Six Key Issues in the Early Stage of the Major AI Cycle

Six Key Issues in the Early Stage of the Major AI Cycle

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With the onset of the AI supercycle, the global technology industry is at the early stage of a structural transformation. Although there is still debate in the market regarding the pace of capital expenditure and returns, the potential productivity boost offered by AI has already established its long-term growth as a central theme. 2026 will be a key window to observe constraints in AI infrastructure, evolution in the chip competitive landscape, and integration of terminal applications.

According to Chasewind Trading Desk, the HSBC analyst team led by Nicolas Cote-Colisson published a report on the 7th, stating that AI is currently in the initial stage of its supercycle. Although there was a period in October 2025 when capital expenditure expectations outpaced initial revenue, given the speed of AI development and its potential impact on over $110 trillion of global GDP, confidence in the outlook for 2026 remains high. The analysts believe that the focus of risks, opportunities, and narrative will revolve around six core dimensions.

On a macro level, HSBC holds an optimistic outlook for US stocks in 2026, setting the S&P 500 target price at 7,500 points. Analysts recommend that investors broaden AI-related trades beyond infrastructure suppliers to also include users and enablers.

Cloud Capacity Constraints and Rising Capital Expenditures

Order backlogs are severe among the world’s three major cloud giants (Amazon, Microsoft, Alphabet), but capacity expansion is limited by data center construction cycles. HSBC expects the tight capacity situation to persist until 2026.

Against this backdrop, tech giants remain keen to invest. Alphabet, Meta, and Amazon have all signaled that capital expenditure will see “significant/major” growth in 2026. HSBC predicts aggregate capital expenditure growth for related companies will reach 44% in 2026. Except for Oracle and CoreWeave, most giants are expected to use free cash flow for financing. HSBC believes the current pace of expenditure is more constrained by “construction capability” than “willingness to invest,” and there is upside risk in the 2026 spending guidance.

Electricity Supply as Core Bottleneck for AI Development

The biggest obstacle to capacity expansion is not funding but electricity. According to HSBC analysis, the delivery cycle for heavy-duty gas turbines has now extended to more than four years, while small modular nuclear reactors (SMR) are unlikely to contribute capacity before 2035. This means the electricity gap for data centers will persist in the short-term.

By contrast, the Chinese market shows different characteristics. Domestic Chinese brands, with shorter delivery cycles, are rapidly penetrating the large engine market. In addition, liquid cooling technology will become a hot topic in 2026; as chip power increases, liquid cooling will shift from optional to mandatory.

Significant Growth in Capital Expenditure

Alphabet, Meta, and Amazon have all signaled “significant/meaningful” growth in capital expenditure in 2026, and HSBC expects most major technology companies to do the same when releasing 2026 guidance (end of January/early February). HSBC forecasts total annual capital expenditure will increase by 44%. Overall, most of the funds are expected to come from current free cash flow, except for Oracle and CoreWeave, which will require additional financing.

Given the aforementioned capacity restraints and strong demand, the report predicts capital expenditure will opportunistically exceed initial guidance. Therefore, there is upside risk in the 2026 forecasts.

ASIC Chip Rise Challenges GPU Dominance

In the AI chip sector, Nvidia’s GPUs remain the preferred choice for cloud service providers, but competition from ASIC chips is intensifying. Alphabet’s Ironwood TPU and Amazon’s Trainium3 are notable examples. With better performance-cost ratios and cost advantages, ASICs are attracting increasing in-house development from hyperscale enterprises.

HSBC expects ASIC’s share of cloud service providers’ capital expenditures to rise from 2% in 2023 to 13% by 2027. While external chip sales may not contribute substantially to financial statements until 2027, the 2026 discussions about orders and technology agreements will influence valuations. Nvidia’s recent licensing agreement with Groq is seen as a positive move to address the trend of declining inference costs.

Competition among frontier AI foundation models is entering a shakeout phase. HSBC believes the high sunk costs will rationalize the market, ultimately leading to an oligopolistic structure dominated by a few giants, with co-existing smaller specialists. Currently, open-source/open-weight models are rapidly catching up with closed-source models, with the gap now shortened to about three months.

Gemini’s smart growth rate has exceeded ChatGPT. The focus for 2026 will be premium model monetization and commercialization of AI advertising. HSBC predicts that AI chat advertising will account for 2% of digital ad spending by 2030.

AI Integration & Form Factor Innovation in End Hardware

2026 is viewed as the pivotal year for integrating AI into smartphones, and also marks the inaugural year for new hardware to challenge traditional platforms. Apple is expected to greatly enhance AI capabilities in its hardware in 2026-2027, including an upgraded Siri and possibly a foldable or 20th anniversary edition iPhone.

Smart glasses are seen as important carriers for unleashing the power of large AI models. Meta’s partnership with EssilorLuxottica currently leads the market, while Samsung, Google, Apple and Amazon all have related product plans for release in 2026-2027. These devices are expected to partially replace smartphone functions through voice dialogue and contextual information capture.

 

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