Focusing on AI and Semiconductors: In-Depth Analysis of 10 Leading Future US Tech Stocks

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You are witnessing the artificial intelligence (AI)-driven technological revolution. AI software ecosystems and semiconductor hardware are the dual engines driving future growth and are golden tracks you cannot miss. We have carefully selected the following 10 leading future US stocks for you:

AI Software Giants: Microsoft (MSFT), Google (GOOGL), Amazon (AMZN), Meta Platforms (META), Palantir (PLTR)

Semiconductor Core: NVIDIA (NVDA), TSMC, ASML , Broadcom (AVGO), Applied Materials (AMAT)

Industry growth forecasts also confirm the enormous potential of this trend.

Key Points

• AI software and semiconductor hardware are important drivers of future tech growth.
• Microsoft, Google, Amazon, Meta, and Palantir are leaders in the AI software field.
• NVIDIA, TSMC, ASML, Broadcom, and Applied Materials are core companies in the semiconductor industry.
• When investing in these companies, you should balance risks and consider long-term holding.
• Understanding the impact of macroeconomic and geopolitical risks on tech stocks is important.

AI Software Giants: Building Future Ecosystems

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The companies you see now are building unbreakable moats in the application and platform layers of AI through software, cloud services, and vast user bases. They not only define technological boundaries but also reshape business models.

Microsoft (MSFT): Leader in AI Commercialization

Microsoft is a giant you cannot ignore in the AI era; it is transforming AI technology into real commercial revenue at an astonishing speed. Through deep ties with OpenAI and its own powerful enterprise channels, Microsoft has successfully injected AI capabilities into its core product matrix.

Its core AI product Microsoft 365 Copilot is sparking an efficiency revolution in the enterprise market. It is not just a tool but more like an intelligent assistant embedded in your workflow.

• Over 90% of Fortune 500 companies have deployed Microsoft 365 Copilot.
• Consulting giants like PwC and EY report that Copilot saves about 46 minutes per employee per day, directly proving its strong return on investment.
• As of the first quarter of fiscal year 2026, Microsoft’s revenue grew 18% year-over-year, with Azure cloud services growing as high as 40%.
• Over 900 million users monthly are using AI-powered Microsoft products.

Microsoft’s unique advantage lies in its Azure OpenAI Service. This service perfectly combines OpenAI’s top models with Azure’s enterprise-grade security, compliance, and private networking features. This provides you with a trustworthy path to safely deploy powerful AI solutions in your existing cloud infrastructure, especially attractive for large enterprises already in the Microsoft ecosystem.

Strategic Vision: Microsoft is not pinning all hopes on OpenAI. The company is actively developing its own AI models, such as MAI-Image-1. This suggests that in the future, Microsoft may reduce dependence on external models and instead build a “good enough and scalable” AI technology stack to meet 80% of enterprise use cases and optimize costs.

Google (GOOGL): AI Model and Search Colossus

Google, as a long-term researcher in the AI field, with its latest Gemini series models, has once again stood at the pinnacle of technology. Gemini is not only the culmination of Google’s AI capabilities but also the core engine reshaping its search and cloud businesses.

The Gemini models, especially its flagship version Gemini Ultra, have shown outstanding performance in multiple key benchmark tests, particularly in multimodal tasks requiring comprehensive understanding across text, images, and video.

The table below visually shows the score comparison between Gemini Ultra and GPT-4 in some key tests:

Google’s competitive advantage lies in its deep technical accumulation and vast data ecosystem. Gemini’s powerful capabilities are being integrated into Google Search, Workspace office suite, and Google Cloud Platform (GCP). For developers and enterprises, GCP provides a powerful platform capable of handling up to 2 million token context windows, meaning you can build more complex and context-aware applications.

Amazon (AMZN): Cloud Computing and AI E-Commerce Engine

Amazon views AI as the key fuel driving growth in its two core businesses—e-commerce and cloud computing (AWS). Every click and search you make on Amazon’s website has AI working silently behind the scenes.

In the e-commerce field, AI applications are everywhere, directly enhancing user experience and company profitability.

