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AI in trade, industry set to increase Thai GDP by 6%

Generative artificial intelligence (GenAI) is projected to raise Thailand’s GDP by 6% by 2030, with hefty contributions from the trade and manufacturing sectors, according to a joint online survey by SCB X and SCB Economic Intelligence Center (SCB EIC).
“Despite having a clear AI vision, Thailand still faces challenges in technology development, governance and regulation, government adaptation, and data readiness,” said Nakarin Amarase, head of the external affairs division and corporate strategy function at Siam Commercial Bank (SCB).
According to the SCB X-SCB EIC survey of small and medium-sized enterprises’ (SMEs) business readiness for GenAI, conducted during April 18-25, 2024, the companies are increasingly familiar with GenAI and have started using AI more widely, especially in the manufacturing and service sectors.
They are using GenAI for marketing and sales, as well as seeking additional information and new business ideas.
However, Thai SMEs are not fully prepared for the arrival of GenAI, particularly in terms of data readiness and infrastructure, noted the survey.
Most of the businesses that are not yet ready are in the construction and trade sectors, and the majority need 2-5 years to be able to fully use GenAI.
In Thailand, GenAI would raise GDP by 6% by 2030, with big contributions from trade and manufacturing, said Mr Nakarin.
In another study, the IDC Data and AI Pulse: Asia Pacific 2024, commissioned by AI analytics firm SAS, only 23% of organisations in Southeast Asia were described as transformative in their AI adoption.
This refers to organisations with a longer-term investment plan that use AI to transform markets and customers by creating new business models as well as product and service experiences.
The study conducted in June surveyed 101 enterprises in Singapore, Malaysia and Thailand, finding the leading reasons for AI failure are untrustworthy or poor quality data (40%), privacy concerns or compliance limitations (38%), and an inability to access data because of business restrictions (36%).
The survey highlights the challenges faced by early adopters, such as a lack of specialised skilled personnel (41%), managing costs associated with AI development and deployment (30%), and lack of clear evaluation criteria for AI solutions (29%).
Singapore stands out as a regional leader in AI adoption, while Thailand and Malaysia are emerging as promising AI markets, with the aim of harnessing AI’s potential to improve operational efficiency, boost profitability, and have a strong emphasis on achieving cost savings.
Both Thailand and Malaysia are taking a wait-and-see approach, observing the evolution of AI technologies and use cases before introducing dedicated AI policies.
“Across Southeast Asia, we observe differing levels of AI maturity. While more leaders in the field are emerging in Singapore, businesses in Thailand and Malaysia are still in the early to mid stages of adoption,” said Amir Sohrabi, regional vice-president and head of digital transformation for Korea and the Asean region at SAS.
While consumer access to generative tools made AI feel magical, the actual implementation of AI into an enterprise environment requires a strong data foundation and structured process for organisations to reap the benefits of AI in an effective and responsible way, he added.

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