The 10-week rolling correlation between European software and semiconductors fell to around -0.7, with AI theme trading dominating sector volatility

Overview

This report reviews the sharp weekly volatility in the European Software & Services sector and analyzes its increasingly strong inverse trading relationship with the semiconductor sector. Morgan Stanley believes AI infrastructure and semiconductors are currently the “price makers” of market sentiment, while Software & Services has become a “price taker” due to long-term concerns about AI disruption. However, second-quarter results were generally solid, software vendors have not shown widespread business impairment, and sector fundamentals are more resilient than the market’s bearish narrative suggests. The report also discusses returns on GenAI infrastructure investment, AI talent restructuring in the IT services industry, earnings progress among European software companies, and legal technology competition.

Core views

First, the negative correlation trade between software and semiconductors has reached a historically rare intensity, and short-term fund flows and AI infrastructure sentiment may still overwhelm software fundamentals. Second, second-quarter growth data indicate that mature software products remain difficult to replace and industry moats still exist, but a broader set of software companies need to prove AI revenue contribution over the coming quarters. Third, as earnings releases continue, differences in growth, competitiveness, and AI monetization among application software companies are expected to drive stock prices from sector-wide linkage toward stock-specific differentiation. Fourth, GenAI infrastructure may generate incremental return on investment of roughly 25% or more under multiple business models, with scale, model innovation, token efficiency, and data center capacity being key variables. Fifth, the IT services industry faces AI talent shortages, delivery model transformation, and ongoing M&A costs; valuations should place more emphasis on free cash flow after deducting stock-based compensation and acquisition spending.

Analysis framework

The report combines rolling correlations of European Software & Services and semiconductor constituents, long-term historical averages, second-quarter company results and guidance, next-twelve-month P/E ratios, AI infrastructure unit economics models, and talent supply-demand analysis based on 5 million job postings and 1 million developer profiles to assess sector fund flows, fundamental resilience, AI investment returns, and the pace of industry transformation.

Methodology notes

• Market Linkage Analysis10-Week Rolling Correlation Analysis

  Compare the short-term rolling correlation between European Software & Services and European semiconductor constituents, using the long-term average correlation as the benchmark.

  The current correlation of around -0.7 contrasts sharply with the approximately 10-year average of +0.55, indicating that the market is treating semiconductors as beneficiaries of AI infrastructure while treating software as a potentially disrupted group.

• Capital Return AnalysisGenAI Incremental Return on Investment and Unit Economics Model

  Separately model three business models: hyperscale cloud provider GPU leasing, model APIs, and model APIs running on third-party infrastructure.

  The framework emphasizes the impact of token pricing, token efficiency, model innovation, infrastructure utilization, and data center capacity on incremental return on investment.

• Labor Supply-Demand AnalysisQuantitative Analysis of the AI Reskilling Race

  Use hiring demand and developer skills profiles to evaluate AI talent supply and demand, changes in job structure, and IT services companies’ transformation capabilities.

  Demand for high-end talent capable of building and deploying AI at scale is growing rapidly, while demand for entry-level and easily automated roles is declining; talent scarcity may force IT services companies to continue acquiring capabilities at higher valuations.

• Valuation AnalysisNext-Twelve-Month P/E Ratio and Free Cash Flow Analysis

  Compare covered companies’ next-twelve-month P/E ratios and valuations relative to the European market, and assess the impact of M&A and stock-based compensation on real cash returns.

  For IT services companies that need to repeatedly acquire AI capabilities, free cash flow after deducting stock-based compensation and acquisition spending may better reflect economic value than traditional P/E ratios.

Asset mapping & comparison

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

• European Software & Services stocks

  A major pressured sector amid AI disruption concerns, while also benefiting from second-quarter fundamental resilience.

  Strengths

  Mature software is embedded in customer workflows, with high replacement costs; companies such as SAP, ServiceNow, RELX, and Sage show solid growth.

  Weaknesses

  Short-term share prices are dominated by semiconductor and AI infrastructure fund flows, and sector-wide proof of AI revenue remains insufficient.

  Comparison

  Relative to semiconductors, Software & Services currently looks more like a “price taker” in the AI theme trade.

  Risks

  AI competition, pricing pressure, growth slowdown, and continuation of the sector’s negative correlation trade.

• European semiconductor and semiconductor equipment stocks

  Viewed by the market as direct beneficiaries of AI infrastructure buildout.

  Strengths

  Benefit from demand for computing power, data center capacity, and sustained capital expenditure.

  Weaknesses

  Valuations and sentiment are highly sensitive to expectations for returns on AI investment.

  Comparison

  The 10-week rolling correlation with Software & Services has fallen to around -0.7.

  Risks

  Slower infrastructure investment, insufficient utilization, or AI commercialization returns below expectations.

• AMZN, GOOGL, MSFT, and META

  Research cited in the report views them as key beneficiaries of scaled GenAI infrastructure and platform economics.

  Strengths

  Have advantages in capital scale, cloud infrastructure, model ecosystems, data, and data center capacity.

  Weaknesses

  Need to continue investing substantial capital and prove that incremental revenue and returns can cover the investment.

  Comparison

  Compared with smaller participants, scaled platforms are better able to absorb model R&D and infrastructure costs.