• Personalized Recommendations: AI algorithms analyze your shopping behavior to provide precise product recommendations, thereby increasing average revenue per user (ARPU).
• Dynamic Pricing: AI adjusts product prices multiple times a day based on market demand, inventory, and competitor prices to maximize profits.
• Operational Efficiency: Amazon uses AI and robotics to automate its fulfillment centers, significantly reducing operating costs, with its operating margin expected to rise from 6% to 11% by 2025.
• Innovative Shopping Experience: The company’s launched conversational shopping assistant Rufus allows you to discover and learn about products through natural language conversations, representing a shift from traditional social e-commerce to AI-driven product discovery.

In the cloud computing field, Amazon Web Services (AWS) is the world’s largest cloud service provider. AWS provides enterprises with a full set of tools needed to build and deploy AI applications, including self-developed Trainium and Inferentia chips, as well as broad support for mainstream AI models. The massive data generated by the retail business in turn provides valuable nourishment for training AI models in AWS and advertising businesses, forming a powerful growth flywheel.

Meta Platforms (META): AI Transformation of the Social Empire

Meta is undergoing a profound strategic transformation, shifting its focus from the metaverse entirely to artificial intelligence. Company founder Mark Zuckerberg has clearly stated that the future goal is to build artificial general intelligence (AGI). To this end, Meta is making massive capital investments.

• The company expects to invest $70 billion to $72 billion in capital expenditures in 2025, mainly for data center construction, AI chip procurement, and model development.
• Although its metaverse project Reality Labs has accumulated losses exceeding $70 billion since 2021, the company’s strong profitability (43% operating margin) and over $70 billion in cash reserves provide a solid financial foundation for its AI ambitions.

Meta’s unique advantage lies in its open-source Llama series large models and vast social data. By open-sourcing Llama, Meta has built a vibrant developer ecosystem, attracting global talent to collaboratively improve and innovate. At the same time, massive image, text, and video data generated by platforms like Facebook, Instagram, and WhatsApp provide unparalleled resources for training more powerful multimodal AI models. You can foresee that AI will be deeply integrated into Meta’s advertising system, content recommendation, and future smart hardware, thereby opening new growth curves.

Palantir (PLTR): Enterprise-Level AI Decision Platform

Palantir is a software company focused on providing data analysis and decision support for governments and large enterprises. Its core products—Gotham (serving governments) and Foundry (serving commercial clients)—aim to transform complex, scattered data into actionable insights.

Palantir’s business model achieves a good balance between government and commercial clients.

• In the past four quarters, its government and commercial revenue ratio has been stable at 55:45.
• In 2024, the company’s global total revenue reached $2.9 billion, with about 55% from government contracts.
• Its recently launched Artificial Intelligence Platform (AIP) allows customers to safely run large language models on their own data, greatly driving growth in commercial customer numbers.

Palantir’s value lies in its ability to solve real problems. It is not a general AI tool but a platform providing deep solutions for specific industries (such as manufacturing, finance, healthcare). For example, global reinsurance giant Swiss Re achieved significant returns on investment after using Palantir’s platform.

For large organizations seeking deep digital transformation and hoping to use AI to optimize core operations, Palantir provides a powerful and reliable choice. This unique US stock represents the enormous potential of AI in enterprise decision intelligence.

Semiconductor Core: US Stocks Worth Investing In

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If AI software is the brain and soul of this technological revolution, then semiconductors are the heart and skeleton providing power. You cannot build an AI empire without a hardware foundation. The following companies are the “pick-and-shovel providers” forming the cornerstone of AI computing power, occupying indispensable strategic positions in the semiconductor industry chain.

NVIDIA (NVDA): AI Computing Hardware Overlord

You can hardly discuss AI without mentioning NVIDIA. This company has successfully transformed from a gaming graphics card manufacturer into the absolute overlord in AI computing. Its GPUs (graphics processing units) are essential core hardware for training and running today’s most advanced AI models.

NVIDIA’s moat lies not only in its powerful chips but also in its CUDA software platform. This platform provides developers with a mature and efficient programming environment, deeply locking them into NVIDIA’s ecosystem.

Core Insight: NVIDIA is building a full-stack computing platform. It provides not just chips but also networking equipment (Mellanox), software, and cloud services. This allows it to offer end-to-end optimized solutions for data centers, further consolidating its market leadership.

