Artificial intelligence (AI) has become one of the most powerful technological and economic forces shaping this decade. Global AI spending is expected to grow 44% year over year to $2.52 trillion in 2026, as companies accelerate AI adoption across industries.

As businesses invest heavily in AI infrastructure, cloud platforms, and AI agents, Nvidia (NASDAQ: NVDA), Taiwan Semiconductor Manufacturing (NYSE: TSM), and Microsoft (NASDAQ: MSFT) have emerged as critical enablers of this transformation. Here's why these three stocks appear well-positioned to benefit from the AI boom over the next 10 years.

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Nvidia has become one of the most important companies powering the global AI infrastructure buildout. The company's recent financial performance has been exceptional, including fourth-quarter (ending Jan. 25) revenue of $68.17 billion and net income of $42.96 billion. Management has also highlighted that demand visibility extends into calendar year 2027, supported by inventory and supply commitments .

However, the bigger story for long-term investors is how deeply embedded Nvidia has become in the global AI computing ecosystem.

Analysts expect the top five cloud providers, which together account for over half of Nvidia's total revenue, to spend nearly $700 billion as capital expenditures (capex) in calendar year 2026. Much of this spending is driven by the transition from traditional CPU-based data center workloads to GPU-accelerated computing.

Additionally, AI models are now transitioning from training to inference (real-time deployment). Inference is also increasingly tied to customer revenue generation, since these models power applications such as coding assistants, search, and enterprise software.

As a result, expanding computing capacity enables cloud providers to deploy more inference workloads, which in turn generates more revenue. This dynamic has created a powerful incentive to invest in AI infrastructure, which further fuels demand for Nvidia's chips. Nvidia expects the transition of the traditional workloads and the rise of inference to collectively account for half of its long-term opportunities.

Nvidia has also positioned itself as a full-stack AI player by offering CPUs, GPUs, high-speed networking technologies, and the CUDA software platform. The deep integration across hardware, software, and networking makes Nvidia's platform difficult to replace. Additionally, since Nvidia's GPU architectures are compatible across generations, software improvements are benefiting the entire installed base of chips. This has further strengthened customer lock-in.

Considering Nvidia's strong AI ecosystem, the company can be a smart buy for the next decade.

Taiwan Semiconductor Manufacturing (or TSMC) is playing a crucial role in the AI boom by manufacturing the advanced logic chips that power much of the global AI infrastructure. High-performance computing, which includes AI accelerators and data center processors, is already a strong business and accounted for almost 58% of the company's fiscal 2025 (ending Dec. 31) revenue.

TSMC's AI accelerator (chip) revenue accounted for a high-teens percentage of total sales in 2025. The company expects this business to grow at a mid-to-high-50% compounded annual growth rate from 2024 through 2029. As AI adoption expands across enterprise, customer, and sovereign use cases, demand for cutting-edge chips will continue to rise.

The tech giant also has strong visibility in future demand. Customer engagement cycles have already lengthened, and chip designers are planning manufacturing capacity two to three years in advance. In fact, in many cases, cloud service providers, who have been clients of the company's chip designer customers, are directly approaching TSMC to request additional manufacturing capacity. These trends reinforce the company's claim that AI is now a multiyear megatrend.

TSMC's technology leadership is also strengthening its long-term position. Advanced process nodes (7-nanometer and below) accounted for almost 74% of the company's fiscal 2025 revenue. The company has started high-volume manufacturing at the 2-nanometer node and expects a solid ramp in 2026.

Advanced packaging is also emerging as a key growth catalyst. Since AI accelerators require complex packaging to integrate logic chips with high-bandwidth memory, TSMC expects this segment to grow faster than its overall business in the next five years.

Coupled with its global manufacturing footprint across Taiwan , the U.S., Japan, and Europe, this leading global foundry can remain a pillar of the AI economy in the next decade.

Tech behemoth Microsoft is building capabilities across the entire AI ecosystem, including cloud infrastructure, enterprise software, and developer tools.

Microsoft Azure is the second-largest cloud infrastructure player globally, with 21% market share at the end of 2025. Despite the scale, management claimed that the available cloud capacity is falling short of the demand from AI workloads.

To address this gap, Microsoft is directing significant capital toward GPUs, CPUs, and data center infrastructure needed to run large AI training and inference workloads. While these investments seem very high today, the resulting infrastructure footprint could prove a competitive moat difficult for rivals to replicate or disrupt over time.

Microsoft is focusing on increasing the adoption of its virtual AI assistant Copilot and related AI tools. The company had 15 million paid Microsoft 365 Copilot seats and 4.7 million paid GitHub Copilot subscribers at the end of the second quarter of fiscal 2026 (ending Dec. 31).

The company is also expanding AI monetization avenues through new enterprise offerings such as Microsoft 365 E7, a premium bundle that combines Copilot with identity, security, and governance tools. As AI capabilities get increasingly adopted in everyday work, enterprises will redesign several core processes around these assistants. This can further deepen Microsoft's customer relationships and increase the stickiness of its client base.

Microsoft is also positioning itself as a platform for building AI applications. Through services such as Azure Foundry and Fabric, customers can deploy models, connect them to enterprise data, and build automated agents that perform tasks across business workflows.

The company enjoys a data and distribution advantage, as a significant amount of the global corporate data is already running on its products. As AI tools increasingly rely on this data to generate insights and automate tasks, Microsoft seems well-positioned to play a central role in the AI economy in the next decade.

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Manali Pradhan, CFA has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Microsoft, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has a disclosure policy.

3 Artificial Intelligence Stocks Worth Owning for the Next 10 Years was originally published by The Motley Fool