While all eyes are on the US AI narrative dominated by Nvidia, Microsoft, and Google, Asia has quietly been moving on AI and is home to some of the world’s most aggressive AI bets.

‍

Quick facts

• SoftBank has committed $41 billion to OpenAI, securing approximately an 11% ownership stake.
• Alibaba plans to invest more than $50 billion in AI infrastructure over the coming years.
• Baidu's Core AI-powered business revenue grew 48% year over year in Q4, with ~70% of search results now AI-generated.

‍

1. SoftBank Group (TYO: 9984)

SoftBank is the most AI-committed company in Asia by capital deployed and ambition. CEO Masayoshi Son has declared the company in "total offence mode," having completed a $41 billion investment into OpenAI for approximately an 11% ownership stake. 

Son has also launched a $100 billion initiative aimed at building a vertically integrated AI semiconductor champion (Project Izanagi), repositioning SoftBank as an "AI-era industrial holding company." 

SoftBank's fortunes are now deeply tied to the success of OpenAI and Son's ability to execute his semiconductor plan that puts it in direct competition with established players.

What to monitor

• OpenAI's trajectory: Any shift in OpenAI's competitive position, valuation, or path to profitability has direct implications for SoftBank's balance sheet.
• Project Izanagi progress: Watch for partner announcements, funding milestones, and whether Son can attract the engineering and manufacturing talent needed.
• Arm Holdings performance: SoftBank also has a listed stake in Arm. Arm's data centre and AI chip licensing momentum is worth tracking.
• Debt levels and Vision Fund exposure: SoftBank carries significant leverage. Rising interest rates or a correction in AI valuations could pressure the group's net asset value.

‍

2. Alibaba Group (BABA)

Alibaba has committed more than US$50 billion to AI infrastructure, making it one of the largest AI capex programmes in the world. 

Its Qwen family of large language models underpins a rebuilt AI-focused cloud platform, and the company has partnered with Nvidia on physical AI projects. 

Alibaba Cloud is also the leading cloud provider in China. The key commercial question is whether Alibaba's can convert this cloud leadership into durable revenue growth.

However, it will have to navigate ongoing regulatory scrutiny in China and competition from local rivals like Huawei and ByteDance.

What to monitor

• Cloud AI revenue growth: The clearest signal of whether the $50 billion investment is translating into commercial traction.
• Qwen model adoption: Enterprise and developer uptake of the Qwen model family could be an indicator of Alibaba's AI platform stickiness.
• Regulatory environment: Beijing's approach to large tech platforms and any renewed regulatory action could disrupt execution and sentiment.
• US-China tech tensions: Nvidia partnership activity and access to advanced AI chips could be affected by further export controls.

‍

3. Baidu (BIDU)

Baidu has made the most visible AI transformation of any company on this list. It has released a 2.4 trillion parameter omni-modal model (ERNIE 5.0) with approximately 70% of its search results now delivered as AI-generated rich media. 

Beyond search, its Apollo Go robotaxi service is now partnering with Uber to expand into Dubai and the UK.

Its Core AI-powered business generated RMB 11.3 billion in Q4 revenue, up 48% YoY. The question now is whether that momentum is sustainable and whether the robotaxi business can scale economically.

What to monitor

• ERNIE monetisation: Watch for updates on enterprise API revenue and advertising yield improvements driven by AI-generated search.
• Apollo Go expansion: Rider volume growth and cost per ride will indicate whether unit economics are improving.
• Search market share: Competition from ByteDance and emerging AI-native search alternatives in China is a potential structural risk.

‍

4. Tencent Holdings (HK: 0700)

Tencent's AI play is to allocate its GPU capacity to itself. This allows it to convert AI directly into efficiency gains across its ecosystem. 

With WeChat's 1.4 billion users providing an unmatched data engine, Tencent is embedding AI across gaming, payments, cloud, and search in a way that is difficult to replicate. 

This approach also offers greater resilience against AI chip export restrictions, since the compute stays internal.

The AI upside here is arguably underappreciated because it is embedded rather than a separate segment, which could also mean the market may find it harder to isolate and value that contribution.

What to monitor

• Advertising revenue trends: The most measurable near-term AI benefit is from ad targeting improvements translating into sustained advertising revenue growth.
• WeChat ecosystem AI integration: Watch for new AI-native features within WeChat, including search, mini-programs, and payments, as signals of platform deepening.
• Regulatory and geopolitical risk: Tencent operates under ongoing scrutiny from Chinese regulators and faces restrictions in some Western markets.

‍

5. Kakao (KRX: 035720)

Kakao is South Korea's dominant AI and internet platform, operating KakaoTalk, which is used by approximately 95% of South Koreans.

It is one of the most aggressively AI-focused non-Chinese tech companies in Asia, investing heavily in LLM development and AI-native services. 