  Risks

  Longer capital expenditure payback periods, declining token prices, intensifying competition, and regulatory constraints.

• Global IT services stocks

  Potential beneficiaries of enterprise AI implementation, while also bearing pressure from talent and delivery model transformation.

  Strengths

  Trusted AI implementation services become more valuable due to talent scarcity, and early transformers may gain share.

  Weaknesses

  Transformation is highly complex and may require continued high-priced acquisitions of skills and capabilities.

  Comparison

  Compared with the 2014 cloud transition, this cycle requires not only changing revenue sources but also restructuring delivery models.

  Risks

  Talent shortages, M&A costs, stock-based compensation dilution, and industry revenue falling into a negative-growth scenario.

• RELX and Wolters Kluwer

  Facing competition from new legal technology entrants, while also possessing content, software, and existing customer bases.

  Strengths

  RELX’s content-based business and Wolters Kluwer’s software and content portfolio have data and workflow advantages.

  Weaknesses

  Competition is intensifying in the market for enterprise legal departments and large law firm workflow tools.

  Comparison

  Harvey and Legora are progressing quickly in legal workflow tools, but the competitive landscape in legal research has changed little so far.

  Risks

  New product substitution, price competition, AI capability gaps, and customer migration.

Key data

• Software and semiconductor 10-week rolling correlationAround -0.7Represents a strong negative correlation; the approximately 10-year average correlation is +0.55.
• Intra-week rebound in the Software & Services sectorMost covered names rose by more than 15% at one pointThe gains mainly occurred from Monday to Wednesday, then retreated noticeably as AI infrastructure and semiconductors strengthened.
• GenAI incremental return on investmentAround 25% or moreApplies to the three main AI inference business models analyzed in the report; actual results depend on assumptions such as pricing, efficiency, and utilization.
• AI talent demand proxy indicatorUp 107% year over yearAs of May 2026, this refers to demand for specialized talent capable of building AI and deploying it at scale.
• Demand for entry-level or easily automated rolesDown 5% year over yearShows clear polarization in the technology talent market.
• 2028 revenue of covered IT services companiesApproximately USD 300 billionAround 20 companies have a 2026 to 2028 base-case compound growth rate of 4%, with a scenario range of -3% to +7%.
• Microsoft Azure growthUp 43% in constant currencyAccelerated by 4 percentage points sequentially, with F1Q27 guidance of around 45%.
• Sage organic total revenue growthApproximately 10.4% for the nine-month cumulative periodCorresponding to around 11% in the third quarter; the share price rose around 9% on the day results were announced.
• Capgemini FY26 growth guidance8.5% to 9%Previously 6.5% to 8.5%; the share price still fell around 5% on the day, reflecting concerns over margins and second-half deceleration.
• RELX legal business revenue growthUnderlying revenue rose around 10% year over year in the first halfAccelerating growth eased some concerns about AI competition.

Impact & implications

In the short term, AI infrastructure capital expenditure and semiconductor performance may continue to determine risk appetite for the software sector, temporarily disconnecting industry fundamentals from share-price performance. Over the medium term, sustained revenue growth, customer retention, pricing power, and verifiable AI revenue will become the core indicators for distinguishing software companies. Hyperscale cloud platforms have strong advantages through capital, computing power, data center capacity, and model ecosystems; IT services companies must restructure skills and delivery models while bearing higher training or M&A investment. Investors should reduce reliance on single-sector valuation averages and place more emphasis on company-level AI monetization, moats, cash-flow quality, and delivery against guidance.

Risks

• The strong negative correlation trade between software and semiconductors may persist, preventing improving software company fundamentals from being reflected promptly in share prices.
• Generative AI may weaken the pricing power, seat demand, or traditional delivery models of some application software and IT services businesses.
• If a broader set of software companies cannot demonstrate AI revenue contribution, sector sentiment may weaken again.
• AI talent scarcity may push up compensation, training, and M&A costs, compressing free cash flow for IT services companies.
• Even if some companies beat revenue expectations, they may still see negative share-price reactions due to margins, guidance, or excessive prior gains.
• Middle East conflicts and changes in air traffic may continue to affect the operating performance of travel technology companies such as Amadeus.
• Intensifying competition in legal workflow tools may create medium- to long-term pressure on related businesses of RELX and Wolters Kluwer.
• The report involves multiple companies with which Morgan Stanley has shareholding, investment banking, or other commercial relationships; investors should make prudent judgments in conjunction with the disclosures.

What to watch

• Whether the 10-week rolling correlation between European software and semiconductors reverts from around -0.7 toward its long-term average.
• Whether software companies can continue to prove growth resilience and AI revenue contribution in subsequent second- and third-quarter earnings reports.
• Whether application software vendors’ share prices shift from sector-wide linkage to fundamentals-based stock-specific differentiation.
• AI infrastructure capital expenditure, data center capacity utilization, and the actual return on investment of the three GenAI business models.
• Progress by IT services companies in AI talent hiring, internal reskilling, delivery model adjustment, and M&A spending.
• Thomson Reuters’ next results as a test of the competitive landscape in legal research and legal workflow.
• Capgemini’s second-half growth pace, Nemetschek’s media business guidance, and the recovery of Amadeus air traffic.