2025 AI Stock Investment Guide: Master These AI-Related Stocks and Seize the Tech Wave Opportunities

Where Are the Investment Opportunities in the AI Revolution?

Since ChatGPT sparked the wave of generative AI, valuations of AI-related companies in the capital markets have undergone dramatic changes. Many companies, despite limited profit growth, have seen their stock prices increase several times. The question is: where exactly are the real investment opportunities in AI-related stocks? How should the AI industry chain be classified? Which AI stocks in Taiwan and the US are worth关注? This article will answer these questions one by one.

What Are AI-Related Stocks?

The essence of artificial intelligence (AI) is to endow computers and machines with human-like intelligence capabilities, enabling them to learn new knowledge, reason, solve complex problems, understand language, generate text and images, etc. Everyday interactions with Siri, ChatGPT, autonomous driving, and others all fall within the scope of AI.

AI-related stocks refer to listed companies that are closely associated with AI technology. These enterprises may be chip manufacturers, server suppliers, or cloud platform and AI software service providers. Essentially, investing in AI-related stocks means investing in the hardware infrastructure and application ecosystem of the AI era.

The Market Status and Growth Potential of AI-Related Stocks

According to the latest IDC research, global enterprise spending on AI solutions will reach $307 billion by 2025. By 2028, total expenditure, including AI applications, infrastructure, and related services, is expected to surpass $632 billion, with a compound annual growth rate of about 29%. Among these, spending on accelerated servers will account for over 75%, becoming the core hardware support for AI technology implementation.

This figure fully demonstrates that the AI industry still has enormous growth space. Increasing numbers of institutional investors and hedge funds are boosting their allocations to AI-related stocks. For example, in Q2 2025, the Bridgewater Fund significantly increased holdings in NVIDIA, Alphabet (Google), Microsoft, and other core AI companies, reflecting capital deployment in key AI ecosystem links such as computing power, chips, and cloud computing.

Many investors are also beginning to allocate through thematic funds and ETFs, achieving a one-time layout across multiple segments. According to Morningstar, by the end of Q1 2025, the total assets of global AI and big data funds had exceeded $30 billion.

Overview of AI-Related Stocks in US and Taiwan Markets

Below are some well-known AI-related stocks selected based on market capitalization, stock price, and annual growth:

Leading US AI Stocks

Representative AI Stocks in Taiwan

(As of September 19, 2025, Source: Google Finance)

Leading AI Stocks in Taiwan

Quanta Computer (2382): A New Star in the AI Server Market

Quanta, once the world’s largest notebook contract manufacturer, has successfully transformed into the AI server field. Its subsidiary QCT specializes in servers and cloud solutions, successfully entering top US data centers, mainly serving NVIDIA and international cloud providers.

In 2024, Quanta’s annual revenue reached NT$1.3 trillion, with a continuous increase in AI server proportion and significant gross margin improvements. Entering 2025, driven by a surge in AI server shipments, Q2 revenue broke NT$300 billion, up over 20% year-over-year, hitting a new high for the same period. Foreign institutional investors are generally optimistic about its long-term growth, with target prices ranging from NT$350 to NT$370.

Realtek-KY (3661): The Hidden Champion in ASIC Design

Realtek focuses on customized ASIC chip design, serving clients including US cloud giants and leading companies in HPC and AI fields. In 2024, full-year revenue reached NT$68.2 billion, with a growth rate exceeding 50%, demonstrating strong growth driven by AI demand.

In Q2 2025, quarterly revenue surpassed NT$20 billion, doubling compared to the same period last year, with continuous improvements in gross margin and net profit margin. Benefiting from large AI client projects entering mass production and receiving new AI accelerator orders for next-generation products. Foreign investors’ average target price is between NT$2,200 and NT$2,400.

Delta Electronics (2308): An AI Layout in Power Management

Delta Electronics is a global leader in power management and power solutions, actively entering the AI server supply chain in recent years. In 2024, annual revenue was about NT$420 billion, with data center and AI application segments steadily increasing.

In Q2 2025, revenue reached NT$110 billion, up over 15% year-over-year, benefiting from expanding demand for AI servers and data center infrastructure, maintaining high gross margins.

