable. The employees are willing. The investment intent is there.
What is missing is the decision to build the system that makes it all work together.
That decision is yours to make.
Dr. Nattavut Kulnides is Founder and CEO of ADGES, a Bangkok-based leadership development and HR consulting firm, and a Reseller Partner of Cornerstone OnDemand. This article is drawn from his keynote at Thailand HR Tech 2026 (June 16–17, Siam Paragon), where ADGES presented the first Thailand data point against the Cornerstone APJ Culture and Capability Index. The full research deck and supporting data are available on request.