Executive Summary
1. What key metrics are you monitoring to assess whether the AI-related investment cycle still has room to run?
We monitor two key indicators: hyperscaler capital expenditure and global data-centre construction. Some forecasts suggest aggregate cloud-equipment spending by the world’s largest cloud providers is expected to grow by 104% year-on-year in 2026 and a further 38% year-on-year in 2027 (up 9 percentage points in a span of a month), reaching approximately US$1.61 trillion in 20271. This suggests that further upward revisions may still be ahead.
Concurrently, the number of tracked AI data centre projects has risen from around 240 to 2802 in recent months. The pipeline of large projects expected over the next two to three years should therefore continue to provide strong and visible demand for the AI hardware supply chain.
NVIDIA's latest earnings and FY28 outlook reinforce our positive view on the AI infrastructure cycle. The company’s management expects roughly 70% revenue growth in FY28, ahead of market expectations, while indicating demand remains stronger than supply. Additionally, NVIDIA highlighted that Sovereign AI projects, NeoCloud providers, AI startups, and enterprise customers now account for roughly half of its business and are growing at around 100%. This diversification should make AI capex more durable and less dependent on a handful of large cloud providers.
All these indicators suggest that the AI investment cycle is moving beyond the initial infrastructure build-out phase and remains supported by visible multi-year demand from hyperscalers, sovereign AI initiatives and enterprise AI adoption.
2. What macro factors could challenge the AI investment thesis, and how are you positioning the portfolio to navigate these risks?
Key risks include data centre build constraints and funding costs. Permits, power, grid access, water availability and community concerns can delay projects, while interest rates affect financing and construction costs.
We focus on whether these challenges are temporary delays or a threat to the long-term AI thesis. If the long-term thesis remains intact, we will maintain exposure while adjusting position sizes and the portfolio mix to reflect changes in risk and valuation. We also diversify across various parts of the AI value chain rather than rely on a single project, customer or funding channel.
3. Beyond macro risks, how do you assess policy or regulatory risk for Asia technology investors?
Policy and regulatory risks are significant and generally fall into two categories. The first is local regulatory risk, including restrictions or delays related to electricity availability, environmental impact, water usage, and community concerns.
The second is geopolitical risk, particularly between the US and China. Examples include restrictions on exports of high-end NVIDIA and AMD products to China, as well as potential US restrictions on imports of certain Chinese optical receivers.
We assess whether an event is a temporary setback or a lasting change to a company’s competitive position, then adjust exposure, diversify risk or add selectively where appropriate.
4. Technology stocks experienced notable volatility in July. Should investors expect volatility in the AI trade to remain elevated, and what factors are likely to drive it?
Volatility is likely to remain elevated because expectations and positioning in AI-related stocks are high, while investors are closely scrutinizing the sustainability of capital expenditure, funding structures, power availability, supply constraints, and the pace of earnings delivery. Following the strong rally in the second quarter of 2026, profit-taking and valuation compression may also amplify short-term market moves even when underlying fundamentals remain intact.
We do not believe the recent pullback reflects a deterioration in long-term fundamentals. Demand across the AI value chain remains supported by rising inference workloads, continued investment in computing infrastructure and an ongoing semiconductor capex cycle. We remain constructive on semiconductor, equipment, and memory companies, where demand continues to outpace supply in several areas, particularly memory. Overall, we view the sell-off as a normal consolidation within a long-term structural growth trend, with the core drivers of AI adoption and digital transformation remaining firmly in place.
5. Which assumption within the AI investment thesis do you believe is most vulnerable to hype or over-extrapolation today?
The most vulnerable assumption is that every part of the AI ecosystem can sustain the same pace of growth and valuation expansion. Investor concerns have recently focused on the durability of AI infrastructure spending and potential overcapacity in selected areas. While we do not see a material deterioration in the sector’s long-term structural outlook, we believe investors should avoid extrapolating short-term growth indefinitely.
Over the past four years, individual technology sub-industries have often outperformed sharply as expectations for innovation or product-specification changes accelerated, before consolidating as those expectations were absorbed. We therefore remain positive on the broader AI theme, while maintaining discipline around valuation, earnings visibility and company-specific execution.
6. Which segment of the Asia technology value chain do you think remains underappreciated by investors, and why?
Software, IT services and digital platforms have lagged semiconductors and hardware, but as AI adoption matures, they should benefit from productivity gains, enhanced products and AI-enabled services. We believe this application layer could be the next beneficiary as investor focus shifts from infrastructure spending to AI monetisation.
Robotics and autonomous driving also remain underappreciated. These areas are still at an earlier stage of earnings contribution and investor recognition, but they have the potential to be re-rated as commercial adoption and profitability become more visible. Asia is particularly well positioned because of its strengths in manufacturing, components and supply chain integration.
7. As AI infrastructure investment relies increasingly on debt, equity, private credit and off-balance sheet structures, do funding conditions pose a bigger risk for the AI investment thesis?
Funding conditions and balance-sheet discipline are becoming more important. While accelerated AI investment may pressure near-term free cash flow for some cloud service providers, AI remains one of their fastest growing and most strategically important businesses, and it can also support broader demand for cloud services.
Major cloud providers retain the financial capacity to expand AI infrastructure, and we do not see current funding conditions as a sign that the AI capex cycle is nearing an inflection point. Instead, we focus on distinguishing well-capitalised operators with visible demand from projects reliant on aggressive leverage or less transparent financing structures.
8. What lessons or insights can investors draw from Asia's recent earnings results?
Asia’s second-quarter 2026 earnings results were strong, and consensus expectations for both 2026 and 2027 earnings have continued to move higher. According to the latest Bloomberg consensus estimates, Asia technology earnings are expected to significantly outpace global peers, with EPS growth forecast at 212% in 2026 and 42% in 2027. We therefore view the recent market pullback as an opportunity for investors to build exposure gradually.
Fig 1: Earning expectations
Source: Bloomberg, Aug 2026
Interesting reads
Sources:
1Morgan Stanley, August 2026
2Nomura report on Asia AI Semi & Server, 30 June 2026
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