30 Jun 2026
While the last technology cycle was consumer led, the AI cycle is shaping up to be more enterprise-focussed. Marcel Stötzel, Portfolio Manager of the Fidelity European Fund and Fidelity European Trust, explains why Europe could prove to be one of the most overlooked AI exposures in global equities, with strengths in sectors such as financials, industrials and healthcare positioning it well for the next phase of AI driven growth.
The last technology cycle was consumer-led. Streaming, social media, smartphones, and electric vehicles transformed daily life, creating enormous value for companies that captured users, attention, and engagement at scale. AI looks different. While consumers will benefit, the biggest economic gains are likely to accrue to businesses using AI to automate workflows, boost productivity, and improve decision-making across the real economy.
That shift has important implications for investors. Europe is often viewed as lacking AI exposure because it has fewer consumer technology champions than the US. But Europe’s strength in banks, insurance, industrials, and pharmaceuticals may make it uniquely positioned for a more enterprise-led AI cycle. As markets move beyond AI model developers and infrastructure providers toward the long-term beneficiaries of adoption, Europe could prove to be one of the most overlooked AI exposures in global equities.
One of the defining features of the last technology cycle was its consumer centricity. The dominant winners of the 2010s - social media platforms, streaming services, smartphones, and electric vehicles - were fundamentally business-to-consumer stories.
Technology delivered more engaging digital experiences, better entertainment, and innovative consumer products, with much of the economic spillover accruing directly to individuals. The next technology cycle, underpinned by AI, is shaping up differently. While consumers will certainly benefit from AI-powered services, the larger economic impact is likely to be felt by enterprises. This cycle is increasingly about businesses becoming more productive, automated, and efficient, shifting the primary spillover beneficiaries from households to companies themselves.
This distinction matters for investors because it changes where value is likely to accrue. It also challenges the simplistic view that Europe lacks meaningful AI exposure. Europe’s deep and diverse base of industrial, financial, healthcare, and infrastructure companies leave it well positioned to benefit from broad-based enterprise adoption of AI.
The previous technology cycle was built around user acquisition and engagement. Companies succeeded by attracting vast consumer audiences and monetising them through subscriptions, advertising, or direct product sales.
Netflix, for example, transformed media consumption through recurring subscriptions, while social media platforms monetised user attention through targeted advertising and powerful network effects. Apple and Tesla combined technology with branding to create highly aspirational consumer products.
Across these businesses, the formula was broadly similar: growth driven by consumer adoption, monetisation through subscriptions, advertising, or product sales, and competitive advantages built on brand strength and network effects. At their core, these were fundamentally consumer-focused business models.
AI is creating a different economic architecture. While consumer-facing applications attract most of the headlines, the larger long-term opportunity may lie in enterprise adoption.
Value in the AI ecosystem can broadly be split into three groups:
So far, investors have overwhelmingly rewarded the first two groups. Share prices of model developers and infrastructure enablers have risen sharply as markets price in accelerating demand and expanding earnings potential. Enterprise beneficiaries, by contrast, have seen far less enthusiasm, creating an inconsistency in the broader AI narrative.
US stocks expensive historically, driven by big tech; Europe relatively cheaper
Source: Fidelity International, LSEG DataStream, May 2026. MSCI indices.
*Big tech (cap weighted) = Nvidia, Alphabet, Apple, Microsoft, Amazon, Broadcom, Tesla, Meta, Micron, Intel, Oracle, Cisco.
If companies are collectively spending hundreds of billions on AI infrastructure and models, it follows that meaningful productivity gains should eventually emerge for the businesses deploying these systems. Yet while providers and enablers have enjoyed both earnings upgrades and multiple expansion, most enterprise users have not.
This incongruence is largely explained by scepticism. Investors want tangible proof that AI adoption will translate into materially stronger earnings for enterprise users before re-rating these businesses accordingly.
Investors have heard promises of digital transformation and process improvement for years, particularly in sectors with legacy systems such as banking and insurance. As a result, there is understandable reluctance towards broad claims around AI-driven productivity.
Many of the most important AI applications are still in their infancy and have yet to meaningfully impact earnings. Most enterprise-grade agentic AI solutions - systems capable of automating entire workflows rather than simply assisting with tasks - have existed for less than six months. It is therefore too early for large-scale benefits to be clearly reflected in reported numbers.
