2025 AI Stock Investment Landscape: Who Will Be the Next Tech Giant? Profit Opportunities from TSMC to NVIDIA

Artificial intelligence is no longer a distant future but a present-day reality. Since the debut of ChatGPT, AI-related stocks have become the most dazzling stars in the capital markets, with gains often multiplying several times. But the question is: in this AI wave, which stocks are truly worth betting on? This article will deeply analyze the AI industry chain and highlight the most promising investment targets in Taiwan and the US.

Why Are AI Concept Stocks So Hot? Insights from Market Data

The explosion of generative AI is no coincidence but the result of a combined effort of computing power, chips, and applications. According to the latest IDC forecast, global enterprise spending on AI solutions will reach $307 billion in 2025, surpassing $632 billion by 2028, with a compound annual growth rate of about 29%.

What does this mean? It indicates that capital is flooding into the AI-related industry. Bridgewater Associates significantly increased holdings of key AI companies like Nvidia, Alphabet, and Microsoft in its Q2 2025 portfolio adjustments. Similarly, the assets under management of AI-themed funds and ETFs have exceeded $30 billion, with institutional investors voting with real money for the AI industry.

Taiwan AI Stocks: The Glamorous Transformation of Manufacturing

Quanta Computer: From OEM Manufacturer to AI Server Powerhouse

When mentioning Quanta (2382), many still think of its notebook OEM business. But by 2024, Quanta’s revenue structure has quietly shifted—AI server business continues to rise. Its subsidiary, Quanta Cloud Technology (QCT), has become a core supplier for global hyperscale data centers, serving clients including NVIDIA and international cloud giants.

In 2024, Quanta’s annual revenue reached NT$1.3 trillion, and momentum is even stronger in 2025. In Q2, revenue first broke NT$300 billion, up over 20% year-on-year. Foreign institutional investors generally raised their target prices to NT$350-370, reflecting market optimism about its AI transformation.

Realtek Semiconductor: Hidden Profitability in Specialized AI Fields

Realtek Semiconductor (3661) is Taiwan’s most pure AI concept stock, mainly providing ASIC design services—simply put, designing customized AI chips for US cloud giants. In 2024, full-year revenue was NT$68.2 billion, up over 50% year-on-year.

In Q2 2025, Realtek’s quarterly revenue exceeded NT$20 billion, doubling from the same period last year. Gross margin and net profit margin both improved, benefiting from large AI customer projects entering mass production and new generation AI accelerators receiving orders. Foreign analysts have raised their target prices to NT$2,200-2,400, optimistic about its long-term growth momentum.

Delta Electronics: Infrastructure Provider for the AI Era

Delta Electronics (2308) controls the “key” components of AI servers—power supplies, cooling, and rack solutions. As AI chips’ power consumption continues to skyrocket, the market is revaluing companies like Delta.

In 2024, Delta’s revenue was about NT$420 billion, with data centers and AI business steadily increasing their share. In Q2 2025, revenue was around NT$110 billion, up 15% year-on-year. With accelerated investment in AI infrastructure, Delta, as a key supplier, has ample long-term growth potential.

MediaTek: Dual Engines of Mobile AI and Edge Computing

MediaTek (2454), though famous for mobile chips, also has a noteworthy AI layout. Its Dimensity series mobile platforms feature enhanced AI computing units, and collaborations with NVIDIA on automotive and edge AI solutions are expanding its high-end AI chip market.

In 2024, revenue reached NT$490 billion, with gross margins improving quarter by quarter. In Q2 2025, revenue was NT$120 billion, up 20% year-on-year, driven by demand for high-end smartphones and AI smart devices. Foreign investors generally favor its dual-drive strategy of mobile AI and automotive AI.

Sunon: Underestimated Leader in Cooling Solutions

While everyone talks about GPUs, Sunon (3324) quietly occupies the high ground in AI server cooling. As AI chips’ power exceeds kilowatts, liquid cooling has become a necessity, and Sunon’s water-cooling modules are preferred by major cloud service providers.

In 2024, revenue was NT$24.5 billion, up over 30% annually. In 2025, with rising penetration of liquid cooling and new high-power AI chips, Sunon’s growth trajectory remains upward. Many foreign analysts set target prices above NT$600.

US AI Giants: Hotspots for Global Capital Allocation

NVIDIA: Absolute Dominator of AI Computing

NVIDIA (NVDA) is the biggest beneficiary of this AI wave. Its GPUs and CUDA software platform have become industry standards, with almost no alternatives for training and deploying large AI models. In 2024, revenue hit $60.9 billion, up over 120% year-on-year.

In Q2 2025, revenue again reached a record $28 billion, with net profit increasing over 200%. The demand for Blackwell architecture GPUs (B200, GB200) is booming, driving data center business to new heights. As AI shifts from training to inference, the demand for high-performance computing solutions from NVIDIA is expected to grow exponentially. Institutional analysts widely raised target prices and issued “buy” ratings.

Broadcom: Key Hub for AI Network Connectivity

Broadcom (AVGO) plays a vital role in the AI data center supply chain, with customized ASIC chips, network switches, and optical communication chips as its core products. In FY2024, revenue was $31.9 billion, with AI-related products rapidly increasing to 25%.

