2025 Tech Stocks Investment New Opportunities: How to Choose AI Concept Stocks? Complete Investment Guide

AI topics remain the focus of the capital markets. Since the advent of ChatGPT, the stock prices of technology stocks related to artificial intelligence have continued to climb, even as profit growth for some companies slows, their stock prices still hitting new highs. So, at this critical moment in 2025, how should investors filter out investment-worthy targets from the many AI concept stocks? This article will analyze in depth from multiple dimensions including market trends, core suppliers, and investment strategies.

How Artificial Intelligence is Defined and Applied

Artificial Intelligence (AI) refers to endowing computers or machines with cognitive abilities similar to humans, enabling knowledge learning, logical reasoning, complex problem solving, natural language understanding, and content generation. In daily applications, voice assistants, intelligent recommendation systems, and autonomous driving are all within the scope of AI.

AI concept stocks are listed companies whose business is closely related to artificial intelligence technology. These companies may be chip designers, server manufacturers, cloud platform providers, or AI software service providers. Investing in such stocks essentially means participating in the infrastructure construction and application ecosystem driven by the AI technology wave.

Global AI Market Size and Growth Drivers

AI has shifted from concept to reality, penetrating fields such as speech recognition, financial forecasting, medical diagnostics, autonomous driving, positioning, and decision models. Increasingly, companies are boosting R&D investment in AI, and market expectations for AI applications continue to rise.

According to the latest IDC data, global enterprise spending on AI solutions is projected to reach $307 billion in 2025. Looking further ahead, by 2028, total AI expenditure (including applications, infrastructure, and related services) is expected to exceed $632 billion, with a compound annual growth rate (CAGR) of 29%. Among these, spending on servers will account for over 75% by 2028, becoming the core hardware foundation supporting AI deployment. This indicates that the AI industry still has vast growth potential.

Institutional Investors’ Logic in Tech Stock Deployment

As AI concepts gain market validation, more institutional investors and hedge funds are increasing their holdings of AI-related stocks. For example, in Q2 2025, Bridgewater significantly increased its holdings in core AI companies like NVIDIA, Alphabet, and Microsoft. This reflects a general optimism among professional investors about AI application prospects, focusing on key nodes in the ecosystem such as computing power, chips, and cloud computing.

Besides direct stock selection, many investors also allocate through thematic funds or ETFs to cover AI 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.

Leading Taiwanese AI Technology Stocks

Quanta Computer (2382): Dark Horse in the Server Market

Quanta is one of the world’s largest notebook OEMs, actively transforming into the AI server field in recent years. Its subsidiary, Quanta Cloud Technology (QCT), specializes in servers and cloud solutions, successfully entering the supply chain of large-scale data centers worldwide, with major clients including NVIDIA and international cloud giants.

In 2024, Quanta’s revenue reached NT$1.3 trillion, with the proportion of AI servers continuously increasing and gross margin significantly optimized. Entering 2025, driven by a substantial increase in AI server shipments, Q2 revenue broke NT$300 billion, up over 20% year-on-year, hitting a new high for the same period. Foreign institutional investors generally view its future growth momentum positively, with an average target price around NT$350–NT$370.

Silicon Motion (3661): Pioneer in Custom Chip Design

Silicon Motion is Taiwan’s most representative AI concept stock, mainly focusing on ASIC chip design services, serving US cloud giants and high-performance computing leaders. In 2024, full-year revenue reached NT$68.2 billion, with a growth rate over 50%, demonstrating strong demand driven by AI.

In Q2 2025, Silicon Motion’s quarterly revenue exceeded NT$20 billion, doubling compared to the same period last year, with continued increases in gross margin and net profit margin. As generative AI applications expand rapidly worldwide, market analysis generally agrees on its long-term growth potential, with an average foreign target price between NT$2,200 and NT$2,400.

Delta Electronics (2308): Green Pioneer in Power Management

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. In 2024, revenue was about NT$420 billion, with the contribution from data centers and AI applications steadily rising.

In Q2 2025, revenue was approximately NT$110 billion, up over 15% year-on-year, benefiting from expanding demand for AI servers and data center infrastructure. Gross margin remains high, reflecting its competitive advantage in the AI field.

