In 2024, the global AI wave continues to surge, and Thailand is no exception, standing on the eve of an AI explosion. Imagine strolling through the streets of Bangkok, where everything is quietly changing around you. Restaurants have intelligent ordering systems that can converse fluently in Thai, AI diagnostic systems in hospitals can accurately analyze your health, and even shared bicycles on the street are equipped with smart navigation. This is not a fantasy; it's the ongoing AI transformation happening in Thailand.
Image Source Note: Image generated by AI, image licensed from Midjourney
How intense is this wave? According to data agency Statista, the generative AI (GenAI) market in Thailand is expected to reach $80 million in 2024, maintaining an average annual growth rate of 46.5% from 2024 to 2030, with the market size projected to reach 77 billion THB by 2030. Furthermore, the Digital Economy Promotion Agency (DEPA) of Thailand boldly predicts in the "2035 Thailand Digital Technology Outlook Report" that the AI market in Thailand will reach 114 billion THB by 2030! This is truly a "Thai"mazing digital feast!
So, what makes Thailand's AI so "luxurious"? It's not just luck but a result of multiple factors working together:
Open Source Models Ignite the Fuse for AI Popularization. In the past, large language models (LLMs) were the "darling" of the AI field, but they often required vast amounts of data and computing power, deterring many companies. Now, with the rise of small language models (SLMs) and open-source AI models, along with an increasing number of skilled technicians, the situation is undergoing a dramatic change. These open-source models not only offer greater transparency and flexibility but also save companies significant computing costs. Especially for industries needing customized AI solutions, open-source models are like tailor-made suits—both fitting and comfortable. They reduce companies' dependence on specific vendors, promote community-driven innovation, and help build more trustworthy AI strategies. Juhi McClelland, IBM's Partner in Consulting for the Asia-Pacific region, states that while general large language models have their advantages, "one-size-fits-all" solutions are not the best choice for all companies, especially in highly specialized industries.
Seamless Integration of Ecosystems Gives Wings to AI's Explosion. Having AI models alone is not enough; a stage for them to showcase their capabilities is also needed. Therefore, seamless integration of application platforms with various models becomes crucial, ensuring greater interoperability and adaptability, allowing companies to quickly keep pace with AI developments. Imagine your developed app easily integrating various AI models like building blocks—what an incredible experience! Anothai Wettayakorn, IBM's General Manager in Thailand, states that IBM will accelerate the adoption of GenAI by promoting open-source models and other key factors. His goal is to help 5-6% of companies in Thailand adopt GenAI this year and increase that number to 15-20% next year, enhancing Thailand's competitiveness.
Talent Development is the True Driving Force Behind AI Progress. Just like building a house, having blueprints and materials is not enough; skilled workers are also needed. Vatsun Thirapatarapong, General Manager of Amazon Web Services (AWS) Thailand, states that GenAI is still a relatively new technology, and many projects are still in the proof-of-concept stage. Companies are using these early projects to learn best practices, assess value, and gain experience to lay the groundwork for future large-scale deployments. He believes that the talent behind the technology is key to innovation, which is precisely the bottleneck for GenAI's popularization at present. Therefore, AWS plans to train 100,000 AI professionals in Thailand by 2026 to meet the market's demand for AI talent. Meanwhile, the Thai government's cloud-first strategy and policies aimed at making Thailand a digital economy hub are also driving the demand for cloud computing and GenAI across various sectors. With talent and policy in place, the soil for AI's takeoff is ready.
The Cost-Reduction and Efficiency-Enhancing Capabilities of AI are Catalysts for Business Involvement. The powerful automation capabilities of generative AI can help companies improve efficiency, reduce repetitive tasks, and lower operational costs, which is undoubtedly a shot in the arm for profit-driven businesses. For example, AI tools can help developers increase their work speed by 57%, an unmatched efficiency! Furthermore, GenAI can give rise to new applications, products, and services, helping businesses stand out in fierce market competition. Currently, sectors like banking/financial services, healthcare, and manufacturing/supply chain are among the first to leverage GenAI.
Of course, the development of AI is not without its challenges. Patama Chantaruck, Managing Director of Accenture Thailand, states that Thailand still faces some challenges in developing GenAI, such as unpredictable costs, security risks, and AI hallucinations (AI-generated content that appears reasonable but is actually incorrect). Gartner's research indicates that cost estimates for GenAI can vary by 500-1000%, making it difficult for companies to make large-scale investments without clear returns.
To make GenAI truly effective, companies must not remain at the proof-of-concept stage but focus more on its actual value, prioritize productivity enhancement, closely monitor AI-related costs, and track expenditures in real time to avoid financial errors. IBM believes that by 2024, many companies will begin to directly link AI with business value and return on investment, transitioning from AI ambitions to AI actions. By 2025, the focus will shift from experimentation to actual business outcomes, with companies deploying AI on a large scale to achieve substantial returns on investment.
Nvidia's founder and CEO, Jensen Huang, recently stated during his visit to Thailand that the first generation of AI is based on digital information, similar to chatbots. The second generation of AI will combine robotics technology to create self-driving cars and robots for industries like agriculture. In the future, robots will be integrated into human workplaces, enhancing productivity and transforming various industries. He emphasized that the future of AI in Thailand requires three key steps: establishing AI infrastructure capable of generating intelligence and transforming industries; cultivating skilled talent capable of operating and developing AI technology; and promoting the application of AI across various sectors to drive economic growth.
In summary, Thailand stands at the forefront of an AI explosion. With the joint efforts of open-source models, talent development, government policies, and business transformation, the Thai AI market is sure to usher in a more brilliant tomorrow!
