Southeast Asia's AI Potential Held Back by Investment Gap

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Technology Новости

AI,Investment,Southeast Asia

While AI giants are investing heavily in Southeast Asia, local startups struggle to attract funding, raising concerns about the region's ability to compete in the global AI landscape.

South-East Asia is quickly becoming a prime investment location for AI giants like Nvidia and Microsoft, who are pouring capital into cloud services and data centers. However, the region's own burgeoning tech companies are struggling to capitalize on this AI boom.

While global companies are projected to invest up to US$60 billion in South-East Asia over the next few years, as its young population embraces video streaming, online shopping, and generative AI, little of this investment is reaching AI-focused startups. Investors are hesitant to back unproven ventures, and the region has yet to demonstrate its ability to produce innovative firms capable of substantial growth. Venture investment in Southeast Asia's young AI companies has only reached US$1.7 billion this year, a mere fraction of the US$20 billion invested across the Asia-Pacific region, according to Preqin. The disparity is raising concerns about Southeast Asia's capacity to develop its private sector and compete with the US and China, the world's leading AI nations. This venture investor skepticism is hindering the growth potential of the entire homegrown tech sector in Southeast Asia. Globally, investors are eager to capitalize on the AI opportunity, but their focus remains primarily on the US and China. The US attracted US$68.5 billion in AI funding in 2024, while China secured approximately US$11 billion, Preqin data reveals. Despite this, Southeast Asia, with its population of 675 million, boasts over 2,000 AI startups, exceeding the number in South Korea and nearly matching those in Japan and Germany, according to a report by tech advisory firm Access Partnership. Singapore, the region's leading business hub, ranks third in the Global AI Index, excelling in indicators such as the number of AI scientists per million people

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