MediaTek (2454): Driver of Mobile AI Chips

MediaTek is among the top ten fabless semiconductor companies globally. With the rise of edge computing and generative AI, it is actively advancing its AI chip deployment. Its Dimensity series mobile platforms have integrated enhanced AI computing units, and it collaborates with NVIDIA to develop automotive and edge AI solutions.

In 2024, revenue reached NT$490 billion, benefiting from increased AI chip shipments, with gross margin improving quarter by quarter. In Q2 2025, revenue was about NT$120 billion, up approximately 20% year-on-year, mainly due to higher market share in high-end mobile chips. Foreign investors generally view its mobile AI and automotive AI as two major growth drivers, with an average target price between NT$1,300 and NT$1,400.

VIA Technologies (3324): Key Player in Liquid Cooling

VIA Technologies is a leading Taiwanese cooling solution provider, focusing on high-performance liquid cooling modules. As AI server chips’ power consumption surpasses the kilowatt level, traditional air cooling reaches a bottleneck. VIA’s advanced liquid cooling technology successfully positions itself in the AI server supply chain.

In 2024, revenue was NT$24.5 billion, with an annual growth rate over 30%. In 2025, driven by cloud service providers accelerating the adoption of liquid cooling solutions, shipments of water-cooled AI servers will surge. Market expectations for new high-power AI chips will further boost liquid cooling penetration, and VIA, as a technology pioneer, will directly benefit. Many foreign institutions set target prices above NT$600.

Investment Opportunities in US Tech Giants

NVIDIA (NVDA): Absolute Leader in AI Computing

NVIDIA is the global leader in AI computing, with its GPU and CUDA software platform becoming industry standards for training and deploying large AI models. With the generative AI wave, NVIDIA has successfully dominated the AI infrastructure market through a complete ecosystem from chips to software.

In 2024, revenue reached $60.9 billion, with an increase of over 120%. In Q2 2025, revenue hit a new high of about $28 billion, with net profit growing over 200% year-on-year. The main driver is the strong demand for Blackwell architecture GPUs. As AI applications shift from training to inference and gradually penetrate enterprise scenarios, demand for NVIDIA’s high-performance computing solutions will continue to grow.

Broadcom (AVGO): Connector in AI Data Centers

Broadcom is a leading global semiconductor and infrastructure software provider, playing a key role in AI chips and network connectivity. Through 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 2025, Q2 revenue grew 19% year-on-year, benefiting from cloud providers accelerating AI data center deployments. Many foreign institutions are optimistic about its AI product line growth potential, with target prices above $2,000.

AMD (NASDAQ: AMD): Challenger in the AI Market

AMD plays an innovative role in high-performance computing, successfully entering the AI chip market with its Instinct MI300 series accelerators and advanced architectures, providing an alternative supply source for enterprises. In 2024, revenue was $22.9 billion, with data center business growing 27% annually.

In Q2 2025, revenue increased 18% year-on-year, boosted by adoption of MI300X accelerators, with AI-related revenue multiplying. As AI workloads diversify, customer demand for alternative solutions increases. AMD leverages its CPU+GPU integration advantages to gradually expand market share. Many foreign institutions set target prices above $200.

Microsoft (MSFT): Promoter of Enterprise AI Transformation

Microsoft is a leading platform for enterprise AI transformation, establishing advantages through comprehensive cloud-to-application AI solutions. Its exclusive partnership with OpenAI, along with Azure AI cloud platform and Copilot enterprise assistant integration, has successfully introduced AI technology into global enterprise workflows.

In FY2024, revenue reached $211.2 billion, with Azure and related cloud services growing 28%, and AI services contributing over half of the growth. In Q1 2025, intelligent cloud revenue first exceeded $30 billion. As Copilot features are deeply integrated into Windows, Office, and Teams, used by over 1 billion users worldwide, monetization potential will continue to be unleashed. Institutional investors see Microsoft as one of the most certain beneficiaries of the enterprise AI wave, with target prices ranging from $550 to $600.

Long-term Investment Value of AI Concept Stocks

AI technology will inevitably change human life and production modes like the internet did, which is beyond doubt. However, judging whether AI concept stocks are worth long-term holding requires analyzing different stages of the industry cycle.

