2025 AI Stock Investment Opportunities Analysis | Which AI Concept Stocks Are Worth Investing In?

Why Have AI Concept Stocks Become an Investment Focus?

Since ChatGPT caused a shockwave in the industry at the end of 2022, the stock prices of listed companies related to artificial intelligence have experienced dramatic surges, with many companies’ stock prices doubling even before significant profit growth. How long will this AI wave last? How should investors position themselves to seize this opportunity?

The Fundamental Definition of AI Concept Stocks

AI concept stocks refer to publicly listed companies whose main businesses are highly related to artificial intelligence technology. These companies cover multiple segments of the AI industry chain: chip manufacturers, server suppliers, cloud platforms, AI software services, and more. Simply put, investing in AI concept stocks is equivalent to investing in the infrastructure and application layers that support the entire AI ecosystem.

Artificial intelligence itself refers to technologies that enable computers or machines to perform tasks similar to human intelligence, including knowledge learning, logical reasoning, complex problem solving, natural language processing, content generation, and more. Everyday interactions with Siri, ChatGPT, autonomous driving, and others fall within AI applications.

2025 AI Industry Investment Status and Market Scale

Market Size and Growth Expectations

According to the latest analysis by IDC, global enterprise spending on AI solutions and technologies is projected to reach $307 billion in 2025. Looking ahead to 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 in 2028 will account for over 75%, becoming the core hardware foundation supporting AI technology.

This data clearly shows that the AI industry still has enormous growth potential, and investment demand at the infrastructure level is becoming a primary driving force.

Large Institutional Capital Movements

As the prospects of AI applications are increasingly validated by the market, institutional investors and hedge funds are ramping up their holdings in related stocks. For example, in Q2 2025, Bridgewater Associates significantly increased holdings in NVIDIA, Google (Alphabet), Microsoft, and other key AI companies, reflecting professional investors’ optimism about core AI ecosystem components such as computing power, chips, and cloud computing.

In addition to direct stock investments, many investors are also choosing to deploy through thematic funds or ETFs, covering multiple layers such as applications, infrastructure, cloud, and big data in one go. According to Morningstar, by the end of Q1 2025, global AI and big data fund assets exceeded $30 billion, indicating strong retail investor interest in this field.

In-Depth Analysis of Leading US AI Companies

1. NVIDIA (NVDA)

As the global leader in AI computing, NVIDIA’s GPUs and CUDA software platform have become industry standards for training and deploying large language models. Through a complete ecosystem from chips to software, NVIDIA has successfully dominated the AI infrastructure market.

In 2024, revenue reached $60.9 billion, with an increase of over 120% year-over-year, demonstrating its growth potential amid exploding AI demand. In Q2 2025, revenue hit a new high of about $28 billion, with net profit increasing over 200%. This growth is mainly driven by strong demand from cloud giants and large enterprises for Blackwell architecture GPUs (such as B200, GB200).

Market analysts generally believe that as AI applications expand from training to inference and further penetrate enterprise and edge computing scenarios, the demand for high-performance computing solutions will maintain exponential growth. Many institutions have raised target prices and given buy ratings, reflecting high expectations for its long-term profit momentum.

2. Broadcom (AVGO)

Broadcom plays an indispensable role in the AI era, with customized ASIC chips, network switches, and optical communication chips becoming key parts of the AI data center supply chain.

In fiscal year 2024 (ending Nov 2024), revenue reached $31.9 billion, with AI-related product revenue rapidly increasing to 25%. Entering 2025, Broadcom’s AI deployment has shown remarkable results, with Q2 revenue up 19% year-over-year, benefiting from cloud service providers accelerating AI data center construction and increasing demand for products like Jericho3-AI chips and Tomahawk5 switches.

As AI model sizes continue to grow, the demand for high-performance network connectivity and customized chips will surge, and Broadcom, as a leader in related technologies, will directly benefit. Foreign investors generally hold a positive outlook on its AI product line, with target prices mostly above $2,000.

3. AMD (Advanced Micro Devices)

AMD plays a vital role in high-performance computing innovation, with its Instinct MI300 series accelerators and CDNA 3 architecture successfully entering the AI chip market dominated by NVIDIA, providing key alternatives for customers.

In 2024, revenue reached $22.9 billion, with data center business up 27% annually. In 2025, AMD’s AI push becomes even more aggressive, with Q2 revenue up 18% year-over-year. Benefiting from the adoption of MI300X accelerators by mainstream cloud providers and the upcoming launch of MI350 series in the second half, AI-related revenue is expected to multiply.

