Wayne Lau,
Vice President, Multi-Asset Strategy
The AI trade has bounced back in recent weeks as investors refocus on the significant infrastructure investments required to support more complex AI workloads.
After losing momentum amid rising geopolitical risks and earlier concerns that tech companies were overspending on AI, the tech‑heavy Nasdaq has since rebounded, climbing almost 16 percent in April. The speed of the rally has left many investors wondering if they have missed the boat, and whether further upside remains.
While such concerns are understandable, we continue to view AI as a durable investment theme and a key driver of market leadership this year. Near-term consolidation is possible after the sharp run-up in share prices, while the ongoing conflict in the Middle East remains a source of volatility.
That said, recent market behaviour suggests investors are increasingly willing to look past near-term uncertainty. Even as broader markets softened following renewed fighting in the Strait of Hormuz on Monday, the Nasdaq proved more resilient, underscoring investor conviction in the AI opportunity. Over a longer-term horizon, we see several structural forces continuing to underpin the AI ecosystem.
1. Agentic AI is reshaping compute demand
Recent advances have expanded AI’s ability to reason, plan and execute tasks with greater reliability, pushing performance closer to — and in some cases beyond — human benchmarks. This has accelerated the shift from generative AI to agentic AI, where software agents can autonomously complete sequences of tasks rather than simply respond to individual prompts.
As these AI agents become more capable, usage intensity is rising sharply. Data shows that weekly AI model activity has increased by more than 90 percent since the start of 2026, driven in part by the growing adoption of agentic solutions.
This has important implications for the underlying technology stack. As agentic AI scales, demand is rising across a broad set of compute and infrastructure inputs, notably central processing units (CPUs). Unlike generative AI workloads that rely heavily on graphics processing units (GPUs) for model training and inference, agentic AI places greater emphasis on sequential task execution, orchestration and control, areas where CPUs are particularly well suited.
As a result, analysts now estimate that agentic AI could translate into a US$32.5 to US$60 billion CPU opportunity by 2030 as workloads become more complex. At the same time, other critical inputs remain in strong demand, including semiconductors, memory, advanced substrates and related components needed to support increasingly intensive AI workloads.
2. AI capex is on track to surpass lofty expectations set at the start of 2026
Based on their recent Q1 earnings updates, hyperscalers such as Amazon, Microsoft, Meta and Alphabet are collectively on track to spend over US$650 billion in capital expenditure (capex) in 2026, with management teams describing this investment as necessary to meet robust and rising demand for AI workloads. The sheer scale of capital commitment from some of the world’s largest tech companies underscores how AI is evolving into a durable, multi-year industrial transformation.
With surveys indicating that 74 percent of companies expect to adopt agentic AI systems within the next two years , AI‑related capex is likely to continue increasing at a significant pace. Reflecting this, some estimates now point to AI capex soaring towards US$1 trillion in 2027, following the expanded spending plans unveiled during the latest earnings season.
While the scale of AI capex may appear aggressive, it is increasingly justified by solid fundamentals. Recent commentary from major hyperscalers point to improving monetisation from AI investments, reflected in rising cloud revenues and stronger platform performance. Supported by strong cash generation, robust balance sheets and long‑term customer commitments, mega-cap hyperscalers are well positioned to sustain this level of spending. In this context, we believe the risk of falling behind in AI capabilities is likely to outweigh the risk of over‑investing.
3. AI cycle remains in its infrastructure build-out phase
The physical requirements needed to support growing AI usage are becoming increasingly evident as well. Beyond compute hardware alone, rising AI workloads are placing growing strain on data centre capacity, power supply and grid infrastructure, reinforcing the need for sustained investment across the AI ecosystem.
In this context, the AI build-out is creating long-term opportunities across the physical backbone of the AI economy. Demand is rising not only for data centre construction, but also for the metals, materials, power systems and cooling technologies needed to operate increasingly energy-intensive computing environments.
Market returns driven by AI-led earnings growth and not multiple expansion
Rising AI investment and infrastructure build-out are increasingly driving earnings growth. As AI adoption deepens across enterprise and consumer applications, AI-related investment spending is estimated to contribute around 40 percent of S&P 500 earnings growth this year. Consistent with this, earnings growth from AI‑related companies has continued to outpace that of non‑AI names within the index.
Furthermore, recent market performance suggests that AI‑driven earnings growth — rather than rising valuations — has been the main driver of returns so far. Gains in AI‑linked stocks have broadly tracked improving earnings expectations, while valuation levels have remained relatively stable.
Positioning suggests further upside potential
Despite the strong rebound in AI‑related stocks, investor positioning suggests that the theme is not yet overcrowded. Measures of US tech exposure relative to the broader market indicate that allocations remain below previous peaks, pointing to room for further investor participation as confidence in the AI cycle builds. At this point in the year, as tax season draws to a close, we typically see larger inflows from retail investors, who tend to allocate more to growth‑oriented stocks.
Sentiment indicators across the semiconductor space tell a similar story. Measures tracking retail and options‑based sentiment remain below euphoric levels, even after the recent run-up in semiconductor stocks.
Taken together, current positioning suggests that the renewed AI rally still has legs. With structural drivers firmly in place and earnings momentum building, the backdrop remains supportive as investor participation continues to broaden.
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