MediaTek (2454): The Promoter of Mobile AI Chips

MediaTek is among the top ten fabless design companies worldwide. With the rise of generative AI, it actively promotes AI chip layout. Its Dimensity series mobile platforms have built-in enhanced AI computing units and collaborate with NVIDIA to develop automotive and edge AI solutions.

In 2024, full-year revenue reached NT$490 billion, with gross margin gradually recovering each quarter. In Q2 2025, revenue was about NT$120 billion, up approximately 20% year-over-year, mainly driven by increased market share in high-end mobile chips and rising demand for AI smart devices. Foreign target prices range from NT$1,300 to NT$1,400.

DFI (3324): Key Supplier of Liquid Cooling Solutions

DFI is a leading Taiwanese manufacturer of cooling solutions, focusing on high-performance water cooling modules. As AI servers’ power consumption exceeds kilowatts, traditional air cooling hits bottlenecks. DFI’s advanced liquid cooling technology successfully positions it in the AI server supply chain.

In 2024, revenue reached NT$24.5 billion, with an annual growth rate over 30%. In 2025, benefiting from cloud providers accelerating the adoption of liquid cooling, shipments of water-cooled modules for AI servers surged significantly. Foreign institutional target prices are mostly above NT$600.

Absolute Leaders of AI Stocks in the US

NVIDIA (NVDA): The Absolute Dominator of AI Computing

NVIDIA is the global leader in AI computing, with its GPUs and CUDA software platform becoming industry standards for training large AI models. In 2024, revenue hit $60.9 billion, with a growth rate over 120%, showcasing its remarkable growth amid AI demand explosion.

In Q2 2025, revenue again hit a new high of about $28 billion, with net profit increasing over 200% year-over-year. Driven by strong demand from cloud providers and large enterprises for Blackwell architecture GPUs. As AI applications shift from training to inference and gradually penetrate enterprise and edge scenarios, the demand for NVIDIA’s high-performance solutions will continue to grow exponentially. Many institutions have raised target prices and issued “Buy” ratings.

Broadcom (AVGO): The Network Hub of AI Data Centers

Broadcom plays a key role in AI chips and network connectivity. With its customized ASIC chips, network switches, and optical communication chips, it successfully positions itself in the AI data center supply chain.

In FY2024, revenue reached $31.9 billion, with AI-related product revenue rapidly increasing to 25%. In Q2 2025, revenue grew 19% year-over-year, benefiting from cloud providers accelerating AI data center deployment, with demand for Jericho3-AI chips and Tomahawk5 switches continuing to rise. Foreign reports set target prices above $2,000.

AMD (Advanced Micro Devices): A Strong Challenger in AI Chip Market

AMD challenges NVIDIA in the AI accelerator market. With its Instinct MI300 series accelerators and CDNA 3 architecture, it successfully enters the dominant NVIDIA AI chip market, providing a secondary supply source for customers. In 2024, revenue reached $22.9 billion, with data center business growing 27% annually.

In Q2 2025, revenue increased 18% year-over-year, with MI300X accelerators adopted, leading to multiple-fold growth in AI-related revenue. As AI workloads diversify, customer demand for alternatives grows. Leveraging its CPU+GPU integration advantages, AMD is gradually expanding its market share. Foreign target prices are mostly above $200.

Microsoft (MSFT): The Platform Leader in Enterprise AI Transformation

Microsoft builds an ecosystem advantage through comprehensive cloud-to-application AI solutions. With exclusive collaboration with OpenAI, Azure AI platform, and Copilot enterprise assistant integration, it successfully embeds AI into global enterprise workflows.

In FY2024, revenue reached $211.2 billion, with Azure and cloud services growing 28%, and AI services contributing over half of that growth. In Q1 FY2025, intelligent cloud revenue first surpassed $30 billion. As Copilot is deeply integrated into Windows, Office, and other products used by over a billion users worldwide, monetization will continue to accelerate. Many institutions see Microsoft as the most certain beneficiary of the enterprise AI wave, with target prices up to $550–$600.

Deep Reflection: Are AI-Related Stocks Worth Long-Term Holding?

AI technology will inevitably change human life and production modes like the internet, generating huge benefits. However, investment strategies need to consider phases.

