AI’s Hidden Giants: Infrastructure Stocks Enabling the Boom

#The Backbone of the AI Economy

This article is part of our in-depth AI investing series, spotlighting companies entering high-growth mode with accelerating market adoption. While Tier 1 companies get the spotlight for developing AI models and flashy applications, companies in the Tier 2: Enablers & Infrastructure sector form the backbone that makes it all possible. These companies may not be creating AI models themselves, but they provide the essential tools, platforms, and hardware that power AI innovation. An overview of the four investing opportunity tiers can be seen in our eye-catching visualization of AI investing opportunities.

From semiconductors to cloud computing, networking, and data platforms, these firms are the picks-and-shovels suppliers in the AI gold rush. Their role is critical because no AI application can run without the processing power, storage, connectivity, and data management systems they provide.

For investors, this tier offers a balance of AI exposure and business stability. Many companies here have diversified revenue streams and are profitable, making them an attractive complement to higher-risk direct AI plays.

*These companies are vertically integrated across multiple categories and tiers.

#Why Enablers & Infrastructure Matter

The companies in this tier serve as the foundation for the AI ecosystem. They ensure AI workloads can run at scale, data can move securely, and models can be trained efficiently. Without this layer, the AI market would stall.

Importantly, growth in AI demand often translates into steady, recurring revenue for these firms. As enterprises increase AI usage, they consume more cloud capacity, buy more chips, and adopt more specialized data and networking solutions.

#Categories and Key Players

Semiconductors & Accelerators

NVIDIA, AMD, and Broadcom are at the core of AI hardware performance. NVIDIA’s GPUs are the industry standard for AI training and inference, while AMD competes in both CPU and GPU markets. Broadcom designs custom chips and networking hardware to handle AI-scale workloads.

The AI boom has driven unprecedented demand for high-performance chips, making this category one of the clearest beneficiaries of the trend.

Cloud Infrastructure Providers

Amazon Web Services (AWS), Microsoft Azure, and Google Cloud provide the computing power and scalability AI workloads require. Enterprises increasingly prefer to train and deploy models on cloud platforms rather than build their own infrastructure, creating sticky customer relationships and long-term contracts.

Data Infrastructure

MongoDB, Elastic, and Confluent specialize in storing, searching, and streaming massive datasets. AI systems rely on high-quality, accessible data, and these companies’ platforms are designed to handle scale and complexity. As AI adoption grows, so does demand for efficient data pipelines.

Data Labeling & Annotation

TELUS International is the only publicly traded company in this space. It helps prepare and label the datasets used to train AI models, a process critical for accuracy. While many competitors are private, TELUS International gives public investors rare access to this essential AI function.

Networking & Edge Computing

Arista Networks, Cisco Systems, and Marvell Technology provide high-speed networking solutions and edge computing capabilities. As AI moves beyond central data centers to edge devices, low-latency connections and distributed processing become increasingly important.

Specialist AI Tools

Datadog, Dynatrace, and Confluent offer monitoring, analytics, and data streaming services tailored for AI workloads. They help ensure systems remain efficient, secure, and scalable as AI adoption expands.

#Opportunities and Growth Drivers

Tier 2 companies benefit from AI demand more consistently than Tier 1. Even if a specific application fails, infrastructure needs persist. Key growth drivers include:

• Expanding enterprise AI adoption, which increases demand for computing and storage.

• AI workloads requiring high-bandwidth networking and advanced data management.

• Long-term cloud migration trends that align with AI deployment.

Because many Tier 2 companies already have established customer bases, AI represents a growth accelerator rather than a complete reinvention.

#Risks and Headwinds

The primary risk for this tier is cyclical demand. Semiconductor and hardware markets can be volatile, with supply chain constraints and overcapacity cycles impacting profitability.

Cloud providers face competitive pricing pressures, and enterprise customers may negotiate aggressively for lower costs. Regulatory issues around data sovereignty could also complicate cloud and data infrastructure operations.

While less volatile than Tier 1, some companies here are still exposed to rapid technology shifts that could disrupt current product lines.

#Portfolio Fit

Tier 2 fits well for investors who want exposure to AI’s growth without the sharp swings common in Direct Exposure (Pure AI Plays). These companies often have established revenue streams and dividend potential, making them suitable for both growth-oriented and more conservative portfolios.

Given the breadth of categories, investors can build diversified AI exposure within AI Enablers and Infrastructure stocks alone, spreading investments across semiconductors, cloud platforms, networking, and data tools.

#FAQs

Do Tier 2 companies rely entirely on AI for revenue?

No. Most generate significant income from non-AI markets, which provides stability.

Are semiconductors the best way to play this tier?

Semiconductors are a high-growth segment, but diversification across categories helps reduce cyclicality risk.

Can Tier 2 outperform Tier 1 over time?

In some market conditions, yes, especially if infrastructure demand remains strong even when direct AI plays face setbacks.

Is Tier 2 suitable for dividend investors?

Some companies here pay dividends, but many reinvest heavily into growth. Dividend yield varies by category.