Currently, NVIDIA holds over 80% share in the data center AI chip market. As AI models become increasingly complex, demand for computing power will only grow exponentially, and NVIDIA is at the center of this demand.

TSMC (TSM): Global Chip Manufacturing Cornerstone

TSMC is the world’s largest and most technologically advanced chip foundry. You can think of it as the “central factory” of the tech world, with almost all top fabless semiconductor companies (such as NVIDIA, Apple, AMD) relying on it to manufacture the most cutting-edge chips.

TSMC has absolute dominance in advanced process nodes. Data shows that in the global advanced semiconductor chip manufacturing market below 7nm, TSMC’s share is about 67%. This technological leadership advantage brings it strong pricing power and stable customer relationships.

The explosive demand for AI chips is directly driving TSMC’s growth. The company is making unprecedented capital investments to meet future demand.

• The company forecasts its fourth-quarter revenue to achieve at least 22% year-over-year growth.
• Due to strong AI-related demand, TSMC is accelerating its 2nm process technology deployment at its Arizona factory in the US.
• The company raised its 2025 capital expenditure guidance to between $40 billion and $42 billion, far higher than $30 billion in 2024.
• More advanced 3nm chip shipments already account for 23% of its total wafer revenue, showing strong market demand for high-performance chips.

Investing in TSMC is equivalent to investing in the growth trend of the entire semiconductor industry. As a partner to many tech giants, it is one of the choices with relatively dispersed risk and high certainty in this track.

ASML: Lithography Technology Monopolist

If TSMC is the factory for chip manufacturing, then ASML is the sole supplier of the most critical and expensive equipment in the factory—lithography machines. Without ASML’s extreme ultraviolet (EUV) lithography machines, you cannot manufacture cutting-edge chips at 5nm and below.

ASML holds over 90% of the global market share in EUV lithography, forming a de facto technological monopoly. This unique position makes it the “throat” of the entire semiconductor industry chain.

This monopoly position translates into astonishing profitability and order visibility.

• The average selling price of an EUV system is about $200 million.
• As of the second quarter of 2025, ASML’s order backlog totaled $39.7 billion, foreshadowing strong revenue for the coming years.
• The company is developing the next-generation High-NA EUV system, which will further consolidate its technological leadership and pave the way for 2nm and below chip manufacturing.

For those seeking long-term allocation in the semiconductor field, ASML is one of the brightest pearls in the crown.

Broadcom (AVGO): Networking Chip and Connectivity Expert

When massive data flows inside and between AI data centers, you need high-performance networking chips to ensure everything runs smoothly. Broadcom is the leader in this field, providing critical networking switch chips, custom AI accelerators, and connectivity solutions.

As AI workloads increase, the importance of data center networking is growing. Broadcom, with its technological advantages, is capturing an increasingly larger share in this fast-growing market. Market forecasts show that Broadcom’s market share in computing and networking AI is expected to grow from 11% in 2025 to 24% in 2027.

In addition, Broadcom successfully transformed into a software-hardware integrated infrastructure giant through its strategic acquisition of VMware.

• After the acquisition, its infrastructure software business segment revenue grew 25% year-over-year to $6.6 billion.
• The company’s total revenue grew 20% year-over-year, with net income soaring 124%.
• Broadcom’s strategy is to transition customers to subscription-based VMware Cloud Foundation (VCF) private cloud services, with 87% of top customers now registered.

This transformation not only brought significant revenue growth but also created stable recurring revenue streams. This makes Broadcom a unique US stock combining semiconductor hardware growth potential and software business stability.

Applied Materials (AMAT): Key Semiconductor Equipment Provider

In the long chip manufacturing process, lithography is just one step. Before and after lithography, wafers need to undergo hundreds of steps such as deposition, etching, and inspection, and Applied Materials is the global leader in these critical equipment fields.

According to 2023 data, Applied Materials is in a leading position in the semiconductor wafer fabrication equipment (WFE) market, jointly dominating the industry with ASML, Lam Research, and others. The equipment it provides is the foundation for building complex three-dimensional chip structures.

Applied Materials drives next-generation chip production through continuous materials science innovation. Its latest technological breakthroughs directly address the industry’s most severe challenges.

