2025 AI Concept Stock Investment Guide: From Infrastructure to Application Gold Rush Route

AI has shifted from a hype concept to a real capital flow. Since the launch of ChatGPT, the AI-related industry chain has been accelerating its evolution, and investors face an essential question: In this wave of AI wealth transfer, what should we invest in?

Where is the investment logic behind AI concept stocks?

According to the latest IDC data, global enterprise AI-related expenditures are expected to reach $307 billion by 2025, surpassing $632 billion by 2028, with a compound annual growth rate of about 29%. This is not a false prosperity but a genuine flow of funds.

Top global institutional investors like Bridgewater are validating this trend through action. In Q2 2025, they significantly increased their holdings in core tech companies such as NVIDIA, Google, and Microsoft, positioning their capital at critical nodes of the AI ecosystem, including computing power, chips, and cloud computing. Meanwhile, the total global assets of AI and big data-related funds have exceeded $30 billion, reflecting strong institutional interest.

Summary of Taiwan stock AI concept stocks: local trailblazers

Quanta Computer (2382): From OEM manufacturer to AI infrastructure supplier

This global largest laptop OEM is completing a spectacular transformation. Quanta’s dedicated team under Quanta Cloud Technology has successfully entered the supply chain of ultra-large US data centers, supplying key clients like NVIDIA. Last year, revenue was NT$1.3 trillion, with a continuous increase in AI server share. In Q2 this year, revenue surpassed NT$300 billion, up over 20% year-on-year, setting a historical record for the same period.

The general view among analysts is that Quanta will maintain long-term growth, with a target price range of NT$350 to NT$370.

Realtek Semiconductor (3661): The hidden champion in AI chip design

One of Taiwan’s most representative AI concept stocks. Focused on ASIC custom chip design, directly serving US cloud giants and high-performance computing leaders. Last year, revenue was NT$68.2 billion, up over 50% annually. In Q2 this year, quarterly revenue exceeded NT$20 billion, doubling compared to the same period last year.

As generative AI applications rapidly expand, Realtek has secured new AI accelerator orders and data center-related large contracts. Foreign institutions’ average target price is between NT$2,200 and NT$2,400, with significant upside potential.

Delta Electronics (2308): The behind-the-scenes hero of AI infrastructure

As a global leader in power management, Delta Electronics has found a new growth curve in the AI era. Its power supplies, cooling systems, and server cabinet solutions have become standard in the AI server supply chain. Last year, revenue was NT$420 billion, with an increasing proportion from data centers. In Q2, revenue was NT$110 billion, up over 15% year-on-year.

MediaTek (2454): From mobile chips to AI computing

This fabless chip designer is expanding into two new tracks: mobile AI and automotive AI. Its Dimensity series mobile platforms now include enhanced AI computing units, and it is collaborating with NVIDIA to develop automotive solutions. Last year, revenue was NT$490 billion, with about 20% YoY growth in Q2, and gross margins are improving quarter by quarter. Foreign institutions’ target price is between NT$1,300 and NT$1,400.

Sunway (3324): Liquid cooling technology capturing AI servers

As AI chip power consumption continues to break the kilowatt barrier, traditional cooling methods face bottlenecks. Sunway’s liquid cooling technology is riding this wave. Last year, revenue was NT$24.5 billion, up over 30%. This year, as cloud service providers accelerate the adoption of liquid cooling solutions, shipments have surged, with foreign target prices mostly above NT$600.

Leading US stocks in AI concept stocks

NVIDIA (NVDA): Absolute market leader

If AI is the new era, NVIDIA is the infrastructure provider of this era. Its GPUs and CUDA platform have become industry standards for AI model training. Last year, revenue was $60.9 billion, up over 120%. In Q2, revenue hit a new high of about $28 billion, with net profit increasing over 200% YoY.

Demand for Blackwell architecture’s B200 and GB200 chips remains strong and is unlikely to be replaced in the short term. Institutions generally rate it as a buy, reflecting strong confidence in its long-term profitability.

Broadcom (AVGO): The network hub of AI data centers

Playing a key role in AI chips and network connectivity. Last year, revenue was $31.9 billion, with AI-related products accounting for 25%. In Q2, revenue grew 19% YoY, with increasing demand from large cloud service providers for its Jericho3-AI chips and high-end switches. Foreign target prices are mostly above $2,000.

