AI Rally Broadens Beyond Big Tech as Semiconductor and Industrial Stocks Gain
The artificial-intelligence rally is increasingly moving beyond the mega-cap technology companies that dominated the first phase of the market cycle.
By June 2026, gains were spreading through semiconductor equipment, connectivity, power-management, healthcare and industrial companies as investors looked further down the AI infrastructure chain. Investing.com's June analysis highlighted this shift, pointing to stocks such as Marvell Technology, Allegro MicroSystems, Onto Innovation, Haemonetics and Nucor among companies that had recorded substantial gains in different strategies.
The development matters because the AI investment boom is becoming less about a handful of chip designers and cloud giants and more about the physical infrastructure required to build and operate increasingly powerful data centres.
At the same time, investors should distinguish between a broadening AI theme and evidence that every company benefiting from it will deliver similar returns. The performance figures highlighted by quantitative models are historical results, not forecasts.
From AI Leaders to the “Picks and Shovels”
The first phase of the AI stock rally was concentrated heavily in companies directly associated with generative AI, particularly GPU manufacturers, hyperscalers and major software platforms.
The next stage is reaching companies that provide the infrastructure underneath that ecosystem.
That includes:
Advanced semiconductor manufacturing equipment
Custom AI silicon
Optical networking
Power-management components
Semiconductor inspection and metrology
Data-centre connectivity
Electricity and grid infrastructure
Investing.com's June ProPicks analysis described this as a structural shift toward companies supplying the infrastructure behind AI rather than only companies selling AI applications to consumers. Its June strategy added Marvell Technology and Allegro MicroSystems, both positioned around data-centre and semiconductor infrastructure.
The underlying logic is straightforward: building more AI computing capacity requires substantially more chips, networking equipment, power electronics and advanced manufacturing tools.
Marvell Shows Why Custom AI Silicon Matters
Marvell Technology has become one of the more visible beneficiaries of the expansion in custom AI infrastructure.
The company develops networking and semiconductor solutions used in data centres. Investing.com's June analysis highlighted Marvell's data-centre exposure and reported that the segment accounted for about 76% of revenue at the time, while first-quarter revenue had risen 28% year over year.
The company is also part of a broader shift toward custom silicon.
Custom AI chips allow large cloud companies to design hardware around their specific workloads rather than relying exclusively on general-purpose accelerators. That can create opportunities for semiconductor designers and connectivity suppliers even when they do not manufacture the final AI processor themselves.
For investors, this means the AI opportunity is increasingly visible across the supply chain.
Onto Innovation Highlights the Semiconductor Equipment Angle
Another example is Onto Innovation, which provides inspection and metrology equipment used in semiconductor manufacturing.
The company became one of the stocks highlighted by Investing.com's AI-based selection process in June. At the time, the analysis pointed to accelerating revenue, advanced-packaging demand and a qualification of Onto's next-generation inspection platform by TSMC.
This is an important part of the AI infrastructure story.
Advanced AI processors are becoming more complicated to manufacture and package. As chip architectures become denser, manufacturers need increasingly sophisticated tools to identify defects and maintain production yields.
That creates a secondary investment theme: the companies helping chipmakers manufacture increasingly complex AI hardware.
However, semiconductor-equipment stocks can also experience significant valuation swings because investors tend to price in future industry growth well ahead of reported earnings.
The Rally Is Also Reaching Non-Tech Sectors
The more interesting development is that the AI-driven market strength is not remaining entirely inside semiconductors.
Investing.com's June data showed gains among healthcare, consumer and industrial names as well. For example, Haemonetics was reported at a 46.39% gain from when it was selected in one of the company's strategies, while Nucor was up 62.35% from its selection point. Cardinal Health and Molina Healthcare were also among the companies showing substantial gains from their respective selection dates.
These figures should be interpreted carefully.
They do not mean that the entire healthcare or industrial sector is now an AI trade. Instead, they illustrate how quantitative strategies can identify companies whose individual earnings, valuation, momentum or industry characteristics align with a broader market rotation.
