AI Industry Chain Investment Panorama: Who Will Be the Favorite of Capital in 2025?

Since the wave triggered by the advent of ChatGPT in 2022, industry restructuring around artificial intelligence has become the most lucrative narrative in the capital markets. However, not all companies labeled with AI are worth long-term attention—where are the true investment opportunities hidden within the industry chain? How do Taiwan and US AI leading stocks differentiate? This article will analyze industry layers to help you find the genuine growth drivers.

The AI Wave Reshaping Capital Landscape

AI (artificial intelligence) has evolved from a laboratory concept to a real force transforming the global economy. From voice assistants, financial forecasting, medical diagnostics to autonomous driving perception systems, AI is penetrating every corner of modern life. This shift is driving companies to accelerate AI R&D budgets, with market expectations climbing steadily.

According to the latest IDC research, global enterprise investments in AI solutions and technologies are projected to reach $307 billion by 2025. By 2028, total spending—including AI applications, infrastructure, and related services—will surpass $632 billion, with a CAGR of about 29%. Notably, spending on accelerated servers is expected to account for over 75% by 2028, becoming the core infrastructure supporting AI commercialization.

This data indicates that upstream infrastructure suppliers in the AI industry chain will be the first beneficiaries. The movements of institutional investors tell the story—Bridgewater Fund significantly increased holdings in key AI players like NVIDIA, Alphabet, and Microsoft in Q2 2025, positioning capital at the three core nodes of computing power, chips, and cloud computing.

The Three Layers of AI Concept Stocks Investment Logic

AI concept stocks essentially refer to listed companies whose business is closely related to artificial intelligence technology. They may be AI chip designers, server suppliers, cloud platform operators, or AI software service providers. Based on their position in the industry chain, AI investment opportunities can be divided into three layers:

Layer 1: Basic Hardware Layer (Chips, Computing Devices)
This is the most directly benefited segment of the AI wave. NVIDIA’s GPUs, TSMC’s advanced processes, AMD’s accelerators, and Broadcom’s customized ASIC chips all belong here. Market data shows that companies in this layer currently enjoy the highest valuation premiums and growth expectations.

Layer 2: Infrastructure Layer (Servers, Cooling, Power Supplies)
Companies like Quanta, Unigroup-KY, Delta Electronics, and DFI are mainly clustered here. These firms provide complete system solutions for AI data centers, with strong growth momentum.

Layer 3: Application Layer (Software, Services, End-User Applications)
Microsoft, Google, and others monetize through cloud platforms and AI application tools. Compared to hardware, the application layer offers more sustainability but also carries higher valuation volatility risks.

US AI Leading Stocks: The Main Players in the Computing Power War

NVIDIA (NVDA): Absolute Technology Monopoly

NVIDIA is the undisputed leader in global AI computing. Its GPU and CUDA software platform have become industry standards for training and deploying large AI models, forming a complete ecosystem from chips, systems to software.

Performance data is impressive: 2024 revenue reached $60.9 billion, up over 120% YoY. In Q2 2025, revenue hit a new high of $28 billion, with net profit increasing over 200% YoY. The main drivers are strong demand from cloud service providers and large enterprises for Blackwell architecture GPUs. Analysts generally expect that as AI applications expand from training to inference and edge computing, demand for NVIDIA’s high-performance computing solutions will continue to grow exponentially.

Multiple institutions have raised target prices and assigned buy ratings, reflecting high market expectations for its long-term profit potential. However, it’s worth noting that NVIDIA’s current valuation is quite full, and short-term high-level fluctuations are inevitable risks.

Broadcom (AVGO): The Hidden Champion in Network Connectivity

Broadcom plays a key role in AI chips and network connectivity. As demand for AI servers explodes, Broadcom leverages its customized ASIC chips, network switches, and optical communication chips to secure a position 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% YoY, benefiting from cloud providers accelerating AI data center deployments, with demand for Jericho3-AI chips and Tomahawk5 switches continuing to rise. Foreign reports are generally optimistic about its AI product line growth potential, with target prices above $2,000.

AMD: The Challenger in Secondary Supply

AMD plays an important role in the AI accelerator market. Its Instinct MI300 series accelerators and advanced CDNA 3 architecture provide cloud service providers with vital alternatives.