AMD (AMD): A strong challenger in the AI market

With its Instinct MI300 series accelerators, AMD is eating into NVIDIA’s market share. Last year, revenue was $22.9 billion, with data center business up 27%. In Q2, YoY growth was 18%, and the MI300X has been adopted by major cloud providers, with the MI350 series upcoming. Foreign target prices are mostly above $200.

Microsoft (MSFT): The driver of enterprise AI adoption

Through exclusive cooperation with OpenAI and the Azure AI platform, Microsoft is seamlessly integrating generative AI into global enterprise workflows. Last year, revenue was $211.2 billion, with intelligent cloud services growing 28%. In Q1, its intelligent cloud business first exceeded $30 billion, and Copilot monetization continues to unfold. The target price range is up to $550–$600.

Google (GOOGL): Beneficiary of search AI transformation

Although it entered the large model competition later, Google has begun catching up through products like Gemini. As a leader in AI application layers, its long-term potential should not be underestimated.

Should AI concept stocks be held long-term?

A calm analysis is needed here. Referencing Cisco Systems during the internet bubble, which peaked at $82 and then fell over 90% after the bubble burst. Although the company continued to operate well, its stock price has not returned to the high levels in 20 years. This serves as a warning:

Infrastructure suppliers (chips, servers, etc.) do experience high growth initially, but maintaining it is extremely difficult. These stocks are suitable for phased investments rather than long-term holding.

Downstream application companies like Microsoft and Google have more sustainable businesses, but their historical trends also show that even top-tier leaders can peak during bull markets and then fall sharply, struggling to regain previous highs for years. Similar to Yahoo during the internet era, which was eventually left behind by the times.

Core advice: timely rotation is more important than stubbornly holding a single stock. Regularly reviewing industry patterns and company fundamentals, and switching positions accordingly, is key to long-term profits.

Practical tips: how to efficiently allocate AI investments?

Buying individual stocks is one approach but concentrates risk. A more prudent method is a diversified portfolio:

Stock + Fund + ETF combination

• Core holdings: select absolute leaders like TSMC, NVIDIA, accounting for about 40% of total funds
• Fund allocation: choose funds like First Gold Global AI Robotics and Automation Industry Fund, accounting for 30%
• ETF coverage: TAIEX Global AI ETF (00851), Yuan Tai Global AI ETF (00762), accounting for 30%

Gradual entry principle Regardless of the method chosen, it’s recommended to adopt a regular fixed amount investment approach rather than a one-time bet. This can effectively smooth out market volatility and avoid buying at high points.

Platform choices Investing in Taiwan stocks via Taiwanese brokers; for US stocks, use cross-trading or overseas brokers. For short-term trading, CFD platforms offer two-way trading and leverage advantages.

Hidden risks in AI concept stocks

It must be honestly acknowledged that there are several risks not to be ignored:

Rapid industry iteration risk — AI technology advances extremely fast; today’s leaders may not be tomorrow’s winners. Investors can easily fall into sharp stock price fluctuations driven by hype around certain companies.

Unproven companies — While mainstream tech giants are deploying AI, many startups have little profitability and higher operational risks.

Policy and regulatory uncertainties — Governments regard AI as a strategic industry, but issues like data privacy, algorithm bias, and copyright may lead to strict regulations, affecting valuations and business models.

Sensitivity to macro environment — AI concept stocks are highly responsive to interest rate policies. When the Federal Reserve adopts easing policies, high-valuation tech stocks benefit; high interest rates suppress valuations. They are also vulnerable to capital shifts to other emerging themes.

Investment outlook from 2025 to 2030

Long-term bullish with short-term volatility is typical for AI concept stocks.

Rapid progress in generative AI, multimodal AI, and other technologies continues to drive demand for computing power, data centers, and specialized chips. In the short term, hardware suppliers like NVIDIA, AMD, and TSMC remain the biggest beneficiaries.

In the medium to long term, AI applications in healthcare, finance, manufacturing, autonomous driving, and other industries will gradually materialize into real revenue streams, fueling the overall growth of AI concept stocks.

A relatively conservative strategy is: prioritize infrastructure providers like chips and accelerators, while also including companies with tangible application deployments such as cloud services and medical AI. Diversifying through AI-themed ETFs can effectively reduce individual company risks. For ordinary investors, long-term allocation and phased entry are preferable to chasing high short-term gains.

When participating in the AI dividend, always remember: this is a long-term wealth transfer, not a casino for overnight riches. Rationality, patience, and regular review are the keys to ultimate success.