2026 AI-Related Investment Guide — Opportunities in AI Concept Stocks from Infrastructure to Application Deployment

The AI industry has entered a period of explosive growth, but this is not just a time of technical hype. By 2026, the real opportunity lies in identifying AI concept stocks that combine commercial potential with solid performance support. This guide will help you understand the structure of the AI industry in depth and highlight selected investment targets worldwide and in Taiwan.

The Economics of AI: Why AI Concept Stocks Are Worth Watching

Over the past five years, AI has moved from laboratories into everyday applications. The popularity of ChatGPT, advancements in autonomous driving, and the deployment of medical imaging diagnostics are no longer just concepts—they are real industry transformations.

The core logic of AI concept stocks is simple: they are the infrastructure providers of the AI era. Whether it’s companies manufacturing high-performance GPUs, firms offering server integration solutions, or those solving cooling and power issues, these companies are selling “shovels” to the gold rushing enterprises.

According to Gartner’s latest data, global AI spending is projected to reach $2.53 trillion by 2026, climbing further to $3.33 trillion in 2027. This is not just a forecast—it’s already happening. McKinsey’s research is even more aggressive—estimating that by 2030, AI will directly contribute $15 trillion to global GDP.

However, this does not mean all AI concept stocks are worth buying. The key is to distinguish truly capable companies from those riding the wave of hype and over-speculation.

The Three Layers of AI Industry Investment Logic

To truly understand the investment value of AI concept stocks, you need to break down the AI industry into three layers—these form a complete ecosystem.

Layer 1: Chip Manufacturing—Indispensable Foundation

Regardless of which company ultimately leads the AI race, the underlying principle of all high-performance AI chips is consistent—they require the most advanced manufacturing processes. TSMC (2330) stands at the top of this pyramid.

2nm process technology and advanced packaging like CoWoS have become industry standards. TSMC’s long-term technological leadership grants it stable pricing power. Companies at this layer tend to have relatively stable growth rates, with less volatile stock prices, offering long-term certainty—making them suitable as core holdings in a portfolio.

Layer 2: System Integration—The True Differentiator

As AI evolves from single chips to entire racks, complete systems, and data centers, the real test is system integration capability. This is where companies can truly differentiate themselves.

Foxconn (2317) and Quanta (2382) represent Taiwan’s strength in this layer. They need to continuously improve rack density, ensure delivery stability, and manage customer concentration risks. The performance of system integrators is highly linked to the capital expenditure cycles of cloud clients—highly elastic during boom times, with amplified fluctuations during downturns.

Layer 3: Cooling and Power—The Critical Investment Focus for 2026

This may be the most overlooked opportunity this year. As AI servers’ power consumption continues to surpass kilowatt thresholds, liquid cooling has shifted from optional to essential. Companies like Chicony (3017) and Shuanghong (3324), which provide cooling solutions, are positioned at this technological turning point.

Demand is structurally rising. As power consumption keeps increasing, the profitability of these companies will continue to expand.

Four Industry Trends Reshaping the Value of AI Concept Stocks

Trend 1: From Model Training to Inference Computing

In recent years, tech giants have aggressively purchased GPUs for model training. Starting in 2026, the industry focus shifts to inference—enabling AI to perform tasks, generate content, and process data in real-time.

This shift means computing is no longer confined to the cloud but is gradually moving to smartphones, laptops, and edge devices. For companies, this offers three benefits: reducing long-term cloud costs, enhancing data privacy, and improving real-time responsiveness.

High-cost general-purpose GPUs will be replaced by specialized ASIC chips for specific tasks. Overseas companies like Broadcom and Marvell, as well as Taiwanese firms such as Phison (3661) and Creative (3443), are seizing new opportunities in this transition. Meanwhile, demand for NPU processors from Qualcomm and MediaTek (2454) is exploding.

Trend 2: Energy and Cooling as New Essential Needs

AI servers consume far more power than traditional servers. As model sizes grow, data centers face dual pressures: heat dissipation and power supply shortages. This is no longer about buying more generators but involves systemic upgrades to power grids, energy sources, and cooling technologies.

Liquid cooling is key. Immersion cooling and direct liquid cooling are gradually becoming standard in data centers, as traditional air cooling cannot handle extreme heat. Additionally, clean energy and smart grid management are emerging as critical factors. Delta Electronics (2308) with its high-efficiency power supplies and cooling systems, and Shuanghong’s liquid cooling tech, are key players.

Trend 3: Application Deployment Outpacing Tech Hype

2026 will be the year AI truly proves its market value. Investors and companies will no longer buy based on “AI features” alone but will focus on results—whether AI can help clients save money or generate profits.

Surviving software companies will be judged less by the sophistication of their models and more by their ability to build hard-to-copy data moats. Companies merely offering ChatGPT API services will be quickly eliminated. The real winners are those with proprietary, domain-specific data—such as medical imaging, legal case data, or factory automation data.

Trend 4: Diverging Capital Expenditure Cycles

While major overseas tech giants’ infrastructure investments are maturing and their capital expenditure growth may slow, emerging application fields like automotive, healthcare, and industrial AI are still in early explosive growth stages. This means the benefits of AI concept stocks will vary depending on their customer base.