In 2024, revenue hit $22.9 billion, with data center business up 27% YoY. In Q2 2025, revenue increased 18% YoY, driven by adoption of MI300X accelerators by major cloud providers. As AI workloads diversify, customer demand for alternative solutions grows, and AMD’s CPU+GPU integration advantage is helping it expand market share. Target prices are mostly above $200.

Microsoft (MSFT): The Ecosystem Ruler in Enterprise AI Transformation

Microsoft is the leading platform for global enterprise AI transformation. Through exclusive collaboration with OpenAI, Azure AI cloud platform, and Copilot enterprise assistant integration, it seamlessly embeds AI into global business workflows.

In FY2024, revenue reached $211.2 billion, with Azure and cloud services growing 28%, and AI contributing over half of the growth momentum. In FY2025, the deployment scale of Copilot for Microsoft 365 continues to expand, and Azure OpenAI usage is growing exponentially, with intelligent cloud revenue surpassing $30 billion for the first time.

As Copilot features are deeply integrated into Windows, Office, and Teams—used by over 1 billion users—its monetization potential will keep releasing. Many institutions see Microsoft as the most certain beneficiary in the enterprise AI proliferation wave, with target prices around $550–$600.

Google (GOOG): Promoter of an Open AI Ecosystem

As a global tech giant, Google also has deep AI expertise. Its large language models, cloud AI services, and hardware chips (TPU) form a complete ecosystem. In 2024, revenue growth remains steady, with AI services revenue steadily increasing, and future growth space still broad.

Taiwan AI Leading Stocks: The Manufacturing Hub of East Asia

Quanta (2382): The New Star in Server OEM

Quanta Computer started as a notebook OEM and has successfully transformed into a core player in the AI server market. Its subsidiary, Quanta Cloud Technology (QCT), specializes in servers and cloud solutions, penetrating major US data centers and AI server supply chains, with key clients including NVIDIA and international cloud providers.

In 2024, revenue reached NT$1.3 trillion, with AI server revenue continuously rising. In 2025, driven by a surge in AI server shipments, Q2 revenue broke NT$30 billion, up over 20% YoY, setting a new record 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 between NT$350 and NT$370, still room for upside.

Unigroup-KY (3661): The Rising Star in AI Chip Design

Unigroup-KY is one of Taiwan’s most representative AI stocks, focusing on ASIC custom chip design services, serving US cloud giants and high-performance computing leaders.

In 2024, full-year revenue reached NT$68.2 billion, with over 50% annual growth, demonstrating strong growth driven by AI demand. In Q2 2025, quarterly revenue exceeded NT$20 billion, doubling from the same period last year, with gross margin and net margin continuing to improve. Benefiting from large AI customer projects entering mass production and new AI accelerators and data center orders, its long-term growth momentum is promising.

As generative AI applications expand rapidly worldwide, market analysis generally remains optimistic about Unigroup’s long-term growth, with foreign institutional target prices between NT$2,200 and NT$2,400, still with upside potential.

Delta Electronics (2308): The Essential Power and Cooling Supplier

Delta Electronics is a global leader in power management and energy solutions. Recently, it has actively entered the AI server supply chain, mainly providing high-efficiency power supplies, cooling, and rack solutions.

In 2024, revenue was about NT$420 billion, with performance from data centers and AI-related applications steadily increasing. In Q2 2025, revenue was about NT$110 billion, up over 15% YoY, benefiting from expanding demand for AI servers and data center infrastructure, with high gross margins maintained. As an indispensable part of infrastructure, Delta offers a relatively stable growth path.

MediaTek (2454): The New Battlefield for Mobile and Edge AI

MediaTek is one of the top ten fabless semiconductor companies globally, with core businesses including mobile chips, smart home, automotive electronics, and networking chips. With the rise of generative AI and edge computing, MediaTek is actively advancing its AI chip layout. Its Dimensity series mobile platforms now include enhanced AI computing units, and it collaborates with NVIDIA to develop automotive and edge AI solutions.

In 2024, revenue reached NT$490 billion, with gross margins improving quarter by quarter. In Q2 2025, revenue is about NT$120 billion, up approximately 20% YoY, mainly driven by increased market share of high-end mobile chips and rising demand for AI smart devices. Analysts generally believe that MediaTek, leveraging both mobile AI and automotive AI momentum, will become an important long-term AI leader in Taiwan stocks, with foreign institutional target prices between NT$1,300 and NT$1,400.