Early Stage: Benefiting from device infrastructure needs, upstream stocks gain. But high growth and market hype are hard to sustain long-term. Referencing Cisco, the first internet equipment stock, which hit a high of $82 during the 2000 bubble, then fell over 90% to $8.12. After 20 years of good management, the stock still hasn’t returned to the high. Such stocks are suitable for phased investments.

Downstream Stage: Downstream companies fall into two categories—those directly using AI technology and those improving operations via AI. The market generally considers these companies’ development relatively sustainable, but looking at the history of Microsoft, Yahoo (delisted), and Google, their stock prices also sharply declined at market peaks and struggled to recover for years.

Even once top-tier internet giants like Yahoo couldn’t maintain their market position and were eventually overtaken by emerging players like Google. Theoretically, timely switching can allow long-term investment, but this is not easy for ordinary investors.

In phased investments, key factors to monitor include: the speed of AI technology development, monetization capability, and whether individual stocks’ profit growth slows down.

The Best Ways to Invest in AI-Related Stocks

Besides directly buying stocks, investors can also allocate through funds and ETFs:

Comparison of Investment Vehicles

It is recommended to combine dollar-cost averaging to buy individual stocks, funds, or ETFs, to average out costs. From Bridgewater’s holdings, although AI continues rapid growth, benefits are not necessarily concentrated in the same companies. Some stocks may have already priced in AI benefits; only continuous innovation can maximize performance.

Platform Selection: For Taiwan stocks, open accounts with Taiwanese brokers; for US stocks, use Taiwanese brokers via CLOB, overseas brokers, or CFD platforms. For short-term trading, CFD platforms are more advantageous, supporting long/short, no commission, and higher leverage.

Investment Outlook for AI-Related Stocks from 2025 to 2030

As large language models, generative AI, and multimodal AI advance rapidly, the demand for computing power, data centers, cloud platforms, and dedicated chips will continue to rise.

Short-term: Chip and hardware suppliers like NVIDIA, AMD, TSMC will remain the biggest beneficiaries.

Mid to Long-term: AI applications in healthcare, finance, manufacturing, autonomous driving, retail, and other industries will gradually materialize into actual revenue, driving overall growth of AI-related stocks.

On the capital side, although AI remains a hot topic, stock prices are inevitably influenced by macroeconomic factors. If the Federal Reserve and other central banks adopt loose monetary policies, it will benefit high-valuation tech stocks; if not, valuations may be compressed. Additionally, AI stocks are sensitive to news, prone to short-term volatility. When funds flow into new energy or other themes, shocks may occur. Therefore, short-term fluctuations are likely, but the long-term trend remains upward.

Policy and Regulation: Governments regard AI as a strategic industry, likely increasing subsidies and infrastructure investments, providing positive support. However, issues like data privacy, algorithm bias, and copyright may lead to stricter regulations. If regulations tighten, valuations and business models of some AI companies could face challenges.

Overall, AI-related stocks from 2025 to 2030 will feature “long-term bullish, short-term volatile.” Investors wishing to participate in AI growth should prioritize infrastructure providers like chipmakers and accelerators, or select companies with tangible applications such as cloud services, healthcare AI, and fintech. Diversified investment via AI-themed ETFs can also effectively reduce individual stock risks.

For ordinary investors, a more prudent strategy is long-term allocation with phased entry, avoiding chasing highs in the short term to reduce market impact.

Risks to Watch When Investing in AI-Related Stocks

When allocating AI-related stocks, be sure to be aware of the following risks:

Industry Uncertainty: Although AI has existed for decades, it only recently became mainstream. Rapid changes mean even professional investors find it hard to keep pace. This implies that buying into a company can easily lead to sharp stock price fluctuations driven by hype.

Unproven Companies: Many emerging AI firms lack a long track record and operational foundation. Compared to stable companies with proven history, their operational risks are much higher.

Potential Risks of AI Technology: Scientific leaders have warned of potential dangers of AI. As the field expands, public opinion, regulations, and other factors may change in unexpected ways, affecting AI stocks’ performance.

Considering these factors, participation in AI stock investments should be rational, with proper risk management and asset allocation.