That said, there are already tangible signs of where AI could drive meaningful change. Banks are increasingly discussing the ability of AI to automate customer servicing, compliance, onboarding, and internal operations. Insurance companies are using AI to improve pricing and risk assessment, while AI-driven weather prediction tools are already helping agricultural insurers and farmers make better decisions, with clear implications for reinsurers. Across professional services, AI has the potential to materially increase the amount of work that can be completed with existing employee bases.
Crucially, the benefit of AI does not necessarily require companies to reduce headcount. The more important opportunity may be allowing businesses to take on more clients, process more work, and improve service quality without proportionally increasing labour costs. In this sense, AI has the potential to become a major productivity multiplier across large parts of the economy.
Other sectors may take longer to realise these gains. Pharmaceuticals, for example, face long and complex drug development cycles, but AI still has significant potential to improve discovery, clinical trial design, and data analysis over time.
The key question no longer appears to be whether viable use cases for agentic AI exist, but rather how quickly these solutions can be deployed at scale across organisations.
This shift toward enterprise and industrial beneficiaries is important for Europe. A common perception is that Europe lacks meaningful AI exposure because it does not possess the same concentration of mega-cap technology companies as the US or parts of Asia. However, this view misunderstands where the AI opportunity is increasingly emerging.
European equity markets are structurally different from those in the US. They are less dominated by consumer internet platforms and far more exposed to sectors likely to benefit from enterprise AI adoption, including financials, energy and power infrastructure, pharmaceuticals, industrial automation, and engineering. In many respects, Europe’s market composition is naturally aligned with a more enterprise-driven AI cycle.
US index dominated by tech; Europe led by financials, industrials and health care
Europe also possesses a deep industrial backbone that is critical to scaling AI infrastructure globally. European companies are global leaders in semiconductor manufacturing equipment, electrical systems, power management, cooling technologies, thermal solutions, industrial automation, and precision engineering. These businesses form part of the enabling layer of AI, supplying the physical infrastructure required to support increasingly compute-intensive systems.
Power is key area of exposure. AI is highly energy intensive, placing electricity generation, grid investment, and energy efficiency at the centre of the investment case. Europe’s providers in these areas therefore stand to benefit directly from rising AI deployment and data centre demand.
Yet the most underappreciated opportunity may lie not with the enablers, but with Europe’s enterprise users themselves. As AI adoption broadens across industries, Europe’s banks, insurers, industrial companies, and healthcare businesses could become some of the largest long-term beneficiaries of AI-driven productivity gains.
We have analysed the opportunity set company by company across Europe and estimate that approximately 20% of MSCI Europe constituents have direct revenue exposure to AI. At a sector level, exposure is particularly high within IT (70%), industrials (35%), and communication services (15%).
Despite this, many enterprise beneficiaries have yet to see their AI potential reflected in share prices - a disconnect that is unlikely to persist indefinitely. Historically, markets tend to reward infrastructure providers early in a technology cycle because capital expenditure is immediately visible in revenues and earnings. The productivity benefits for end users typically emerge later, once adoption becomes widespread and operational improvements begin to flow through to financial results. That pattern appears to be unfolding again.
The first phase of the AI cycle rewarded the builders: semiconductor companies, model developers, and infrastructure suppliers. The next phase may increasingly reward the adopters - companies capable of translating AI into higher productivity, stronger margins, improved customer retention, and faster growth. This is an area where Europe may contain many of the market’s future winners.
The last technology cycle was consumer-led. Smartphones, streaming, digital payments, social media, and cloud software transformed convenience, entertainment, and connectivity for individuals. Companies created enormous value by capturing users, monetising attention, and building powerful consumer brands.
The AI cycle is likely to evolve differently. While consumers will still benefit, the potentially larger and more durable economic gains may accrue to enterprises through productivity improvements, workflow automation, and better decision-making. That distinction matters because it changes where investors should look for long-term value creation. Rather than focusing solely on consumer technology platforms, investors increasingly need to consider the broader ecosystem - particularly the enterprise users capable of deploying AI effectively at scale.
Europe is well positioned for this shift. Its enterprise-heavy market structure means it is far more exposed to AI than conventional wisdom suggests. The market has already rewarded the builders of AI. The next question is whether it is beginning to underestimate the long-term beneficiaries who will ultimately use it most effectively.
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