In Q2 2025, revenue grew 19% year-on-year, supported by cloud providers accelerating AI data center deployments. Demand for Jericho3-AI chips and Tomahawk5 switches continues to rise. Foreign analysts are optimistic about its AI product line prospects, with target prices above $2,000.

AMD: The Challenger’s Counterattack

Although AMD started later than NVIDIA in the GPU market, its Instinct MI300 series accelerators are gradually gaining ground. In 2024, revenue was $22.9 billion, with data center sales up 27%.

In Q2 2025, revenue increased 18% year-on-year, with MI300X accelerators adopted by major cloud providers, and MI350 series upcoming. As AI workloads diversify, customer demand for alternatives is growing, and AMD’s CPU+GPU integration and open ecosystem strategies are expanding market share. Many foreign analysts set target prices above $200.

Microsoft: Platform Leader in Enterprise AI Transformation

Microsoft (MSFT), through exclusive partnership with OpenAI, Azure AI platform, and Copilot enterprise assistants, has secured a leading position in enterprise AI applications. In FY2024, revenue was $211.2 billion, with Azure and cloud services growing 28%.

In Q1 FY2025, intelligent cloud revenue first exceeded $30 billion. Deployment of Copilot for Microsoft 365 accelerates, and Azure OpenAI usage is growing exponentially. Microsoft deeply integrates Copilot into Windows, Office, and Teams, serving over 1 billion users worldwide, with monetization capabilities continuously unleashed. Many institutions see it as the most certain beneficiary of the “enterprise AI popularization” wave, with target prices reaching $550-600.

Google: The AI Transformation of the Search Empire

Google (GOOGL), though slightly later in generative AI, benefits from its search advertising empire and vast user base, providing unique advantages for AI monetization. Its TPU (Tensor Processing Unit) chips are also making strides in AI inference. As search engine AI integration advances and ad systems optimize, long-term revenue growth remains strong.

Investment Equation for AI Stocks: How to Deploy Efficiently?

Comparing Three Investment Tools

Direct Stock Purchase offers maximum flexibility but concentrates risk. Suitable for investors with in-depth research on individual companies, low transaction costs but requires self-assessment of stock selection risks.

Stock Funds balance returns and risks. Managed by fund managers selecting diversified stocks, but management fees are higher. Examples include First Gold Global AI Robot and Automation Fund.

ETFs Tracking Indexes have the lowest costs and best diversification. Products like Taishin Global AI ETF (00851) and Yuan Da Global AI ETF (00762) allow investors to deploy AI applications, infrastructure, and cloud segments in one go.

Dollar-Cost Averaging Strategy: Time for Space

Rather than betting all at once, adopting regular fixed investments can average costs and avoid buying at high points or being trapped at lows. As seen from Bridgewater’s holdings, despite rapid AI development, positive news isn’t always concentrated in the same companies—some stocks may already reflect the good news, so continuous adjustment maximizes performance.

Pitfalls and Long-term Outlook of AI Concept Stocks

Will History Repeat? Lessons from the Internet Bubble

Back in the day, Cisco Systems (CSCO) was the first internet equipment stock, reaching $82 in 2000. After the bubble burst, it fell over 90% to $8.12. Even after 20 years of steady operation, its stock price has not returned to its peak.

Downstream companies tell similar stories. Yahoo was once a top internet leader but was overtaken by Google; Microsoft, though still around today, saw its stock plummet at major market peaks and struggled to recover for years. Theoretically, timely switching investments can bring long-term benefits, but for ordinary investors, it’s easier said than done.

The 2025 AI Stock Outlook: Opportunities and Risks Coexist

Short-term focus: Chip and hardware suppliers (NVIDIA, AMD, TSMC) remain the biggest beneficiaries. As computing power demand continues to rise, the share of spending on servers and custom chips is expected to exceed 75% by 2028.

Medium to long-term variables: AI applications in healthcare, finance, manufacturing, autonomous vehicles, and other industries will gradually materialize into actual corporate revenue, expanding the growth ceiling of the entire AI concept stock sector.

Macro risks: Federal Reserve and other central banks’ interest rate policies will directly impact high-valuation tech stocks. Loose monetary environments favor AI stocks, while high interest rates compress valuations. Additionally, issues like data privacy, algorithm bias, and copyright regulations may pose challenges to some AI companies.

How Should Investors Respond?

For general investors, a more prudent strategy is:

1. Long-term allocation, dollar-cost averaging. Avoid chasing highs; use time to gain space.
2. Focus on infrastructure providers. Chipmakers, servers, and underlying components have more certain demand.
3. Moderate diversification. Use AI-themed ETFs to reduce individual stock volatility.
4. Regularly review holdings. AI industry evolves rapidly; continuous adjustment is necessary.

Overall, from 2025 to 2030, the investment landscape for AI concept stocks will feature “long-term bullishness with short-term volatility.” The key is to recognize that this is not a short-term frenzy but a long-term industry upgrade—cautious investors will ultimately reap the rewards.