Southeast Asia is at a point where its digital economy, youthful population — more than 200 million people aged between 15 and 34 — and government-led tech initiatives could accelerate the adoption of AI. This technology holds transformative potential for Southeast Asia’s economies: McKinsey estimates AI could add US$1 trillion to the region’s GDP by 2030, potentially revolutionising everything from rural agriculture to urban healthcare systems.
However, without bolder AI strategies, Southeast Asia risks remaining an adopter rather than an innovator. The region also faces several structural hurdles that could limit its AI potential: fragmented regulations, uneven investment, increased energy demand from AI data centres, and a shortage of deep-tech capabilities. Whether Southeast Asia gains ground or remains on the periphery will depend on how well governments, investors, and the private sector coordinate around AI development in the next few years.
Moving beyond experimentation
Unlike manufacturing and other traditional industries that require extensive physical infrastructure, AI development can scale rapidly with relatively modest initial investments. A small, highly skilled team with sufficient data can build sophisticated AI solutions within months.
Yet competition is fierce; established players in China, the United States, and elsewhere already enjoy significant advantages in capital, talent, and research capabilities. Southeast Asia has an opportunity — albeit a narrow one — to move beyond pilot projects and proofs of concept, rather than relying primarily on imports of AI solutions from other markets.
Comparing with established AI hubs
When comparing Southeast Asia with established AI hubs, some important distinctions emerge:
- China: Powered by extensive state support, enormous data pools, and a rapidly expanding AI industry, it has implemented large-scale AI applications in transportation, fintech, and smart cities.
- US: Bolstered by strong research pipelines, robust venture capital networks, and an active enterprise market, it maintains a leadership position in foundational and applied AI research.
All ASEAN nations have introduced AI strategies, but progress varies significantly:
- Singapore leads with a SG$500 million AI strategy, integrating AI into healthcare and port logistics.
- Vietnam is positioning itself as a disruptor by aligning semiconductor investments with AI and producing 50,000 IT graduates annually.
- Indonesia and Malaysia focus on SME support and fintech, while rural areas remain underserved.
- Thailand and the Philippines apply AI to agriculture and BPO automation but face fragmented data challenges.
Southeast Asia’s diversity can drive AI innovation, but only if countries create a unified data-sharing framework that enables seamless cross-border collaboration. The region’s scale is undeniably an asset: over 650 million people, diverse consumer markets, and rising internet penetration. However, regulatory fragmentation often slows the cross-border data sharing and collaboration that AI thrives on.
The investment landscape
Investment in Southeast Asian AI ventures is gaining momentum, particularly in application-specific areas such as fintech, e-commerce, and logistics. AI-powered fraud detection, credit analytics, and demand forecasting are attracting significant investor interest, while AI-driven diagnostics are making inroads into healthcare.
Despite this progress, there are still critical investment shortfalls. The main gap is in deep-tech AI research, where the region lags behind global leaders. While countries such as the US and China devote billions to foundational AI breakthroughs — from advanced machine learning algorithms to next-generation robotics — Southeast Asia’s AI funding levels remain modest and are much lower per capita than, for example, in China.
Scaling up deep-tech R&D is essential for building truly innovative AI capabilities and reducing reliance on external solutions. By investing more aggressively in foundational research, Southeast Asia can cultivate robust homegrown AI firms that drive sustainable growth and resilience across the region.
Promoting AI: why public visibility matters
A robust deep-tech ecosystem — encompassing AI, robotics, biotechnology, and other frontier technologies — needs more than government policy and venture capital. It requires broad public awareness to fuel entrepreneurship, talent development, and market acceptance. When citizens, business leaders, and community stakeholders see practical deep-tech applications, such as AI-driven healthcare diagnostics or automated logistics solutions, regularly featured in the media, they are far more likely to embrace, and advocate for, technological advancements at a faster pace.
Governments across the region can help spur this awareness by elevating deep tech into a true “media project.” Sponsoring public demonstrations of cutting-edge technologies — ranging from AI-powered city services to next-generation manufacturing robotics — can showcase the tangible benefits for everyday life. Amplifying success stories not only builds trust and excitement, but also encourages talented individuals to seek opportunities in emerging fields. Showcasing examples of effective deep-tech entrepreneurship, including AI and other areas, fosters additional momentum for innovation and investment.
Taken together, these communication strategies serve as a powerful complement to policy frameworks and R&D incentives. By making emerging technologies more visible and comprehensible to the wider public, Southeast Asia can strengthen support for homegrown deep-tech start-ups, boost adoption in traditional industries, and ultimately accelerate the region’s innovation ecosystem.
Seizing the AI opportunity
Southeast Asia is actively embracing AI-driven solutions in digital finance, e-commerce, and mobile tech, signalling a growing demand for innovation. Local entrepreneurs, who understand the region’s cultural and linguistic diversity, are uniquely positioned to innovate in ways that might elude global tech giants.
Yet genuine progress hinges on decisive, coordinated action. Refining data governance, scaling deep-tech R&D, and nurturing a robust AI talent pipeline are critical next steps. Treating these priorities with urgency can help Southeast Asia progress from technology adopter to technology creator. By combining targeted innovation, regulation, and investment, and by ensuring AI stays in the public eye, Southeast Asia can move beyond simply importing breakthroughs to actively shaping an AI future on its own terms.
