2025 AI Stock Investment Guide: A Complete Layout from Chips to Applications

The explosive popularity of generative AI is no longer news. Since the advent of ChatGPT, the AI-related industry chain has been fiercely pursued by the capital market, and the stock prices of companies involved in AI have soared — some even doubling or tripling in valuation before their performance has caught up.

The question is: Can you still invest in AI stocks in 2025? Which AI stocks are worth paying attention to?

What exactly are AI concept stocks?

First, it’s essential to understand a basic concept. AI (Artificial Intelligence) essentially means enabling machines to have thinking abilities similar to the human brain — learning new things, reasoning and judging based on existing information, solving complex problems, understanding and generating language. Everyday tools like Siri, ChatGPT, and autonomous driving all fall into this category.

AI concept stocks refer to listed companies whose business is closely linked to AI technology. They may specialize in AI chips, or be server suppliers, cloud platform providers, or software service providers. Essentially, investing in AI concept stocks means investing in the hardware infrastructure and ecological applications behind this AI technological wave.

What is happening in the AI market in 2025?

Data speaks volumes. According to the latest IDC report, global enterprise spending on AI solutions is expected to reach $307 billion in 2025. By 2028, this figure will 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 supporting AI technology implementation.

What does this mean? There is still huge growth potential in the hardware segment of the AI industry chain.

Not only is the market outlook optimistic, but institutional funds are also heavily increasing their positions. For example, Bridgewater Associates significantly increased holdings in Nvidia, Alphabet, Microsoft, and other key AI companies in its Q2 2025 report. Meanwhile, many investors are choosing to allocate AI industry exposure through thematic funds or ETFs. As of the end of Q1 2025, the total assets of global AI and big data funds exceeded $30 billion.

Which AI concept stocks in Taiwan stock market are worth watching?

Quanta Computer (2382)

As one of the world’s largest notebook contract manufacturers, Quanta has recently shifted focus to AI servers with notable results. Its subsidiary, Quanta Cloud Technology (QCT), specializes in servers and cloud solutions, successfully entering large-scale US data centers. In 2024, Quanta’s revenue reached NT$1.3 trillion, with a continuous increase in AI server sales share. Entering 2025, its Q2 revenue surpassed NT$300 billion, up over 20% year-on-year, hitting a new high for the same period. Foreign investors generally see long-term growth potential, with a target price of NT$350-370.

Vanguard-KY (3661)

One of Taiwan’s most representative AI concept stocks, mainly providing ASIC custom chip design services. Its clients include US cloud giants and leading companies in high-performance computing and AI fields. In 2024, revenue was NT$68.2 billion, up over 50% annually. In Q2 2025, quarterly revenue exceeded NT$20 billion, doubling from last year, with gross margin and net margin continuing to improve. Benefiting from major AI clients entering mass production, foreign investors’ target price is NT$2200-2400.

Delta Electronics (2308)

As a global leader in power management and power solutions, Delta has recently entered the AI server supply chain, mainly providing high-efficiency power supplies, cooling, and cabinet solutions. In 2024, revenue reached NT$420 billion, with an increasing proportion from data centers and AI applications. In Q2 2025, revenue was NT$110 billion, up over 15% year-on-year, with gross margins maintained at a high level.

MediaTek (2454)

One of the top ten fabless semiconductor design companies worldwide, with core businesses including mobile chips, smart home, and automotive electronics. With the rise of generative AI and edge computing, MediaTek is actively deploying AI chips. Its Dimensity series already integrates enhanced AI computing units, and it collaborates with Nvidia to develop automotive and edge AI solutions. In 2024, revenue was NT$490 billion, and in Q2 2025, revenue was NT$120 billion, up about 20% annually. Foreign investors’ target price is NT$1300-1400.

Sunon (3324)

A leading Taiwanese manufacturer of cooling solutions, focusing on high-performance water-cooled cooling modules. As AI server chip power consumption continues to break through limits, traditional air cooling has become a bottleneck. Sunon’s liquid cooling technology is becoming a key position. In 2024, revenue was NT$24.5 billion, up over 30% annually. Driven by major cloud service providers accelerating the adoption of liquid cooling solutions, Q2 shipments of water-cooled modules for AI servers surged. As new higher-power AI chips are introduced, liquid cooling penetration will rapidly increase, with many foreign targets above NT$600.

How to view leading AI stocks in the US stock market?

Nvidia (NVDA)

The undisputed leader in global AI computing. Its GPUs and CUDA software platform have become industry standards for training and deploying large AI models. In 2024, revenue was $60.9 billion, up over 120% year-on-year. In Q2 2025, revenue was approximately $28 billion, with net profit increasing over 200%. The main drivers are strong demand from cloud service providers and enterprises for Blackwell architecture GPUs. Analysts expect that as AI applications shift from training to inference, the demand for Nvidia’s high-performance computing solutions will continue to grow exponentially.