The domestic dominance of KakaoTalk provides a captive distribution platform for AI products in a way few companies outside China can match. The key question is whether Kakao can monetise that distribution advantage before global competitors close the gap.

What to monitor

• KakaoAI product rollouts: New AI-native features within KakaoTalk and Kakao's broader service suite are the most direct signal of commercial AI progress.
• Cloud division growth: Kakao's cloud business is the infrastructure layer for its AI ambitions. Revenue growth and enterprise customer additions are key metrics.
• LLM competitive positioning: Monitor how Kakao's models benchmark against global and regional peers, and whether Korean enterprise customers are adopting them at scale.
• Corporate governance: Kakao has faced governance-related scrutiny in recent years; any developments here could affect sentiment independently of AI progress.

‍

Bottom line

Asia's AI landscape is far more complicated than a simple "follow the AI spend" narrative suggests. 

China's top companies are innovating rapidly but operate under regulatory and geopolitical constraints. Japan's SoftBank is making the biggest single bet, but at a level of concentration risk that demands scrutiny. And South Korea's Kakao offers a differentiated, lower-geopolitical-risk angle.

The AI push in Asia is real. But the range of outcomes across these five names is wide, making it pivotal to understand each company's specific exposure and risk profile, not just its AI narrative.

The war in Iran is increasingly shifting from a regional conflict into a global energy shock, as disruption in the Strait of Hormuz threatens the oil market at its most critical chokepoint.

Key takeaways

• Around 20 million barrels per day (bpd) of oil and petroleum products normally pass through the Strait of Hormuz between Iran and Oman, equal to about one-fifth of global oil consumption and roughly 30% of global seaborne oil trade.

• This is a flow shock, not an inventory problem. Oil markets depend on continuous throughput, not static storage.

• If the disruption persists beyond a few weeks, Brent could shift from a short-term spike to a broader price shock, with stagflation risk.

The world’s most critical oil chokepoint

The Strait of Hormuz handles roughly 20 million barrels per day of oil and petroleum products, equal to about 20% of global oil consumption and around 30% of global seaborne oil trade. With global oil demand near 104 million bpd and spare capacity limited, the market was already tightly balanced before the latest escalation.

The strait is also a critical corridor for liquefied natural gas. Around 290 million cubic metres of LNG transited the route each day on average in 2024, representing roughly 20% of global LNG trade, with Asian markets the main destination.

The International Energy Agency (IEA) has described Hormuz as the world’s most important oil transit chokepoint, noting that even partial interruptions may trigger outsized price moves. Brent crude has moved above US$100 a barrel, reflecting both physical tightness and a rising geopolitical risk premium.

Tankers idle as flows slow

Shipping and insurance data now point to strain in real time. More than 85 large crude carriers are reported to be stranded in the Persian Gulf, while more than 150 vessels have been anchored, diverted or delayed as operators reassess safety and insurance cover. That would leave an estimated 120 million to 150 million barrels of crude sitting idle at sea.

Those volumes represent only six to seven days of normal Hormuz throughput, or a little more than one day of global oil consumption.

A market built on flow, not storage

Oil markets function on continuous movement. Refineries, petrochemical plants and global supply chains are calibrated to steady deliveries along predictable sea lanes. When flows through a chokepoint that carries roughly one-fifth of global oil consumption and around 30% of global seaborne oil trade are interrupted, the system can move from equilibrium to deficit within days.

Spare production capacity, largely concentrated within OPEC, is estimated at only 3 million to 5 million bpd. That falls well short of the volumes at risk if Hormuz flows are severely disrupted.

Oil market analysis

How long do idle tankers last?

135M idle barrels — days of cover against each demand benchmark

vs. Strait of Hormuz daily flow  (20M bbl/day)

6.75 days of Hormuz throughput covered

6.75 days

0

5

10

15

20

25

30 days

vs. Global oil consumption  (104M bbl/day)

1.3 days of world demand covered

1.3 days

0

5

10

15

20

25

30 days

vs. US Strategic Petroleum Reserve release  (1M bbl/day)

135 days of full SPR release pace covered

135 days — but SPR exists to replace this role

0

5

10

15

20

25

30 days

---

135M

idle barrels on tankers (midpoint of 120–150M range)

~33%

of daily Hormuz flow that is idle storage, not transit

<31 hrs

is all idle storage against global daily consumption

Sources: IEA, EIA, industry estimates. Idle crude midpoint of 120–150M bbl range used.

GO Markets

Scenarios for the weeks ahead

Market trajectories now hinge on the duration and severity of the disruption.

Short disruption, 1 to 2 weeks

If tanker traffic resumes within 1 to 2 weeks, the shock may show up as a sharp but ultimately reversible spike.