Innovation Drives the Future: Kinex™ Hybrid Bonding System: For advanced packaging, efficiently integrating different chips. Centura™ Xtera™ Epitaxy System: For producing high-bandwidth memory (HBM) and advanced logic chips. PROVision™ 10 eBeam Metrology System: Provides ultra-high precision measurement, ensuring chip manufacturing yield and reliability.

Investing in this US stock Applied Materials means you are bullish on continuous progress in materials and processes across the semiconductor industry. As chip structures become increasingly complex, demand for Applied Materials’ equipment and technology will also rise accordingly.

Long-Term Investment Strategies and Risk Management

With a selected stock list, you also need a clear strategy to navigate market waves. Successful investing lies not only in choosing the right companies but also in correct execution and risk awareness. This section provides a practical framework for building portfolios, maintaining a long-term mindset, and identifying key risks.

Build Your AI Tech Stock Portfolio

To build a robust AI tech stock portfolio, you need to balance the roles of giants and specialists. An effective method is to adopt a “core-satellite” strategy.

• Core Holdings: Allocate most funds to industry giants like Microsoft (MSFT) and NVIDIA (NVDA) with diversified businesses and abundant cash flows. They are the ballast stones of your portfolio, providing relatively stable growth.
• Satellite Holdings: Use a small portion of funds to invest in specialized companies with high growth potential in specific fields, like Palantir (PLTR) or Applied Materials (AMAT). These investments may bring higher returns but also higher volatility.

This way, you can capture overall industry growth while managing individual stock risks through diversification.

Long-Term Holding Mindset and Discipline

Tech stock volatility is normal. You need discipline to overcome emotional interference. Dollar-Cost Averaging (DCA) is a powerful tool that helps you establish long-term discipline.

Dollar-cost averaging invests a fixed amount at fixed intervals (e.g., monthly), regardless of market price. The core of this strategy is persistence; it helps you accumulate more shares when the market falls and diversify timing risks.

Historical data also supports this strategy. For example, from 2015 to 2020, using DCA on high-growth stocks like Amazon (AMZN) outperformed lump-sum investing. You can use digital asset platforms like Biyapay to set automatic transfers from bank accounts to investment accounts, easily achieving automated DCA and incorporating discipline into your investment process.

Common Risk Identification for Tech Stocks

When investing in high-growth US stocks, you must clearly recognize their inherent risks.

1. Macroeconomic Risks: Tech stocks are particularly sensitive to interest rate changes. When rates rise, future earnings expectations are discounted more heavily, pressuring valuations. At the same time, higher borrowing costs directly affect company profits. History shows that high interest rate environments often challenge growth stocks.
2. Geopolitical Risks: The semiconductor industry is particularly deeply affected by geopolitics. Tensions between the US and China have already reshaped global supply chains. US policies like the CHIPS Act are driving manufacturing reshoring, which helps reduce dependence on single regions but also brings complex logistics challenges and short-term cost increase risks.

You have seen that artificial intelligence and semiconductors are the core themes driving the next decade. The 10 companies we analyzed are leaders in their respective tracks with strong growth potential.

• Goldman Sachs predicts that cloud giants will invest nearly $500 billion in AI capital expenditure next year.
• McKinsey reports that by the next decade, the total AI infrastructure market size could reach $7 trillion.

You can use this article as a starting point for research. Please combine your risk tolerance and investment goals to make informed long-term decisions.

Investment Disclaimer: The stock market involves risks; invest with caution. The content of this article does not constitute any specific investment advice.

FAQ

How Much Starting Capital Do I Need?

The starting capital you need depends on your broker. Many platforms allow you to buy fractional shares, with a minimum of just a few dollars. This lets you start investing in these top US tech companies with small amounts.

These Stocks Are Too Expensive; What Should I Do?

You can consider two strategies:

• Buy fractions of stocks through platforms supporting fractional shares.
• Invest in tech-themed ETFs that include these companies for diversified exposure to the entire industry.

How to Track These Companies’ AI and Semiconductor Business Progress?

You should focus on the company’s quarterly earnings reports, particularly revenue growth in data centers, cloud computing, and AI-related businesses. At the same time, pay attention to guidance on new products and capital expenditures in company conference calls.