Sunlord (3324): Pioneer in Liquid Cooling Solutions

Sunlord is a leading Taiwanese cooling solution provider, focusing on high-performance water cooling modules. As AI server chips’ power consumption surpasses the kilowatt threshold, traditional air cooling hits a bottleneck. Sunlord’s advanced liquid cooling technology successfully secures a position in the global AI server supply chain.

In 2024, revenue was NT$24.5 billion, up over 30%. In 2025, driven by major cloud providers accelerating liquid cooling adoption, shipments of water-cooled AI server modules surged, boosting revenue and gross profit margins. With new generation, higher-power AI accelerators emerging, liquid cooling penetration will rapidly increase. As a technology pioneer, Sunlord will directly benefit, and analysts are optimistic about its profitability, with target prices mostly above NT$600.

TSMC (2330): The Hidden Champion in Process Technology

Although TSMC does not directly manufacture AI chips, its advanced process technology underpins the entire AI industry chain. Global chip designers like NVIDIA, AMD, and Apple rely on TSMC’s 3nm and 2nm processes to realize AI chip designs.

In 2024, revenue reached NT$32.8 trillion, with high-performance computing (including AI chips) rapidly increasing its share to over 50%. In the first half of 2025, buoyed by strong AI orders from major chip companies, capacity utilization remained high, with revenue and gross margins growing in tandem. As the most upstream infrastructure provider in the AI industry chain, TSMC’s long-term growth prospects are equally bright.

Three Paths to Investing in AI Leading Stocks

Path 1: Direct Stock Holdings

Advantages include ease of buying and selling, low transaction costs, suitable for investors with thorough research capabilities. However, single-stock risks are concentrated, requiring close monitoring of company performance and industry dynamics.

Path 2: Theme-based Funds

Managed by professional fund managers selecting AI-related stocks, effectively balancing risk and return. According to Morningstar, as of Q1 2025, global assets in AI and big data funds exceeded $30 billion, indicating strong institutional interest.

Path 3: AI ETFs

Lowest transaction costs and highest diversification. Several AI-related ETFs are available in Taiwan, such as Taishin Global AI ETF (00851), Yuan Global AI ETF (00762), among others.

Long-term Investment Outlook and Risks of AI Leading Stocks

In the short term, with rapid advances in large language models, generative AI, and multimodal AI, demand for computing power, data centers, cloud platforms, and dedicated chips will continue to rise. NVIDIA, AMD, TSMC, and other chip and hardware suppliers will remain the biggest beneficiaries.

However, it’s crucial to recognize that phase growth and permanent investment returns are two different things. Historical experience shows that internet equipment stocks like Cisco Systems (CSCO) hit a high of $82 in 2000, then plummeted over 90% to $8.12 after the boom. Despite 20 years of steady operation, the stock price has yet to return to that high. Similarly, downstream application companies like Microsoft, Yahoo, and Google also peaked during major bull markets and then fell sharply, unable to regain previous highs for years.

This implies that even top-tier leading stocks cannot guarantee permanent market dominance. As AI technology evolves and competition intensifies, today’s leaders may be overtaken by emerging players. For average investors, a more prudent strategy includes:

1. Adopting long-term allocation rather than short-term chasing, using dollar-cost averaging to smooth entry points
2. Regularly reviewing holdings and timely rebalancing, rather than stubbornly holding onto a single stock
3. Diversifying across hardware and application companies to reduce sector-specific risks
4. Monitoring policy and regulatory changes—while governments support AI development, issues like data privacy, algorithm bias, and copyright may lead to tighter regulations

Conclusion

The investment landscape for AI leading stocks from 2025 to 2030 will feature a “long-term bullish, short-term volatile” pattern. Investors wishing to participate in AI growth should prioritize infrastructure suppliers like chipmakers and accelerated servers, or select companies with tangible applications. Diversifying through AI-themed ETFs can also effectively reduce individual stock volatility.

In essence, a rational AI leading stock investment strategy is not about predicting short-term rises and falls but understanding industry trends, choosing appropriate investment tools, and maintaining long-term discipline. Only then can investors share in the growth dividends of the AI era’s capital restructuring rather than being swayed by market sentiment.