Beyond the Mag 7: Investing Across the AI Ecosystem

Capturing the evolution of AI

As AI capital expenditures expand across the technology value chain, we believe a holistic investment approach is increasingly important. While mega-cap companies, particularly the Mag 7, are likely to remain central to the AI build-out, investors may benefit from broadening their exposure beyond these dominant players.

The AI ecosystem can be thought of as consisting of five distinct layers. Diversified exposure across these layers may provide broader participation in the evolving opportunity set.

Exhibit 1: Multiple layers of AI

FIVE-LAYER ARCHITECTURE OF THE AI STACK

1. Energy and power infrastructure
    This foundational layer includes power generation and grid modernization to support AI’s high energy demands. ETN, TT, XYL, SU, and TTE

2. Chips and computing infrastructure
    This layer provides semiconductor design, GPUs, and hardware essential for high-performance AI computing. AMD, LRCX, NVDA, ADI, and ASML

3. Cloud data centers
    Cloud platforms aggregate compute resources, offering scalable and reliable AI processing worldwide. AMZN, GOOG, MSFT, and SPCX

4. AI models
    This core layer encompasses foundational and large language models enabling advanced reasoning and content generation. SPCX, OpenAI, and Anthropic

5. Applications adopters
    AI applications deliver value across industries, driving automation, decision support, and productivity gains. Software, JPM, LLY, HLT, SPCX, industrials, and financials

Source: Allspring. The securities listed above should not be considered a recommendation to purchase or sell any particular security.

The case for a broader allocation

The AI infrastructure build-out has been rapid and capital-intensive. As this phase matures, we expect spending to increasingly shift toward implementation and application across the broader value chain. This evolution could create opportunities in areas such as software, industrial technology, data procurement, and real-world AI use cases.

At the end of 2025, a valuation gap existed between the Mag 7 and the remainder of the S&P 500, with the Mag 7 trading at approximately 22x earnings versus roughly 17x for the rest of the index.² As AI adoption broadens and earnings growth inflects upward across a wider set of companies, this disparity could narrow, potentially driving a rotation toward more diversified exposure. While early signs of this trend have emerged, we believe its full extent still lies ahead.

Our investment approach

Against this backdrop, we are employing a barbell approach, balancing exposure to established leaders with emerging AI beneficiaries.

On one end of the barbell, we maintain exposure to the Mag 7 with reduced position sizes. These companies remain key beneficiaries of ongoing AI-related capital expenditures. Data center spending among the largest players is projected to reach approximately $630 billion in 2026 and $705 billion in 2027, with some estimates exceeding $800 billion over that period. Over the longer term, total spending could surpass $1 trillion by 2028, which we believe underscores the durability of the current investment cycle, though outcomes may vary.²

Exhibit 2: Capital expenditures

Source: Bloomberg Finance L.P. Consensus estimates as of 17-Jun-26. The securities listed above should not be considered a recommendation to purchase or sell any particular security.

At the other end, we are increasingly focused on identifying opportunities at the “edges” of the AI ecosystem—companies with less direct or underrecognized exposure to AI where earnings growth may begin to accelerate. As productivity gains materialize and monetization improves, these companies could see valuations expand, potentially creating attractive stock-specific return opportunities.

Recent developments reinforce this view. For example, results from companies such as ASML Holding N.V. (ASML) and Taiwan Semiconductor Manufacturing Co. Ltd. (TSM) suggest that demand for compute remains strong. Looking ahead, the shift from generative AI to agentic AI may result in higher levels of token consumption (that is, AI processing activity), which could help drive the next phase of AI applications.

Beneficiaries of a broadening AI ecosystem

As the AI theme evolves, certain sectors appear particularly well positioned to benefit.

Industrials offer a compelling mix of secular and cyclical exposure. AI adoption across capital goods and diversified industrials is expanding, with potential applications in product design, engineering, factory automation, labor productivity, predictive maintenance, and pricing optimization. We believe rising investor interest reflects a broader effort to identify AI-linked opportunities with tangible, near-term earnings impact.

Financials, particularly banks, may benefit in multiple ways. While productivity improvements are an important component, the opportunity extends beyond cost efficiencies. Potential applications include credit underwriting, pricing optimization, fraud detection, and risk management. These use cases may span not only consumer banking but also corporate and investment banking as well as asset and wealth management. Additionally, enhanced data capabilities could support improved cross-selling and client engagement, contributing to revenue growth over time.

Positioning for the next phase of AI

The AI investment opportunity is evolving beyond its initial infrastructure-driven phase and broadening across the economy. As capital moves downstream toward implementation and real-world application, relying solely on mega-cap exposure may limit participation in the next phase of value creation.

A diversified, layered approach, combining exposure to established compounders with emerging companies positioned to benefit from the expansion of AI adoption, can offer a more balanced way to capture this evolution. While outcomes are not guaranteed, investors positioned across multiple segments of the AI value chain may be better equipped to navigate and participate in the next wave of technological innovation.

1. The “Magnificent 7” comprises the seven largest tech companies by market capitalization in the S&P 500 as of 3/31/2026: Apple (AAPL), Microsoft (MSFT), Amazon (AMZN), Alphabet (GOOGL), Meta Platforms (META), Nvidia (NVDA), and Tesla (TSLA).

2. Source: Bloomberg Finance L.P.

All investing involves risks, including the possible loss of principal. There can be no assurance that any investment strategy will be successful. Investments fluctuate with changes in market and economic conditions and in different environments due to numerous factors, some of which may be unpredictable. Each asset class has its own risk and return characteristics.

This material is provided for informational purposes only and is intended for retail distribution in the United States.

Diversification does not ensure or guarantee better performance and cannot eliminate the risk of investment losses.

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