In 2024, the global AI wave will sweep across the world, and Thailand, as an important economy in Southeast Asia, will also usher in the opportunity of the AI explosion. This article will conduct an in-depth analysis of the factors that drive the booming development of Thailand's AI market, and explore the reasons for the rapid growth of Thailand's AI market from aspects such as the popularization of open source models, seamless integration of ecosystems, acceleration of talent training, and AI's significant ability to reduce costs and increase efficiency. , and look forward to its future development prospects. The article will also objectively point out the challenges faced by Thailand's AI development, such as the uncertainty of cost forecasts and AI security risks, and propose corresponding response strategies.
In 2024, the global AI craze continues to rise, and Thailand is no exception. It is on the eve of an artificial intelligence (AI) explosion. Imagine that you are walking on the streets of Bangkok, and everything around you is quietly changing. The smart ordering system in the restaurant can talk to you in fluent Thai, and the AI diagnostic system in the hospital can accurately analyze your physical condition. Shared bicycles on the roadside are equipped with intelligent navigation. This is by no means a fantasy, but an AI revolution taking place in Thailand.
How violent is this wave? Data agency Statista predicts that Thailand's generative AI (GenAI) market will reach US$80 million in 2024 and maintain an average annual growth rate of 46.5% from 2024 to 2030. By 2030, the market The scale will reach 7.7 billion baht. In the "Thailand Digital Technology Outlook Report 2035", Thailand's Digital Economy Promotion Agency (DEPA) even boldly predicted that by 2030, the size of Thailand's AI market will reach 114 billion baht! This is simply an astonishing figure for "Thailand" feast!
So, what makes Thai AI so "arrogant"? Behind this is not simple luck, but the result of the combined effect of multiple factors:
Open Source open source model ignited the fuse of AI popularization. In the past, large language models (LLM) were popular in the field of AI, but they often required massive amounts of data and computing power, which discouraged many companies. Now, with the rise of small language models (SLM) and open source AI models, and the emergence of more and more skilled technical personnel, the situation is changing dramatically. These open source models not only provide greater transparency and flexibility, but also save enterprises significant computing costs. Especially for industries that require customized AI solutions, open source models are like tailor-made suits that fit and are comfortable. They reduce enterprise dependence on specific vendors, promote community-driven innovation, and help build more trustworthy AI strategies. Juhi McClelland, managing partner of IBM's Asia Pacific consulting business, said that although general-purpose large-scale language models have their advantages, a "one-size-fits-all" solution is not the best choice for all enterprises, especially in some highly specialized industries.
The seamless integration of the ecosystem has given wings to the explosion of AI. It’s not enough to have AI models, you also need a stage where they can “flex their muscles”. Therefore, seamless integration of application platforms with various models has become critical to ensure greater interoperability and adaptability, allowing enterprises to quickly keep up with the pace of AI development. Imagine that the APP you develop can be easily connected to various AI models like building blocks. This experience is simply not too pleasant! Anothai Wettayakorn, general manager of IBM Thailand, said that IBM will promote open source models and other four key factors to accelerate the pace of enterprise adoption of GenAI. His goal is to help 5-6% of Thai companies adopt GenAI this year and increase this number to 15-20% next year to enhance Thailand's competitiveness.
The cultivation of talents is the real driving force for the development of AI. Just like building a house, drawings and materials alone are not enough, you also need skilled workers. Vatsun Thirapatarapong, general manager of Amazon Cloud Services (AWS) Thailand, said that GenAI is still a relatively new technology and many projects are still in the proof-of-concept stage. Enterprises are using these early projects to learn best practices, assess value, and gain experience to lay the foundation for future large-scale deployments. He believes that the talents behind the technology are the key to innovation, and this is precisely the bottleneck in the current popularity of GenAI. Therefore, AWS plans to train 100,000 AI talents in Thailand by 2026 to meet the market demand for AI talents. At the same time, the Thai government’s cloud-first strategy and policies to build Thailand into a digital economic center are also driving demand for cloud computing and GenAI in all walks of life. With talent and policies, there will be soil for AI to take off.
AI's ability to reduce costs and increase efficiency is a "catalyst" for companies to enter the industry one after another. The powerful automation capabilities of generative AI can help enterprises improve efficiency, reduce repetitive labor, and reduce operating costs. This is undoubtedly a boost for enterprises that pursue high efficiency. For example, AI tools can help developers increase their work speed by 57%. This efficiency is unparalleled! Not only that, GenAI can also spawn new applications, products and services, helping companies stand out in the fierce market competition. Currently, areas such as banking/financial services, healthcare, and manufacturing/supply chain have become the focus of GenAI’s efforts.
Of course, the development of AI is not smooth sailing. Patama Chantaruck, managing director of Accenture Thailand, said that Thailand still faces some challenges on the road to developing GenAI, such as: unpredictable costs, security risks and AI illusions (AI Generating content that appears reasonable but is actually incorrect). Gartner's research shows that GenAI cost estimates can be subject to errors of 500-1000%, making it difficult for companies to make large-scale investments without clear returns.
In order for GenAI to really work, companies cannot just stay at the proof-of-concept stage, but must pay more attention to its actual value, prioritize productivity improvements, pay close attention to AI-related costs, and monitor expenditures in real time to avoid financial mistakes. IBM believes that in 2024, many enterprises will have begun to directly link AI to business value and return on investment, moving from AI ambition to AI action. By 2025, the focus will shift from experimentation to real business results, and enterprises will deploy AI on a large scale to achieve a significant return on investment.
Nvidia founder and CEO Jensen Huang said during a recent visit to Thailand that the first generation of AI is based on numbers and information, similar to chatbots. The second generation of AI will combine with robotics to create self-driving cars and robots used in industries such as agriculture. In the future, robots will integrate into human workplaces, increase productivity, and revolutionize various industries. He also emphasized that the future of AI in Thailand requires three key steps: establishing AI infrastructure that can generate intelligence and change industries; cultivating skilled talents with the ability to operate and develop AI technology; and promoting the application of AI in various industries to drive the economy increase.
All in all, Thailand is on the cusp of an AI explosion. Driven by the open source model, talent training, government policies, corporate transformation and other forces, the Thai AI market will surely usher in a more brilliant tomorrow!
All in all, the rapid development of Thailand's AI market is the result of multiple factors, and there is huge potential for future development. But at the same time, we need to pay attention to potential risks and actively respond to challenges to ensure the healthy and sustainable development of Thailand's AI industry and ultimately achieve the goal of economic transformation and upgrading.