APAC sovereign investors move from caution to action on AI

To the point 

• APAC sovereign investors have shifted from cautious observation to optimistic conviction regarding AI.
• Across the Asia Pacific region, sovereign funds and large institutional managers are expanding their exposure to AI related assets such as cloud infrastructure, data centers, and semiconductors, while increasingly integrating AI tools across front-to-back investment and operational processes.
• Global investors should take note of APAC’s growing focus on sovereign AI, governance, and strategic positioning to capture long-term value from AI.

The evolution of Asia PacificAsia Pacific countries (APAC) sovereign investors from watchful curiosity to active conviction on AI reflects a pragmatic regional mindset, viewing the technology as an enabler to enhance portfolio resilience, operational efficiency, and investment insights. While Gulf investors have prioritized external investments to build global competitiveness, APAC investors are balancing capital deployment with developing in-country capabilities and effective governance. 

At the organization level, focus is also shifting. Whereas Gulf funds increasingly involve chief technology officers (CTOs) in strategic decision-making, some APAC funds are introducing chief AI officer roles, tasked with driving AI strategy and transformation.

Australia: Infrastructure and internal adoption

Australia’s Future Fund has embraced AI-related infrastructure while simultaneously piloting AI tools internally. Its portfolio includes a stake in CDC Data Centers¹, supporting the view that AI will drive sustained demand for compute, storage, and energy. Internally, the Fund launched LUMi², a proprietary digital collaboration and AI tool designed to enhance information access and decision-making. 

Policy evolution in Australia also plays an important role. The National Framework for the Assurance of Artificial Intelligence in Government provides a structured approach to the safe and responsible use of AI³ by the federal, state and territory governments. Together, these initiatives reflect a strategy that combines sovereign discipline, infrastructure foresight, and ethical guardrails for AI adoption.

Southeast Asia: Balanced ambition and operational focus

In Southeast Asia, sovereign wealth funds are taking a balanced approach, adopting AI internally while investing selectively in enabling infrastructure and strategic collaboration.

Some SWFs have piloted AI tools for deal screening, document summarization, and research, gradually expanding AI usage across both investment and operational teams while others are supporting portfolio companies in applying AI meaningfully, providing access to subject matter specialists and tools to integrate AI into core business processes⁴. 

Southeast Asian funds have also been disciplined on valuation⁵, favoring infrastructure-linked investments over highly priced speculative bets⁶. This measured approach, balancing internal adoption with targeted external exposure, reflects the region’s broader policy stance—a dedication to responsible innovation underpinned by strong governance and ecosystem development.

China: Scale, sovereignty, and speed

China’s AI investment trajectory operates on an entirely different scale. China state-led funding, estimated at approximately US$98 billion, is driving rapid expansion across compute, semiconductors, and large model capabilities⁷. The China State Council has established 15 national AI teams, linking government research, private sector innovation, and large-scale infrastructure development across the AI value chain⁸.

While Gulf funds leverage their financial power to invest abroad in AI platforms, China’s approach focuses on building sovereign capability and self-reliance. This contrast highlights the diversity of AI strategies across APAC: some prioritizing resilience and autonomy, while others emphasize collaboration and integration.⁹

Regional momentum

Beyond Australia, Singapore, and China, other APAC markets are also accelerating AI adoption.  Japan’s Government Pension Investment Fund (GPIF) is exploring AI applications in investment manager selection and monitoring through strategic relationships¹⁰, while Korea Investment Corporation (KIC) is investing in AI and technology companies in public markets, while also exploring opportunities throughout the AI value chain, including data centers, energy infrastructure, core technologies, and applications¹¹.

According to International Data Corporation (IDC), AI and GenAI investments in APAC are expected to reach US$175 billion by 2028, growing at a CAGR of 33.6% from 2023 to 2028¹². This exceptional growth highlights APAC’s rising adoption of AI and its increasing influence on shaping the future of technology.

Perspectives and lessons for global investors

Sovereign investors who integrate AI thoughtfully across both operations and investment allocations may be positioning themselves for durable competitive advantages. In the APAC region, this means deploying capital into cloud infrastructure, data centers and semiconductors, while embedding AI tools into investment and operations workflows, and guarding the process with strong governance frameworks.

Johor in Malaysia’s southern corridor is an example of the AI growth in APAC; over 40 data-center projects worth ~US$40 billion approved by mid-2025¹³ reflect how infrastructure is being used as the foundation for AI-driven growth. These projects are not just real estate plays, rather they are core enablers of compute, connectivity, and capacity that sovereign investors recognize as important for future digital economies.The increased adoption can be attributed to Generative AI breakthroughs raising compute demand, rising cloud-scale use cases, and strategic shifts prompted by data-sovereignty and supply-chain concerns. AI is no longer just a technology wager, but a lever for operational resilience, insight-driven decision-making and economic competitiveness.

For global investors, the APAC experience offers three lessons:

1. Governance matters: AI adoption should not outpace control. A focus on ethical frameworks and accountability gives scaling legitimacy.
2. Infrastructure first: Access to compute, data-center capacity and power supply is as critical as algorithmic innovation.
3. Capability integration: Embedding AI in operations, from research to risk-monitoring, shifts the value-creation from access to deployment.

In short, sovereign investors that both invest in AI ecosystems and deploy AI within their organizations may be better placed to convert today’s technology transition into enduring advantage.