Early-stage infrastructure stocks: short-term optimism, long-term caution

In the early development of AI, upstream chip and server manufacturers will benefit first. But rapid growth and market hype are hard to sustain long-term. Referencing Cisco Systems during the internet bubble, which hit a high of $82 in 2000, then collapsed over 90% to $8.12. After 20 years of continuous operation, the stock price still has not returned to the high. Such stocks are suitable for phased investment rather than indefinite holding.

Downstream application stocks: opportunities and risks coexist

Downstream companies can be divided into AI technology developers and enterprises using AI to improve operations. While the market considers these companies’ development relatively sustainable, historical experience shows it’s not always the case. The trajectories of Microsoft, the delisted Yahoo, and Google demonstrate that even top-tier companies can see their stock prices sharply decline at market peaks and struggle to recover for years. Yahoo was a leading internet company but was eventually overtaken by Google, illustrating that no company has eternal market dominance.

If investors can timely “rotate,” they can achieve long-term gains, but this is not easy for ordinary investors.

Investment Strategies and Tool Selection for AI Tech Stocks

Besides directly buying stocks, investors can also allocate through various methods:

Direct stock picking: Easy to buy/sell, low cost, but high risk from individual stock volatility; requires good stock selection skills.

Stock mutual funds: Managed by fund managers selecting a diversified portfolio to balance risk and return. Management fees are higher, but risk is reduced. The First Financial Global AI Robot and Automation Industry Fund is a representative product.

ETFs: Passive index tracking, low transaction costs, low management fees. Products like Taishin Global AI ETF (00851), Yuan Da Global AI ETF (00762) offer convenient AI industry allocation options.

Investment advice: Combining regular fixed investments in stocks, funds, or ETFs can average costs and reduce emotional trading risks. From institutional deployment, although AI is still rapidly developing, positive factors may be dispersed across different companies. Some stocks may already reflect AI benefits sufficiently; only continuous innovation can maximize performance.

For platform choices, investors in Taiwan can open accounts with local brokers; for US stocks, via Taiwanese brokers or overseas brokers. Short-term traders may consider margin contract platforms, which allow long and short trading, with no commission and higher leverage.

Investment Outlook for AI Concept Stocks from 2025 to 2030

In the next five years, the investment landscape for AI concept stocks will feature “long-term bullish, short-term volatility.” As large language models, generative AI, and multimodal AI advance rapidly, demand for computing power, data centers, cloud platforms, and dedicated chips will continue to rise. In the short term, chip and hardware suppliers like NVIDIA, AMD, and TSMC will remain the biggest beneficiaries.

In the medium to long term, AI applications in healthcare, finance, manufacturing, autonomous vehicles, and retail will gradually land in enterprises, translating into actual revenue and driving the growth momentum of the overall AI concept stocks.

From a capital perspective, although AI remains a focus, stock price movements will inevitably be affected by macroeconomic conditions. If the Federal Reserve and other central banks adopt loose monetary policies, it will benefit high-valuation tech stocks; if interest rates stay high, valuations may be compressed. Additionally, AI concept stocks react sensitively to news, prone to sharp fluctuations in a short period.

Policy and regulation will become key variables. Governments worldwide generally see AI as a strategic industry and may increase subsidies and infrastructure investments. However, issues like data privacy, algorithm bias, copyright, and ethics could lead to stricter regulations, challenging the valuation and business models of some AI companies.

Risks to Watch When Investing in AI Concept Stocks

When participating in AI investments, investors should be fully aware of the following risks:

Industry uncertainty: Although AI technology has existed for decades, it only entered mainstream application recently. Rapid changes and advancements make it difficult even for knowledgeable investors to keep pace. This can lead to hype around certain companies, causing large stock price swings.

Unproven companies: While major tech firms are involved in AI, some AI startups are relatively new and less stable. Compared to well-established companies, these carry higher operational risks.

Policy and public opinion risks: As AI expands and evolves, public sentiment, regulations, and other factors may change unexpectedly, affecting AI stocks’ performance.

Investors should adopt a long-term allocation and staggered entry strategy rather than chasing short-term highs, to effectively reduce market volatility risks.