Cumulative supply loss would remain relatively limited, while inventories and strategic stocks may partly bridge the shortfall. In that scenario, Brent could trade in roughly the US$95 to US$110 range as traders price temporary disruption and elevated risk premia.

Extended disruption, 2 to 4 weeks

Beyond a fortnight, the cumulative loss becomes more material.

A 2 to 4 week disruption affecting up to 20 million bpd could imply roughly 280 million to 560 million barrels of lost supply. Commercial inventories, floating storage and strategic reserves may then begin to erode more visibly. In that scenario, Brent could shift toward the US$110 to US$130 range, while higher fuel costs may begin feeding into transport and industrial production.

These price ranges are scenario-based and indicative, not forecasts.

If the war ends within four weeks

A ceasefire or credible de-escalation within roughly four weeks would likely trigger a sharp reversal in oil markets, though not an instant reset to pre-crisis levels.

Initially, the unwinding of geopolitical risk premia and the normalisation of tanker traffic could push Brent lower, potentially into the US$80 to US$95 range as speculative and hedging positions are reduced.

Assuming flows are fully restored and further disruptions are avoided, prices could gradually trend back toward the low US$70s over subsequent months, broadly consistent with projections that show inventories rebuilding once supply regains a small surplus over demand.

Watching the oil shock play out on the ASX?
‍See 5 Australian energy stocks traders are tracking after the Iran oil shock.

Inflation risks and macro spillovers

The inflationary impact of an oil shock typically arrives in waves. Higher fuel and energy prices may lift headline inflation quickly as petrol, diesel and power costs move higher.

Over time, higher energy costs may pass through freight, food, manufacturing and services. If the disruption persists, the combination of elevated inflation and slower growth could raise the risk of a stagflationary environment and leave central banks facing a difficult trade-off.

Higher crude rarely moves in isolation.
‍See which global energy and oil-services names tend to come into focus when oil prices rise.

No easy offset, a system with little slack

What makes the current episode particularly acute is the lack of slack in the global system.

Global supply and demand near 103 million to 104 million bpd leave little spare cushion when a chokepoint handling nearly 20 million bpd, or about one-fifth of global oil consumption, is compromised. Estimated spare capacity of 3 million to 5 million bpd, mostly within OPEC, would cover only a fraction of the volumes at risk.

Alternative routes, including pipelines that bypass Hormuz and rerouted shipping, can only partly offset lost flows, and usually at higher cost and with longer lead times.

Bottom line

Until transit through the Strait of Hormuz is restored and seen as credibly secure, global oil flows are likely to remain impaired and risk premia elevated. For investors, policymakers and corporate decision-makers, the core question is whether oil can move where it needs to go, every day, without interruption.

Ready to trade beyond the majors?
‍Open an account · Log in

‍

^{Any scenarios, price ranges or market views in this article are illustrative only and should not be relied on as forecasts, guarantees or trading recommendations. Geopolitical events can cause sudden volatility, reduced liquidity and sharp price movements across oil, forex and CFD markets, and trading in these conditions carries a high risk of loss.}

After three consecutive years in which mega-cap AI-linked names carried the Nasdaq, the mix of winners may be starting to change.

2026 is the "show me the money" year. Any hint of doubt about whether tech companies were correct to spend nearly US$700 billion on AI last year could have a major impact on market sentiment.

‍

Quick facts

• Global AI capex is projected to exceed US$600 billion in 2026.
• The total addressable market (TAM) for AI data centre systems is estimated to exceed US$1.2 trillion by 2030.
• Nvidia, Microsoft and TSMC are all trading below analyst fair value estimates, despite surging revenues.
• Broadcom's AI chip division is targeting US$100 billion in AI revenue by 2027.

‍

What is powering the AI trade?

Multiple macro forces are likely to underpin the AI investment theme through 2026. The direction of US interest rates, the scale of AI infrastructure spending and the geopolitical backdrop are all likely to matter.

Rates and valuations

The Federal Reserve delivered 75 basis points (bps) of rate cuts in 2025, and markets expect another 50 bps in 2026. Lower rates can reduce the discount applied to future tech earnings and typically support growth stocks, including AI-linked names.

Infrastructure spending and earnings expectations

On the spending side, Nvidia CEO Jensen Huang has said data centre operators could spend up to US$4 trillion annually by 2030, and AI capital spending is projected to reach US$571 billion in 2026 alone.

However, markets appear to have already priced in much of this optimism. Analysts are projecting 14% to 16% annual earnings per share (EPS) growth in 2026. That would require S&P 500 stocks outside the Magnificent 7 to roughly double the pace of earnings growth recorded in 2025.

Geopolitics and export controls

Geopolitics could also shape the outlook. US-China export controls on AI chips, along with reduced access to key international buyers, could weigh on data centre growth projections.