As AI workloads diversify, customer demand for alternative solutions is increasing. AMD leverages its CPU-GPU integration advantages and open ecosystem strategy to expand its share in AI training and inference markets. Many foreign institutions are optimistic about its growth potential, with target prices mostly above $200.

4. Microsoft (MSFT)

Microsoft has built a strong enterprise AI transformation platform through exclusive collaboration with OpenAI, Azure AI cloud platform, and Copilot enterprise assistants. The company seamlessly integrates generative AI into the workflows of global enterprises, becoming one of the most certain beneficiaries of the “enterprise AI popularization” wave.

In FY2024, revenue reached $211.2 billion, with Azure and cloud services growing 28%, and AI services contributing over half of the growth. In FY2025, large-scale deployment of Copilot for Microsoft 365 by enterprise clients and exponential growth in Azure OpenAI usage have driven cloud business revenue to surpass $30 billion for the first time.

As Microsoft deeply integrates Copilot features into Windows, Office, Teams, and other products used by over 1 billion users, its monetization capability will continue to be unleashed. Many institutions see Microsoft as the most certain player in enterprise AI adoption, with target prices ranging from $550 to $600.

5. Google (GOOGL)

Google’s AI layout spans search, advertising, cloud, and hardware, with Gemini large language models and TPU dedicated chips becoming competitive advantages. The company’s integrated AI strategy has established an important position in enterprise AI applications.

Investment Opportunities in Taiwan AI Concept Stocks

1. Quanta Computer (2382)

Quanta Computer is one of the world’s largest notebook OEMs and has actively transitioned into the AI server market in recent years. Its subsidiary, Quanta Cloud Technology (QCT), specializes in servers and cloud solutions, successfully entering the supply chain for US data centers and AI servers, with major clients including NVIDIA and international cloud providers.

In 2024, revenue reached NT$1.3 trillion, with the proportion of AI servers continuously increasing and gross margin significantly improving. In 2025, driven by a surge in AI server shipments, Quanta’s performance remains strong, with Q2 revenue surpassing NT$300 billion, up over 20% year-over-year, reaching a new high for the same period. Analysts are optimistic that Quanta will maintain long-term growth driven by AI and cloud trends, with foreign institutional target prices averaging NT$350–NT$370.

2. Himax Technologies (3661)

Himax specializes in ASIC custom chip design services, serving clients including US cloud giants and leading companies in high-performance computing and AI. In 2024, revenue reached NT$68.2 billion, up over 50% annually, demonstrating strong growth driven by AI demand.

In Q2 2025, Himax’s quarterly revenue exceeded NT$20 billion, doubling compared to the same period last year, with gross margin and net margin continuing to improve. Benefiting from large AI client projects entering mass production, the company has received new orders for next-generation AI accelerators and data center solutions. Foreign institutional target prices range from NT$2,200 to NT$2,400, still with upside potential from current stock levels.

3. Delta Electronics (2308)

Delta Electronics is a global leader in power management and power solutions, actively entering the AI server supply chain by providing high-efficiency power supplies, cooling, and cabinet solutions. It is a representative AI concept stock in Taiwan.

In 2024, annual revenue is about NT$420 billion, with the performance from data centers and AI applications steadily increasing. In Q2 2025, revenue is about NT$110 billion, up over 15% year-over-year, supported by expanding demand for AI servers and data center infrastructure, with high gross margins maintained.

4. MediaTek (2454)

MediaTek is among the top ten fabless semiconductor design companies globally. With the rise of generative AI and edge computing, MediaTek is actively advancing its AI chip deployment. 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, revenue reached NT$490 billion, benefiting from increased AI chip shipments, with gross margins improving quarter by quarter. In Q2 2025, revenue is about NT$120 billion, up approximately 20% year-over-year, mainly driven by higher market share in high-end mobile chips and growing demand for AI smart devices. Analysts generally believe that MediaTek, leveraging mobile AI and automotive AI as two major growth engines, will become an important representative of Taiwan’s long-term AI concept stocks.

5. Sunlord (3324)

Sunlord is a leading Taiwanese provider of cooling solutions, focusing on high-performance liquid cooling modules. As AI server chips’ power consumption surpasses kilowatts, traditional air cooling has reached a bottleneck. Sunlord’s advanced liquid cooling technology has successfully positioned itself in the global AI server supply chain.

In 2024, revenue reached NT$24.5 billion, with an increase of over 30%. In 2025, Sunlord’s growth momentum accelerates further, supported by major cloud service providers adopting liquid cooling solutions. From Q2 onward, shipments of water-cooled modules for AI servers have surged. As new high-power AI accelerators enter the market, liquid cooling penetration will rapidly increase, and Sunlord, as a technology pioneer, will directly benefit. Foreign institutional target prices are mostly above NT$600.

