The AI cycle continues to support global markets, but the narrow support base makes risk assets more fragile

Overview

This report discusses the macro tug-of-war between the 2026 AI investment cycle and energy shocks. UBS believes that tensions in the Middle East and energy supply risks have eased, but this has not changed the market's core drivers: AI capital spending, technology trade, corporate earnings, and equity wealth effects are still supporting global growth and risk-asset performance. The question has shifted from 'can the AI cycle continue?' to 'what will ultimately constrain the AI cycle?'

Core views

The core views are as follows: first, the AI investment cycle will continue to dominate markets in the second half of 2026, driving earnings, capital spending, and equity performance; second, macro hard data have not yet deteriorated materially, with weakness mainly showing up in soft data such as business and household confidence; third, global equity fundamentals remain strong, but gains are highly concentrated in a small number of technology companies, making the market more vulnerable to AI disappointment or valuation pullbacks; fourth, emerging-market performance is shifting away from traditional beta logic toward structural divergence driven by AI supply-chain exposure and energy exposure; fifth, the credit market may be where macro fragility shows up first, especially in leveraged loans and private credit.

Analysis framework

The report uses a cross-asset macro framework, comparing AI capital expenditure, technology trade, energy supply, inflation, interest rates, equity earnings, credit spreads, and regional asset performance within the same cycle, with a focus on whether AI can continue to offset energy and geopolitical shocks.

Methodology notes

• Macro shock absorption frameworkAI and energy shock hedging analysis

  Compare the positive shock from AI capital spending and technology trade with the negative shock from disrupted energy supply, higher oil prices, and rising logistics costs.

  The report argues that AI is not just a thematic trade but the core driver of current market behavior; the scale of technology trade and AI-related wealth effects allows it to offset part of the energy and geopolitical shocks in the short term.

• Economic data validation frameworkDivergence between hard data and soft data

  Distinguish the different signals from real activity data and survey-based confidence data.

  UBS notes that the deterioration since the start of the year has been concentrated mainly in soft data such as business and household confidence, while global macro hard data have not yet shown broad-based weakness.

• Cross-asset allocation frameworkMonitoring earnings concentration and credit pressure

  Use equity earnings concentration, valuations, credit spreads, and default risk to assess the resilience of risk assets.

  The report argues that equities remain supported but have already become crowded, and that credit markets, especially leveraged loans and private credit, may be the first to expose pressure from a slowdown in the AI cycle or rising financing costs.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Global equities

  Supported by AI capital spending, earnings resilience, and equity wealth effects.

  Strengths

  Fundamentals remain strong, and MSCI AC World still has 7% target upside.

  Weaknesses

  Valuations and positioning already reflect high confidence, and return sources are concentrated.

  Comparison

  The US and emerging markets outperform Europe and the UK.

  Risks

  Disappointment in AI expectations, persistently high interest rates, rising energy costs, or earnings downgrades could trigger a pullback.

• US technology and AI equities

  They are the core driver of the current market cycle.

  Strengths

  Contributed 81% of MSCI US year-to-date returns, and AI capex and valuation expansion form a positive feedback loop.

  Weaknesses

  Dominated by a small number of companies, with insufficient market breadth.

  Comparison

  Magnificent 7 earnings performance is significantly ahead of the other 493 companies in the S&P.

  Risks

  US tech or AI disappointment is one of the main downside risks listed in the report.

• Emerging markets and North Asian semiconductors

  AI supply-chain positioning is reshaping the relative performance of emerging markets.

  Strengths

  North Asian markets such as South Korea, Taiwan region, and China are deeply embedded in the AI supply chain and show strong earnings upgrades.

  Weaknesses

  Not all emerging markets benefit simultaneously, and energy-importing countries may face inflation and exchange-rate pressure.

  Comparison

  Emerging-market performance is increasingly driven by structural AI exposure rather than traditional beta.

  Risks

  Slower global demand, overly slow supply-chain expansion, or cooling AI capital spending.

• Credit, leveraged loans, and private credit

  These may be the asset classes where macro pressure appears earliest.

  Strengths

  Yields still provide some support for spreads.

  Weaknesses

  Concentration is high in technology and related sectors, and default rates in leveraged loans and private credit may rise.

  Comparison

  Compared with IG and HY, risks are more pronounced in leveraged loans and private credit.

  Risks

  Spread widening, rising default rates, hidden leverage, and overlapping investors causing stress spillover.

• US dollar and foreign exchange

  Supported by relative growth, interest rates, and AI leadership.

  Strengths

  The US dollar still has structural support and is broadly stable in the near term.

  Weaknesses

  There is a slight short-term downside bias.

  Comparison

  JPY may require further intervention to prevent continued weakening.

  Risks

  Convergence in growth differentials, a shift in rate expectations, or changes in market risk appetite.

