## The Rise of AI Chip Concept Stocks: Who Will Become the Next Gold Digger?

Since the launch of ChatGPT, the entire tech market's enthusiasm for AI has continued to heat up. But the real profit opportunities are not in those hype-driven application companies, but in **the suppliers of chips, hardware, and infrastructure that support AI operation**. Which companies in this industry chain are worth paying attention to?

## How Does the Industry Chain Profit in the AI Wave?

The commercialization process of AI essentially follows a clear logic: first, massive computing power is needed, then various applications can be supported. This means that **upstream chip and hardware manufacturers are often the first and most direct beneficiaries**.

According to IDC's latest forecast, global enterprise spending on AI infrastructure and solutions will reach $307 billion in 2025. By 2028, this figure is expected to double to $632 billion, with a compound annual growth rate (CAGR) of 29%. Among them, spending on accelerated servers will account for over 75%, becoming the hardware foundation of the AI industry.

In other words, **the demand for AI chips and data center equipment will maintain rapid growth for a considerable period**. This creates a rare investment window for related concept stocks.

## US Stock AI Chip Concept Stocks: Who Are the True Winners?

### NVIDIA (NVDA) — Absolute Industry Monopoly

NVIDIA's GPU and CUDA ecosystem have become the industry standard for AI model training. In 2024, revenue reached $60.9 billion, with an annual growth rate of over 120%, creating a rare growth curve in tech history.

Entering 2025, NVIDIA's momentum shows no signs of slowing. Second-quarter revenue surpassed $28 billion, with net profit increasing over 200% year-over-year. The launch of Blackwell architecture GPUs (B200, GB200) further consolidates its monopoly position in high-end computing markets. As AI applications continue to expand, NVIDIA's demand curve is unlikely to decline.

**But it is important to note** that NVIDIA's current valuation is already high, and the stock price has fully reflected this. Short-term breakthroughs are difficult, and there is a risk of a pullback.

### Broadcom (AVGO) — Hidden Champion

Unlike NVIDIA's "spotlight," Broadcom's role in the AI industry chain is more discreet but equally critical — it provides network connection chips for AI servers, customized ASIC chips, and optical communication solutions.

In fiscal year 2024, revenue was $31.9 billion, with AI-related products accounting for 25%. Second-quarter revenue increased by 19% year-over-year, mainly driven by cloud giants' intensive procurement of chips like Jericho3-AI and Tomahawk5.

As AI model sizes continue to grow, the demand for high-performance network connectivity will only increase. Broadcom's technological advantages in this niche are hard to shake.

### AMD (NASDAQ: AMD) — Challenger's Opportunity

AMD plays the role of "second source" in the AI accelerator market, with its Instinct MI series continuously gaining recognition from cloud giants. In 2024, data center business grew by 27% annually, and in Q2 2025, it increased by 18%.

The MI350 series is set to be released in the second half of the year, potentially further eating into market share. From a supply chain security perspective, companies tend to prefer multiple suppliers, providing AMD with rare growth opportunities.

### Microsoft (MSFT) — The Largest Beneficiary on the Application Side

Microsoft has successfully integrated generative AI into enterprise workflows through exclusive cooperation with OpenAI and the complete Azure AI ecosystem. In fiscal year 2024, cloud service revenue grew by 28%, with AI services contributing over half of that growth.

In Q1 2025, intelligent cloud business revenue first exceeded $30 billion. As Copilot features are deeply integrated into Windows, Office, and other products used by over a billion users worldwide, monetization potential continues to be unleashed. Compared to hardware manufacturers, Microsoft's business model is more mature and sustainable.

## Taiwan Stock AI Chip Concept Stocks: Where Are the Domestic Opportunities?

### TSMC (2330) — Industry Lifeline

As the world's largest wafer foundry, TSMC provides chip manufacturing for NVIDIA, AMD, and others. The surge in AI chip orders has directly boosted its capacity utilization and gross margin. In 2024, revenue is approximately NT$490 billion, with the proportion of AI chips continuously rising.

