Big tech’s historic spending spree on AI infrastructure is creating opportunities across the entire technology stack.
Microsoft (MSFT 0.53%), Amazon (AMZN 0.74%), Meta Platforms (META 1.25%), and Alphabet (GOOGL +3.13%) (GOOG +3.10%) are on course to collectively invest $405 billion in artificial intelligence (AI) infrastructure in 2025, 58% more than in 2024. The spending extends far beyond AI accelerator chips such as GPUs — it also includes high-speed networking equipment, massive data centers with available power, advanced cooling systems, and server racks optimized for AI workloads.
Despite fears about the possibility that a recession may be coming, and uncertainties about how the Federal Reserve will act on interest rates, Big Tech executives are planning to accelerate their capital expenditures in 2026 rather than pulling back. Demand for AI-capable computing infrastructure vastly exceeds supply, and for cloud companies, falling behind their competitors means ceding territory in what could be the largest technology shift since the rise of the internet.
Image source: Getty Images.
Here are 10 stocks benefiting heavily from this megatrend.
The computing power leader
Nvidia (NVDA 1.91%) designs the graphics processing units (GPUs) and AI accelerators that power the majority of large-scale AI training and inference workloads. It maintains its dominant position in part thanks to its popular CUDA software ecosystem. Because developers are used to CUDA, and because the programs built on it are only compatible with Nvidia’s chips, it creates significant switching costs for customers already running workloads on Nvidia chips.
Today’s Change
(-1.91%) $-3.63
Current Price
$186.54
Key Data Points
Market Cap
$4534B
Day’s Range
$184.32 – $189.00
52wk Range
$86.62 – $212.19
Volume
100K
Avg Vol
184M
Gross Margin
69.85%
Dividend Yield
0.00%
The networking backbone
Broadcom (AVGO 0.08%) supplies networking chips and custom AI accelerators that connect massive AI clusters, enabling data to flow between thousands of GPUs. The company benefits as hyperscalers build larger AI training clusters that require more sophisticated networking infrastructure to prevent bottlenecks.
The vertically integrated hyperscaler
Microsoft operates Azure cloud infrastructure and is building its own data centers to support both internal AI development and meet the demands of its enterprise customers. Its vertical integration enables it to capture value across the entire AI stack, from infrastructure spending to software revenue generated by AI-powered products.
Today’s Change
(-0.53%) $-2.69
Current Price
$507.49
Key Data Points
Market Cap
$3772B
Day’s Range
$504.91 – $512.12
52wk Range
$344.79 – $555.45
Volume
787K
Avg Vol
21M
Gross Margin
68.76%
Dividend Yield
0.01%
The custom chip innovator
Alphabet operates Google Cloud and designs its own AI chips, known as Tensor Processing Units (TPUs), while building data centers globally to support search, YouTube, and cloud customers. The company’s recent deal to reserve 1 million TPU chips for Anthropic demonstrates how internal infrastructure can generate external revenue streams.
The network fabric specialist
Arista Networks (ANET 3.14%) manufactures high-speed networking switches and routers designed for data center environments where AI workloads demand massive bandwidth. The company’s products form the network fabric that allows AI clusters to scale beyond thousands of GPUs without performance degradation.
The rack integration partner
Super Micro Computer (SMCI 6.40%) builds fully integrated server racks and cooling systems optimized for AI workloads, selling complete solutions rather than individual components. The company serves as a critical link between chip manufacturers and data center operators, providing the hardware integration needed to deploy AI infrastructure quickly.
The data center landlord
Digital Realty Trust (DLR 0.30%) owns and operates data centers globally, leasing space and power to cloud providers and enterprises building AI infrastructure. The real estate investment trust is benefiting from the surging demand for data center capacity in markets with additional electrical capacity, as actual power to support computing power has become a critical constraint for AI deployments.
The interconnection hub
Equinix (EQIX 1.11%) operates interconnection-focused data centers that help companies connect their AI workloads across cloud providers and geographic regions. The company is expanding its portfolio of AI-ready facilities, featuring higher power density and advanced cooling, to capture demand from customers running inference workloads at scale.
Today’s Change
(-1.11%) $-8.69
Current Price
$776.88
Key Data Points
Market Cap
$76B
Day’s Range
$771.00 – $790.51
52wk Range
$701.41 – $994.03
Volume
117
Avg Vol
476K
Gross Margin
34.86%
Dividend Yield
0.02%
The competitive alternative
Advanced Micro Devices (AMD 2.74%) competes directly with Nvidia in AI accelerators, but it also is a major supplier of central processing units (CPUs) for the servers that support AI workloads. The company offers alternatives to Nvidia’s products at competitive prices, positioning it to capture share as enterprises seek to avoid single-vendor dependence.
The long-haul connectivity provider
Ciena (CIEN +0.04%) provides optical networking equipment and software that enables the movement of data between data centers and across long distances at high speeds. It benefits as AI infrastructure becomes geographically distributed, requiring robust connectivity between training clusters, inference deployments, and end users.
The AI infrastructure opportunity
This infrastructure buildout won’t peak in 2026. Morgan Stanley projects an additional $2.9 trillion in AI infrastructure spending through 2028, suggesting years of sustained investment ahead. The companies above represent different layers of the stack, ranging from chips and servers to networking and real estate, providing investors with multiple opportunities to capitalize on this trend.
The key insight is that AI infrastructure spending has become self-reinforcing. As companies like Microsoft and Amazon deploy more capacity, they unlock new AI applications that drive additional demand for computing power, creating a cycle where supply will continue struggling to keep pace. For infrastructure providers, this dynamic translates into multiyear visibility into orders, as well as a level of pricing power that is rarely found in technology hardware markets.