‍

Trade the US earnings season

‍

Top AI-linked stocks

Nvidia (NVDA) 

Nvidia remains the clearest expression of the AI trade. It holds a wide economic moat thanks to its market leadership in GPUs, hardware, software, and networking tools. 

Goldman Sachs and Morgan Stanley both carry price targets near $250 on NVDA, with Goldman's call based on a 2027 revenue forecast of over $380 billion. Bank of America sits in the $275 camp, effectively pricing in more AI upside on 2027 earnings.

At 21.6 times forward earnings, Nvidia is now trading below the broader S&P 500's multiple. Key risks include the overhang from US–China export restrictions and any softening in data centre capex guidance from major cloud providers.

Microsoft (MSFT)

Microsoft is down around 25% from its all-time high. During the second quarter of fiscal year 2026, Azure's revenue increased 39% year over year, and the company holds a US$625 billion backlog of contracted usage still to come. 

The gap between the stock's recent performance and its underlying revenue growth has drawn attention from analysts, though elevated valuations across the broader tech sector remain a risk to watch.

Broadcom (AVGO)

While Nvidia makes broad-purpose GPUs, Broadcom is winning business by going bespoke, designing custom AI chips tailored specifically to the needs of individual hyperscalers like Google and Meta.

During Q1 of FY2026, Broadcom's AI semiconductor division grew at a 106% pace to US$8.4 billion, and by the end of 2027 it expects its AI chip revenue to reach more than US$100 billion.

Broadcom trades at a significant premium to the broader market, which could amplify any downside if growth expectations are not met.

TSMC (TSM) 

Almost every major AI chip is manufactured by TSMC. The company holds approximately 70% market share in chip foundry, making it the single most critical piece of infrastructure in the entire AI supply chain. 

TSMC sales are projected to increase by 30% in 2026, with gross margins expected to remain above 60% as new fabrication capacity comes online.

The primary risk is geopolitical: any escalation in Taiwan Strait tensions could weigh heavily on the stock regardless of its underlying fundamentals.

Vertiv (VRT)

Less prominent than the semiconductor giants, Vertiv provides the power management, cooling, and data centre infrastructure that keeps AI hardware running. 

Nvidia, Broadcom, and Vertiv sit at different points in the AI build-out, including compute, custom silicon, networking and physical infrastructure.

Vertiv's revenue is tied to overall AI capex rather than any single chip maker, which gives it a different risk profile to the names above.

Corning (GLW)

Corning's stock rose 84% in 2025 thanks to surging demand from data centres for its fibre optic cables. Its optical communications segment has grown 69% YoY. 

At a Price-to-Earnings (P/E) ratio of roughly 37x, Corning trades at a discount to Nvidia and Broadcom while still carrying direct exposure to AI infrastructure spending. However, its valuation depends heavily on continued capex from the major hyperscalers.

‍

US market drivers for March 2026

‍

AI trades beyond the headline stocks

Energy and utilities

Training large-scale AI models is extraordinarily energy-intensive. A typical 1 gigawatt AI data centre facility requires upwards of US$60 billion in capital expenditure, with roughly half going directly to hardware. Utilities exposed to data centre power demand could also be affected by the AI build-out.

International spillover

South Korea's Kospi surged 76% in 2025 due to AI-linked chipmakers like SK Hynix. Japan's Topix, Germany's DAX, and the UK's FTSE 100 also saw gains of more than 20%. Memory supplier Kioxia was the world's best-performing stock, surging 540%.

Data centre infrastructure

Companies like Emcor, which provides critical electrical, HVAC, and power infrastructure to data centres, reported its contracted backlog surged 31.2% year over year to a record US$13.25 billion. These companies can offer different exposure to the AI capex cycle, but they carry their own execution, backlog, margin and valuation risks.

‍

What could derail the AI trade?

Valuation compression

Broadcom trades at about 50x earnings and AMD at 56x. Any disappointment in forward guidance could trigger a sharp contraction in multiples.

The return on investment test

Companies are investing today on the assumption that highly profitable business applications of AI will emerge over time. If the timing or scale of those returns disappoints, the AI trade could face pullbacks.

Index concentration

The 10 largest stocks in the S&P 500 account for about 40% of the index's total value. A rotation out of mega-cap tech could disproportionately affect broad indices.

Efficiency disruption

China's DeepSeek recently published research suggesting large language models may be developed more efficiently than previously assumed. If AI can be built with less compute, demand for GPUs and data centre hardware could fall short of current forecasts.

‍

Bottom line for traders

The AI trade is maturing but far from over. 2026 is shaping up to be a more nuanced chapter, spreading across the full AI value chain. 

The US earnings season will be closely watched for evidence that the hundreds of billions being poured into AI infrastructure are beginning to generate the anticipated returns.

‍

All data points referenced in this article were verified against primary sources on 18 March 2026.