### Quanta Computer (2382) — The Hidden Giant in AI Servers

Quanta has successfully transformed from a notebook OEM to the world's largest AI server OEM. Its subsidiary, Quanta Cloud Technology (QCT), has successfully entered the supply chain of US mega data centers. In Q2 2025, revenue surpassed NT$300 billion, up over 20% year-over-year, setting a new high for the same period.

### Unisoc-KY (3661) — The Key to Customized Chips

Unisoc specializes in ASIC design services, with clients including US cloud giants and AI leading companies. In 2024, revenue was NT$68.2 billion, with an increase of over 50% year-over-year. In Q2 2025, quarterly revenue doubled, surpassing NT$20 billion. The ongoing mass production of large AI client orders ensures its long-term growth momentum.

### MediaTek (2454) — The Player in Mobile AI

MediaTek integrates enhanced AI computing units into mobile chips and collaborates with NVIDIA to develop automotive and edge AI solutions. In 2024, revenue was NT$490 billion, with gross margin gradually improving quarter by quarter. In Q2 2025, revenue increased by about 20% year-over-year, mainly driven by demand for high-end mobile chips and AI smart devices.

### Delta Electronics (2308) and Zhaohong (3324) — The Behind-the-Scenes Heroes of Infrastructure

As AI server power consumption surpasses the kilowatt threshold, traditional cooling becomes a bottleneck. Delta Electronics provides high-efficiency power supplies and cooling solutions; Zhaohong leads the global AI server market with liquid cooling technology. Both companies' growth stems from rigid industry upgrade demands.

## Three Major Traps in Investing in AI Chip Concept Stocks

### 1. Valuation Trap

During the dot-com bubble, Cisco Systems (CSCO) hit a high of $82 before crashing over 90%. Even with good performance over the next 20 years, the stock never returned to its peak. This lesson applies to today's AI concept stocks — **don't assume high growth will always correspond to high valuation**.

### 2. Industry Risks

The development speed of AI technology is unpredictable, and policy regulation also carries uncertainties. Issues like data privacy, algorithm bias, and copyright may trigger strict controls, impacting some companies' business models. Meanwhile, new technological routes may weaken current players' advantages.

### 3. Capital Flow Risks

Although AI themes remain focal points, stock prices are susceptible to macroeconomic influences. Changes in central bank interest rate policies and the diversion of new hot topics can cause short-term volatility in AI concept stocks. Even leading stocks are prone to phased corrections.

## How to Scientifically Allocate AI Chip Concept Stocks?

**Avoid heavy concentration in a single stock**. A more rational approach is diversification to spread risk:

**Individual Stocks** — Suitable for investors with in-depth understanding of the industry chain and time to track, select 2-3 core companies for focused attention

**AI-themed ETFs** — Such as Taishin Global AI ETF (00851), Yuan Da Global AI ETF (00762), providing broad coverage of the entire industry chain, with low fees and convenient, efficient access

**Stock Funds** — Managed by professional fund managers, offering balanced risk and return, suitable for investors with moderate risk appetite

**Dollar-Cost Averaging** — Regardless of the method chosen, regular fixed-amount purchases can effectively smooth costs and avoid timing risks

## Long-term Outlook for AI Chip Concept Stocks

From 2025 to 2030, the demand for AI chips and computing power will grow exponentially. The gradual implementation of applications like medical diagnostics, financial risk control, manufacturing optimization, and autonomous driving will translate into real revenue growth for companies.

**Short-term (1-2 years)** — Hardware suppliers remain the biggest beneficiaries, with companies in chips, servers, and cooling solutions showing good performance

**Medium-term (2-5 years)** — Application-side companies gradually realize revenue, and the overall profitability of the AI ecosystem improves, but valuation volatility increases

**Long-term (beyond 5 years)** — Industry enters maturity, and only companies with strong technological moats and continuous innovation can maintain competitiveness

**Therefore, the most prudent strategy is:** prioritize infrastructure suppliers as core holdings, regularly review industry landscape changes, reduce positions when overvalued, and add in phases during pullbacks. Do not pursue short-term quick profits but share in the growth dividends of the AI chip industry over the long term.