Thailand pushes AI skills and adoption to lift competitiveness

Thailand needs to accelerate artificial intelligence adoption, strengthen education and data capabilities, and bring government, universities and businesses into closer collaboration if it is to raise productivity and remain competitive, three panellists told a Bangkok forum.

The discussion was part of “THAILAND’S MOMENTUM 2026: Navigating a Fragmented World”, hosted by the Foreign Correspondents’ Club of Thailand (FCCT) on Wednesday (September 16).

The panel brought together Prof Dr Yodchanan Wongsawat, Deputy Prime Minister and Minister of Higher Education, Science, Research and Innovation; Dr Kobsak Pootrakool, director and senior executive vice-president of Bangkok Bank; and Jirayut Srupsrisopa, founder of Bitkub Capital Group Holdings.

Yodchanan puts data, skills and niche technology at the centre

Yodchanan argued that Thailand should build its AI strategy around areas where it can develop distinctive capabilities rather than attempting to compete directly with larger economies in mass production.

“The thing is, we also need to build two things: high technology and also human capital development. We cannot compete with mass production at all with China,” he told the forum.

He identified biodiversity, agriculture, environmental technology and other areas generating valuable local data as potential strengths. Combining information from sources such as agriculture, soil, weather and space could help Thailand create models and applications tailored to domestic needs and potentially relevant to other tropical markets.

Data, he argued, should be treated as a national asset, while Thailand should retain a degree of technological sovereignty in strategically important areas rather than depending entirely on one company or country.

Yodchanan also pointed to selected parts of the AI and technology supply chain where Thailand could build deeper expertise, including photonics, advanced semiconductor packaging, sensors and high-value local content linked to data centres.

Instead of trying to master every part of emerging technologies, Thailand should develop specialised capabilities that can fit into international supply chains, while using science diplomacy and partnerships with other countries to fill gaps.

Education would be central to that transition. Yodchanan argued that schools and universities should place greater emphasis on enduring foundations such as mathematics, algorithms, physics, chemistry and biology, while also developing creativity, entrepreneurship, design thinking and systems thinking.

“Education should be the new infrastructure for Thailand. So when you know that we have enough education, even though AI is coming, we can think about something to leverage AI,” he said.

He also called for lifelong learning, reskilling and upskilling as technologies change, while encouraging Thai researchers, entrepreneurs and companies to think beyond the domestic market and connect more closely with global partners.

Kobsak says AI must translate into business productivity

Kobsak described AI as a technological transformation on the scale of electricity and the steam engine, but warned that the pace of development was moving faster than many people and organisations could adapt to.

“The key risk of AI and its big advancement is the speed of the AI. It has exceeded the ability of people and also organisations to adapt,” he said.

For businesses, he argued, the challenge was not simply about adopting the latest models or launching pilot projects. Companies needed reliable data and had to integrate AI-generated recommendations into real decision-making and daily operations.

“If you would like to adopt AI, you have to have the right data sets first. To adopt AI without the right data will get you nowhere,” Kobsak said.

He noted that many organisations were experimenting with AI without yet achieving clear financial results, and argued that treating AI as a showcase project rather than embedding it in operations would limit its impact.

The next stage, he added, would involve combining AI with sensors, robotics and automation. Thai manufacturers increasingly face competition from highly automated Chinese factories, making technological upgrades important for maintaining productivity and cost competitiveness.

Kobsak cited an SCG ceramics operation where only seven people were needed to run a factory supported extensively by automation, robotics and AI. He used the example to illustrate both the productivity gains available from new technology and the disruption it could create for employment.

He argued that the private sector should take the lead in investment, while the government should improve data availability and quality, strengthen AI infrastructure and cloud services, and establish an appropriate legal framework to build trust.

Education would also need to focus increasingly on people’s ability to use AI effectively in their work. Kobsak called for training that moves users beyond basic awareness towards more advanced applications, workflow automation and AI-driven innovation.

Jirayut calls for an AI-first economy

Jirayut argued that AI and other Fourth Industrial Revolution technologies were creating a widening divide between countries able to adopt them quickly and those that remained tied to older economic models.

He pointed to China’s adoption of AI, smart factories and automation as an example of how technology could reshape productivity and industrial competitiveness.

For Thailand, however, he argued that competing in the most capital-intensive layers of AI infrastructure would be difficult. Instead, the country should concentrate on localising AI models and, above all, applying AI tools across the economy.

“Thailand as a country should be an AI-first nation in order to leapfrog, in order to leverage on this platform shift. We should make sure that every enterprise here would be an AI-first enterprise,” he said.

Jirayut linked that approach to Thailand’s demographic challenges, arguing that AI could help raise output per worker as the population ages and the workforce comes under pressure.

He also called for a different approach to education. Basic literacy, mathematics and English would remain essential, but schools and universities should move beyond memorisation towards reasoning, creativity and the ability to formulate useful questions.

“We should shift from remembering stuff towards reasoning, and also from the ability to answer the right questions to the ability to ask the right questions, because AI will be doing all the answering in the future,” he said.

In his view, government should create the right regulatory and innovation environment, universities should develop human capital and support workforce reskilling, and the private sector should apply technology to real business problems with greater urgency.

Jirayut argued that AI should not be confined to a handful of industries because, like the internet or computers, it represented a broader platform shift with applications throughout the economy.

“So the answer is to apply AI with urgency across literally every single sector,” he concluded.

Turning AI adoption into long-term competitiveness

Despite approaching the issue from government, banking and technology perspectives, the three panellists converged on a common theme: AI adoption alone will not be enough to strengthen Thailand’s competitiveness. The country will also need stronger human capital, better use of data, appropriate regulation and closer cooperation between the public and private sectors.

Their discussion also underscored that the challenge is not simply whether Thailand adopts AI, but whether the technology can be translated into higher productivity, new skills and economic opportunities across the wider economy.