• Commodities and energy

  Energy shocks are one of the main constraints on the AI cycle.

  Strengths

  Some commodity exporters may benefit from support to their terms of trade.

  Weaknesses

  The report does not expect a commodity supercycle over the next few years.

  Comparison

  Energy exporters have more cushioning than energy importers.

  Risks

  Prolonged disruption to global energy supply, renewed oil-price increases, and intensified logistics and supply-chain disruptions.

• Rates and central bank policy

  High interest rates affect financing costs and the sustainability of AI capital spending.

  Strengths

  The market's priced hawkish path may be more aggressive than reality.

  Weaknesses

  Inflation may still remain elevated, limiting room for rate cuts.

  Comparison

  Market expectations for most major central banks are more hawkish than UBS believes may ultimately materialize.

  Risks

  Oil prices pushing up inflation, tough central bank communication turning into actual tightening, and financing costs suppressing AI investment.

Key data

• US AI capital expenditureAbout USD 850 billion annualizedThe report states that US AI capex is close to an annualized USD 850 billion.
• Valuation amplification effect of AI capital expenditureEach additional USD 1 of AI capital expenditure corresponds to about USD 20 of added tech equity valuationEquivalent to additional household equity wealth of about 24% of GDP.
• Technology trade and energy tradeTechnology-related trade accounts for nearly 4% of global GDP, while energy trade accounts for about 2%The scale of technology trade is close to twice that of energy trade.
• Weight of AI supply-chain economiesMore than 50% of global GDPThe report states that economies related to the AI supply chain account for more than half of global GDP.
• AI contribution to US growthAbout 80% over the past five quartersReflected through capital expenditure and wealth effects among high-income groups.
• Contribution to MSCI US year-to-date returnsTechnology stocks contributed 81%Showing that US equity gains are highly concentrated.
• Concentration of US equity market gains10 core US technology and AI companies contributed more than 80% of gains in 2026The concentration has increased market fragility.
• Global growth momentumAbout 2.2%, versus about 2.9% before the Middle East conflictUBS global growth tracking indicators show slowing growth momentum.
• UBS FY2026 global growth forecast3.1%In contrast with current growth momentum.
• Forecast revisions2026 global growth forecast cut by 30bp, inflation forecast raised by 90bpRevised since late February to reflect supply-chain disruptions.
• MSCI AC World targetYear-end target 1200, implying 7% upsideThe report still expects some upside for global equities.
• Year-end credit spread forecastIG 85bp, HY 325bp, leveraged loans 610bpUBS expects credit spread widening, with the greatest pressure in leveraged loans.
• Samsung and SK Hynix free cash flowFCF over the next three years is expected to exceed 90% of current market capUsed to illustrate the profitability of North Asian semiconductor companies within the AI supply chain.

Impact & implications

The investment implication is that AI can still support global growth, the US dollar, and parts of the equity market, but the market is not broadly healthy and is becoming increasingly reliant on a small number of technology companies, the North Asian semiconductor supply chain, and hyperscale cloud providers' capital spending. If energy costs, financing costs, or AI earnings expectations shift unfavorably, equity and credit markets could quickly move from resilience to fragility. Regionally, the US, South Korea, and Taiwan region, which are embedded in the AI supply chain, stand to benefit relatively more, while Europe, the UK, and energy-importing economies face greater pressure.

Risks

• Prolonged disruption to global energy supply, especially if the Strait of Hormuz or the Middle East situation deteriorates again.
• Rising energy costs or financing costs constraining AI capital expenditure.
• US technology or AI earnings coming in below expectations, breaking the market's current core narrative.
• Equity valuations and positioning overly pricing in AI growth, leading to amplified pullbacks.
• Credit pressure spreading through leveraged loans and private credit and spilling over into public markets.
• Inflation remaining high, causing major central banks to follow a tighter policy path than the market hopes for.
• Greater divergence across emerging markets, with energy-importing economies facing higher inflation, weaker currencies, and tighter financial conditions.

What to watch

• Developments in the Middle East, transit through the Strait of Hormuz, and the recovery of global energy supply.
• Whether the oil price curve moves lower and whether inflation forecasts are revised down accordingly.
• Whether AI capital expenditure broadens from hyperscale cloud providers to a wider range of industrial sectors.
• Magnificent 7 second-quarter earnings report dates: TSLA, GOOGL, NVDA, META, MSFT, AMZN, AAPL.
• Credit spreads, technology-sector spreads in leveraged loans, and private credit default rates.
• Global supply-chain delivery times, air freight costs, shipping costs, and non-energy trade volumes.
• FOMC meetings and the actual policy path of major central banks.
• China's Politburo meetings, the Fifth Plenary Session of the 20th Central Committee, and the Central Economic Work Conference.
• Whether JPY requires further intervention, and whether the USD continues to be supported by relative growth and AI leadership.