Broadcom (AVGO)

A leader in semiconductor and infrastructure software solutions, playing a key role in AI chips and network connectivity. In fiscal 2024, revenue was $31.9 billion, with AI-related product revenue rapidly rising to 25%. In Q2 2025, revenue increased 19% year-on-year, benefiting from cloud providers accelerating AI data center deployments and increasing demand for customized chips and optical communication chips. Many foreign targets are above $2000.

AMD (Advanced Micro Devices)

An innovator in high-performance computing, challenging Nvidia in the AI accelerator market. Its Instinct MI300 series accelerators have successfully entered the market dominated by Nvidia, providing enterprises with a secondary supply source. In 2024, revenue was $22.9 billion, with data center business up 27% annually. In Q2 2025, revenue grew 18% year-on-year, boosted by the adoption of MI300X by major cloud providers, with AI-related revenue multiplying. Many foreign targets are above $200.

Microsoft (MSFT)

A leading platform for enterprise AI transformation, seamlessly integrating generative AI into global enterprise workflows through exclusive cooperation with OpenAI and Azure AI platform advantages. In fiscal 2024, revenue was $211.2 billion, with Azure and cloud services growing 28%, and AI services contributing over half of the growth. In Q1 2025, intelligent cloud revenue first exceeded $30 billion, driven by the large-scale deployment of Copilot for Microsoft 365 and exponential growth in Azure OpenAI usage. Many institutions see Microsoft as the most certain beneficiary of the “enterprise AI popularization” wave, with a target price range of $550-600.

Google (GOOGL)

A tech giant with deep layout in search, cloud computing, and AI. Leveraging Alphabet’s ecosystem advantages and AI technology accumulation, it holds an important position in the enterprise AI application market. Market cap is $3.05 trillion, with a YTD increase of 32.5% in 2024.

Long-term investment or short-term trading?

This is a key question. Looking at history, Cisco’s first internet device stock peaked at $82 during the 2000 dot-com bubble, then fell over 90%. After 20 years of sustained good performance, its stock price never returned to the high. What does this tell us? Upstream infrastructure stocks are suitable for phased investment rather than long-term hold.

For downstream companies like Microsoft and Google, history also shows that market peaks are followed by sharp declines, and long-term growth back to previous highs is difficult. Yahoo was once a leading internet company, but was eventually overtaken by emerging giants like Google. Theoretically, timely rotation can enable long-term investment, but this is not easy for ordinary investors.

In the short term, chip and hardware suppliers will still be the biggest beneficiaries in 2025-2026. In the medium to long term, as AI applications in healthcare, finance, manufacturing, autonomous driving, and other industries gradually land, they will translate into actual revenue for enterprises.

Investors should closely monitor:

• Whether the development speed of AI technology slows down
• Whether companies can monetize AI technology
• Whether the profit growth rate of individual stocks begins to decline

These are important signals for adjusting positions.

How to efficiently deploy AI stocks?

Besides directly buying stocks, you can participate through the following methods:

Individual stocks — Choose stocks yourself, with concentrated risk but easy to trade and low transaction costs. Consider Taiwan’s leading stocks like TSMC, MediaTek, or US giants like Nvidia.

Stock funds — Managed portfolios selected by fund managers, with relatively diversified risk but higher transaction costs and management fees. For example, First Financial Global AI Robotics and Automation Industry Fund.

ETFs — Passive index tracking, low trading costs and management fees, diversified risk. Examples include Taishin Global AI ETF, Yuan Quan Global AI ETF.

Recommended strategy: Combine dollar-cost averaging to buy in, smoothing out costs. As seen from Bridgewater’s holdings changes, although AI is rapidly developing, the positive news is not always concentrated in the same companies. Some stocks have already fully priced in AI benefits. Only by staying up-to-date can you maximize investment returns.

Risks that cannot be ignored

Industry uncertainty — While AI has existed for decades, it has only become mainstream in recent years. Rapid technological change makes it difficult even for knowledgeable investors to keep pace, risking large stock price swings driven by hype.

Unproven companies — Many AI startups have little history or foundation to reference, with much higher operational risks than established tech giants.

Policy and regulatory changes — Governments view AI as a strategic industry and may increase investment subsidies, but issues like data privacy, algorithm bias, and copyright could lead to stricter regulations, directly impacting valuations and business models of some AI companies.

Macroeconomic environment — Interest rate policies directly influence high-valuation tech stocks. Loose monetary policy is bullish, while high interest rates may compress valuations. Funds may also shift to new themes like renewable energy.

Overall judgment: Between 2025 and 2030, AI concept stocks will show a “long-term bullish, short-term volatile” pattern. To participate in AI growth dividends, focus first on infrastructure providers like chipmakers and server accelerators, or companies with tangible applications such as cloud services, healthcare AI, and fintech. Diversifying through AI-themed ETFs can also effectively reduce the risk of individual stock fluctuations.

For ordinary investors, a more prudent approach is long-term allocation and phased entry rather than chasing highs in the short term, to reduce the impact of market volatility.