Selected Taiwanese AI Stocks—Capturing Infrastructure Opportunities

Taiwan is no longer just an OEM hub but now plays a central role in global AI infrastructure. Here are some selected stocks:

Process Layer: TSMC (2330)

Regardless of who wins the AI race, 2nm and advanced packaging are essential. TSMC’s technological leadership and pricing power provide long-term certainty. Its stock performance remains relatively stable, making it a good anchor for investment portfolios.

System Integration Layer: Quanta (2382) and Foxconn (2317)

Quanta’s Quanta Cloud Technology (QCT) has successfully entered the US large-scale data center supply chain, with clients including NVIDIA and major cloud providers. System integration capability is increasingly a key market metric. Foxconn is also advancing in edge computing and terminal integration.

Edge AI Chips: MediaTek (2454) and Phison (3661)

MediaTek’s Dimensity series now includes enhanced AI processing units, collaborating with NVIDIA in automotive and edge AI. Phison specializes in ASIC customization, serving US cloud giants and HPC leaders.

Cooling and Power Layer: Shuanghong (3324) and Delta Electronics (2308)

Shuanghong’s liquid cooling tech has become standard in AI servers, with demand accelerating as power consumption rises. Delta provides comprehensive power management, cooling, and rack solutions, directly entering the AI server supply chain.

Leading Global Companies—Players Shaping the AI Ecosystem

NVIDIA (NVDA)

Still the undisputed leader in AI computing worldwide. The focus has shifted from “whose chip is fastest” to “how to make AI faster and more power-efficient.” NVIDIA’s complete ecosystem—from chips to systems to software—gives it an unmatched moat.

Broadcom (AVGO) and Marvell (MRVL)

With the advent of ASICs, these companies are gaining prominence. They offer not just chips but also architecture design and mass production capabilities, becoming preferred partners for cloud giants.

AMD

Successfully penetrating the NVIDIA-dominated market, with its Instinct MI300 series providing an alternative for cloud providers and large enterprises. Competition is intensifying.

Microsoft (MSFT)

A platform provider for enterprise AI transformation. Its exclusive partnership with OpenAI, Azure AI platform, and deep integration of Copilot make it a major beneficiary of enterprise AI adoption. Its ability to monetize Copilot across a billion users continues to grow.

Arista Networks (ANET)

As AI clusters expand, high-speed, low-latency networking becomes critical. Arista benefits from replacing InfiniBand with Ethernet in this process.

Consolidation Energy (CEG)

Possessing large nuclear power assets, capable of providing stable, large-scale, low-carbon baseload power long-term. For 24/7 operation of AI data centers with rising power demands, this strategic energy source is far more valuable than simple electricity pricing.

How to Systematically Allocate AI-Related Investments

Comparison of Investment Options

In Taiwan, recommended ETFs include Taishin Global AI ETF (00851) and Yuan Da Global AI ETF (00762) for diversified exposure. In the US, several AI-focused ETFs are available.

The Value of Dollar-Cost Averaging

Instead of trying to perfectly time the market, adopting a regular investment plan (dollar-cost averaging) is more effective. Even giants like Bridgewater adjust their holdings constantly, indicating that AI-related opportunities are dynamic. Some stocks may already reflect AI optimism, so continuous updating and adaptation are key to maximizing returns.

Balancing Short-Term Risks and Long-Term Opportunities

Short-Term Challenges

AI concept stocks react quickly to news, leading to significant short-term volatility. Federal Reserve and other central bank policies, new themes like renewable energy, can cause capital shifts. Expect some turbulence through 2026.

Historical Lessons: The Cisco Story

During the dot-com bubble, Cisco Systems was the “Internet equipment king.” At its peak in 2000, its stock hit $82, but after the bubble burst, it fell to $8.12—over 90% decline. Despite Cisco’s subsequent strong performance, its stock has yet to return to the high point.

This teaches us that even fundamentally solid infrastructure companies should be approached with phased allocations rather than long-term, unwavering holdings.

Policy and Regulatory Variables

Governments view AI as a strategic industry and may increase subsidies and infrastructure investments. However, issues like data privacy, algorithm bias, and intellectual property rights could lead to regulatory risks. Tightening regulations could challenge some companies’ valuations and business models.

The Right Investment Mindset

When investing in AI stocks, continuously monitor: whether the pace of AI technology development is slowing, whether application monetization is improving as expected, and whether individual companies’ profit growth is decelerating. Only if these conditions remain favorable can AI-related investments sustain market support.

2026: The Turning Point for AI Concept Stock Investing

AI concept stocks have evolved from “concepts” to “real applications.” 2026 will be the year of deployment and the year to adjust investment strategies.

In the short term, infrastructure and hardware suppliers will benefit most. In the long term, companies with core vertical applications will emerge. Whether choosing individual stocks, funds, or ETFs, the key is to distinguish companies with genuine performance support from those driven purely by hype.

To participate in AI growth, investors should prioritize chipmakers and server providers, while diversifying through ETFs to reduce single-stock risks. Most importantly, stay attentive to technological progress, application deployment, and profit recovery to find your own balance between risk and opportunity.