💥 2 Artificial Intelligence Stocks You Can Buy and Hold for the Next Decade

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Hi Fellow Investors,

Artificial intelligence is still in the early stages of a multi-decade transformation.

The biggest winners will not be fleeting app developers, but foundational infrastructure providers.

Two companies stand out as long-term cornerstones of the AI economy.

Key Points:

• AI infrastructure spending is expected to grow aggressively throughout the next decade.

• Nvidia dominates AI computing while continuously expanding its software moat.

• Taiwan Semiconductor Manufacturing enables the entire advanced-chip ecosystem at scale.

Why Long-Term AI Investing Favors Infrastructure Leaders

AI adoption is accelerating across enterprises, governments, and consumers.

This growth requires massive investment in computing power and advanced semiconductors.

Companies providing core AI infrastructure benefit regardless of which applications succeed.

Long-term investors should prioritize durable competitive advantages over short-term trends.

Two companies exemplify this approach better than any others.

The Backbone of AI Computing Power

Nvidia (NASDAQ: NVDA) has emerged as the undisputed leader in AI computing hardware, with its graphics processing units serving as the standard platform for training and deploying advanced AI models.

Its GPUs power the vast majority of AI workloads globally, reflecting both technological superiority and the massive ecosystem built around its products.

Market share approaching 90% did not happen overnight, but rather through years of investment in performance, developer tools, and system-level optimization.

Even as competitors attempt to enter the market, Nvidia continues to widen its lead through rapid innovation and strategic expansion.

This dominance positions Nvidia to remain central to AI infrastructure well into the next decade.

A Software and Ecosystem Moat That Keeps Widening

Nvidia’s competitive advantage extends far beyond the physical chips it sells.

Its CUDA software platform underpins most foundational AI code, creating a deeply entrenched developer ecosystem that is difficult to replicate or replace.

Proprietary networking technologies such as NVLink allow Nvidia’s chips to function as a single, massively powerful computing unit, which is critical for large-scale AI training.

Recent strategic moves into orchestration and inference optimization further strengthen this integrated ecosystem.

Together, these layers of hardware, software, and networking create high switching costs that reinforce Nvidia’s long-term leadership.

Strengths

• Dominant share of AI data center GPUs creates enormous pricing power.

• Deep software ecosystem locks in developers and enterprise customers.

• Continuous innovation across hardware, software, and networking.

Weaknesses

• Revenue remains highly tied to AI capital spending cycles.

• Competition is intensifying at the margins of the inference market.

• Rapid growth raises expectations that must be consistently met.

Potential

• AI workloads are likely to expand exponentially across industries.

• Inference demand could rival training workloads over time.

• Platform expansion may unlock new recurring software revenue streams.

The World’s Most Critical Chip Manufacturer

Taiwan Semiconductor Manufacturing (NYSE: TSM) occupies one of the most powerful and irreplaceable positions in the global AI supply chain.

As the world’s leading advanced semiconductor foundry, TSMC enables nearly every top AI chip designer to manufacture cutting-edge processors at scale.

Producing advanced chips is extraordinarily complex, and rivals continue to struggle with yield, reliability, and consistency at leading-edge process nodes.

These execution challenges have only reinforced TSMC’s dominance in advanced manufacturing.

Without TSMC, the modern AI boom would not be possible.

Winning Regardless of Which Chips Dominate

Unlike chip designers, TSMC does not need to predict which architecture or company will ultimately win market share.

Every increase in AI chip demand flows directly through its manufacturing pipelines.

AI-related chip demand is growing at an estimated compound annual rate exceeding 40%, creating sustained pressure on advanced manufacturing capacity.

This imbalance between supply and demand has improved TSMC’s pricing power, allowing the company to raise prices while maintaining strong customer relationships.

Planned price increases in 2026 further strengthen its long-term earnings trajectory.

Strengths

• Unmatched leadership in advanced semiconductor manufacturing.

• Deep partnerships with leading AI chip designers.

• Strong margins supported by technological complexity.

Weaknesses

• Capital-intensive operations require ongoing massive investment.

• Geopolitical risks periodically impact sentiment.

• Revenue growth depends on global semiconductor demand cycles.

Potential

• AI-driven chip demand could last well beyond the current decade.

• Advanced-node pricing power may continue to strengthen.

• Capacity expansion positions the company for sustained earnings growth

Conclusion

Artificial intelligence is reshaping the global economy over decades, not years.

Nvidia and Taiwan Semiconductor Manufacturing sit at the heart of this transformation.

For long-term investors, these two stocks offer rare durability and scale in AI exposure.

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