Overview of Major AI Concept Stocks in Taiwan Stock Market

Data as of September 19, 2025, Source: Google Finance

Overview of Major US AI Concept Stocks

Prices as of September 19, 2025

Comparison of Investment Methods for AI Concept Stocks

Different types of investors can choose different investment approaches:

Direct Stock Investment: Concentrated risk but easy to buy and sell. Suitable for investors with in-depth understanding of individual companies’ fundamentals. Choosing leading companies like NVIDIA or TSMC can reduce risk.

Stock Funds: Managed by fund managers selecting a diversified portfolio of stocks. Risk is relatively lower but involves higher transaction costs and management fees. For example, First Financial’s global AI robot and automation industry fund and other thematic funds.

ETF Funds: Passively track indices, with the lowest transaction costs and management fees, offering good diversification. Products like Taishin Global AI ETF (00851) and Yuan Da Global AI ETF (00762) provide convenient ways for diversified investment.

Long-term Investment Value Assessment of AI Concept Stocks

Differences in Early and Mid-term Investment Strategies

AI development will inevitably change human life and production modes like the internet, generating huge benefits. However, in the early stages, due to infrastructure needs, upstream hardware companies will be the first to benefit, but high growth and market hype are unlikely to be sustained long-term.

Referring to Cisco Systems (CSCO), a pioneer in internet equipment: it hit a high of $82 during the 2000 dot-com bubble, but after the hype faded, it fell over 90% to $8.12. Despite 20 years of steady operation, the stock price has not returned to its high. This shows that chip and infrastructure stocks are suitable for phased investments.

Long-term Performance of Downstream Application Companies

Downstream companies generally fall into two categories: AI technology companies and those improving operations through AI. The market believes these companies have relatively sustainable development prospects, and their stock prices could benefit long-term. However, historical trends of Microsoft, Yahoo (delisted), and Google show that downstream stocks often decline sharply at market peaks and struggle to recover high valuations afterward.

Yahoo was once a leading internet company but was eventually overtaken by Google. Theoretically, timely switching targets allows long-term investment gains, but this is not easy for ordinary investors.

Key Monitoring Indicators for Phased Investment

When engaging in phased AI investments, pay attention to these key factors: the speed of AI technological development, the ability to monetize AI, and whether individual stock profit growth is slowing. Continuous monitoring of these indicators is essential to grasp the best buying and selling opportunities.

Risks and Precautions in AI Concept Stock Investment

Industry Development Uncertainty

Although AI technology has existed for decades, it only became mainstream recently. Rapid technological changes mean even seasoned investors find it hard to keep up. Buying stocks of certain companies may lead to sharp price fluctuations driven by hype.

Unproven New Companies Risks

While many major tech firms are involved in AI, some AI startups have little historical basis for investors to evaluate. Compared to mature companies with proven track records, these new firms carry higher operational risks.

Policy and Regulatory Changes

Governments worldwide view AI as a strategic industry and may increase subsidies or infrastructure investments. However, issues like data privacy, algorithm bias, copyright, and ethics could lead to stricter regulations. If regulations tighten, valuations and business models of some AI companies may face challenges.

Macroeconomic Factors

AI concept stocks are sensitive to news and can fluctuate significantly in the short term. Easing monetary policy by the Federal Reserve or other central banks can boost high-valuation tech stocks; higher interest rates may compress valuations. Additionally, other themes like renewable energy may cause capital to flow elsewhere.

AI Investment Outlook from 2025 to 2030

Overall, AI concept stocks will likely exhibit a “long-term bullish, short-term volatile” pattern over the next five years.

Immediate Beneficiaries

Due to ongoing demand for computing power, data centers, cloud platforms, and dedicated chips, NVIDIA, AMD, TSMC, and other chip and hardware suppliers will continue to benefit in the short term. Rapid advances in large language models, generative AI, and multi-modal AI will further boost demand for computing resources.

Medium to Long-term Growth Drivers

AI applications in healthcare, finance, manufacturing, autonomous vehicles, and retail will gradually materialize into tangible revenue for more enterprises, driving the growth of the entire AI concept stock sector.

Prudent Investment Strategies

For general investors, a more stable approach is long-term allocation with phased entry rather than chasing high prices in the short term. Those wishing to participate in AI growth should prioritize chipmakers, accelerated server providers, or companies with tangible applications. Using AI-themed ETFs for diversification can effectively reduce individual stock volatility and, combined with dollar-cost averaging, enhance long-term investment returns.