That distinction is particularly important for retail investors.
A stock rising alongside the AI rally does not automatically mean its underlying business is driven by AI.
Why the Rally Is Spreading
Several forces can help explain the widening market participation.
1. AI capital spending is becoming broader
Large technology companies continue to invest heavily in data centres, computing capacity and networking.
That spending creates revenue opportunities for suppliers further down the chain.
2. Investors are searching for the next beneficiaries
After major AI leaders generated enormous gains, investors naturally began looking for companies that could benefit from the same spending cycle without having the same business model or valuation profile.
That search can move capital into smaller semiconductor, networking and infrastructure companies.
3. Earnings are becoming more important
The market is increasingly looking for evidence that AI spending translates into actual revenue and earnings growth.
Companies supplying the infrastructure can sometimes benefit from AI investment without needing to develop a successful consumer-facing AI application themselves.
4. Quantitative strategies can accelerate rotation
Systems that screen thousands of stocks using momentum, valuation and financial metrics can identify companies showing improving characteristics before they become widely discussed.
Investing.com says its ProPicks system evaluates thousands of global equities using more than 150 quantitative models and more than 15 years of financial data.
That is a description of the platform's methodology, not independent evidence that the model will outperform in the future.
The 29% Lesson: Models Can Also Sell Winners
One of the most important details in the June analysis is that quantitative models were not simply adding AI-related stocks.
They were also taking profits.
Applied Materials, for example, was shown with a total return of about 29.7% since selection in the Tech Titans strategy before being rotated out. Investing.com's analysis attributed the decision to valuation concerns and slower relative growth, alongside other factors.
Asana was another previous winner that the strategy exited after a reported return of more than 29%.
This illustrates how systematic investing differs from a simple “buy AI stocks” strategy.
A quantitative model may identify a company because its momentum and fundamentals improve, then later reduce or eliminate the position when valuation becomes less attractive or another stock offers a stronger combination of signals.
For investors, that is a useful reminder that the theme and the individual stock are two different things.
What Could Go Wrong?
The AI infrastructure trade also carries significant risks.
Valuation risk: Strong expected growth can already be reflected in share prices. If earnings fail to catch up, even good companies can experience sharp corrections.
Capital-spending risk: Data-centre construction depends on continued spending by hyperscalers and other large technology companies. A slowdown could ripple through the semiconductor supply chain.
Cyclical risk: Semiconductor equipment and components remain cyclical industries. Demand can rise quickly and then weaken when customers adjust inventories or capital expenditure.
Concentration risk: Many companies benefiting from AI infrastructure ultimately depend on a relatively small group of large technology customers.
Model risk: Historical quantitative performance does not guarantee future results. Market regimes change, and signals that worked during one phase may become less effective during another.
What Investors Should Watch
The next phase of the AI rally will depend increasingly on earnings rather than headlines.
Investors should monitor capital expenditure plans from major cloud companies, semiconductor orders, data-centre power demand, advanced-packaging capacity and revenue growth among equipment suppliers.
It is also worth watching whether market leadership continues to broaden.
If semiconductor infrastructure companies continue reporting strong order growth while industrial and power-related businesses begin seeing tangible AI-linked demand, it would provide stronger evidence that the investment cycle is spreading through the wider economy.
Conversely, if AI capital expenditure slows or valuations expand much faster than earnings, the most aggressively priced stocks could become vulnerable even if the long-term AI theme remains intact.
Bottom Line
The AI rally is increasingly spreading beyond the most familiar mega-cap technology names. Companies involved in custom silicon, networking, semiconductor inspection, power management and other infrastructure are becoming increasingly important parts of the investment story.
Recent performance figures cited by Investing.com's quantitative strategies — including gains above 40% in some individual positions and roughly 29% returns on certain exits — show how quickly leadership can change. But these are historical model results, not promises of future performance.
For investors, the more durable question is whether AI spending continues to translate into rising revenue, margins and cash flow across the broader supply chain. That is likely to matter more than any single stock's past percentage gain.
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This article is for informational and educational purposes only and should not be considered investment advice.