AI stocks and Nasdaq outlook: which tech events could affect the U.S. market?

Artificial intelligence is still an important theme driving the U.S. technology stocks market. In the past few years, the development of generative AI has rapidly expanded the GPU, cloud computing, and data center industrial chain. The Nasdaq 100 index has also continued to rise under expectations of growth from major technology companies. According to data from the Gate platform’s NAS100 market, the index gradually recovered from levels near the adjustment low at the end of 2022, and in 2026 it briefly approached around 30,000 points. It is currently still in a high-range consolidation phase.

However, the AI rally is entering a new validation stage. The market is no longer simply trading the imagination space created by AI, and is instead focusing on whether technology companies’ AI spending can translate into actual revenue, and whether an overvalued market can be supported by future earnings growth. Key variables that will shape AI stocks and the trajectory of the U.S. market in the future will center on technology companies’ earnings reports, investment in AI infrastructure, changes in chip demand, and Federal Reserve monetary policy.

Why has the Nasdaq 100 kept rising? How has the AI investment cycle changed valuation logic for tech stocks?

The Nasdaq 100’s rise in recent years is closely related to the AI industry cycle. Since 2023, generative AI applications such as ChatGPT have pushed the market to reassess the value of AI infrastructure. Large amounts of capital flowed into semiconductor, cloud computing, and software companies, triggering a round of valuation reconfiguration around the AI industrial chain.

From the Gate platform’s NAS100 chart, after the index ended its correction near the end of 2022, an upward trend began. Between 2024 and 2026, it has continued to break above prior highs. Recently, NAS100 prices have remained above 28,000 points and even approached the 30,000-point psychological level, reflecting that the market still recognizes long-term growth opportunities brought by AI technology.

A major driver of this rally has been improved earnings expectations for large technology companies. NVIDIA has benefited from rising demand for AI servers and GPUs. Companies such as Microsoft, Alphabet, and Amazon have expanded their AI business footprint through cloud computing and enterprise AI services. AI is no longer just an emerging concept in the tech sector, but an important factor influencing major tech companies’ capital expenditure and future revenue expectations.

But high valuations also mean the market is demanding more from future growth. In the past, investors focused on “who could catch the AI trend.” Now the market is more focused on “whether AI investment can generate enough returns.” If future revenue growth at companies cannot match continuously increasing AI capital spending, tech stock valuations may face a reset.

Which tech events could affect AI stock performance? Earnings, chips, and capital expenditures become key watch indicators

The core events affecting AI stock performance are shifting from product releases toward business data validation. Quarterly earnings, the scale of AI infrastructure investment, and chip supply conditions of large technology companies could all change the market’s assessment of the AI industry cycle.

The 2026 earnings season for technology companies will be an important window to watch. The market will focus on AI business growth at companies such as Microsoft, Alphabet, and Amazon, including cloud computing revenue, demand for enterprise AI services, and the scale of data center investment. If AI-related businesses begin contributing more noticeably to revenue growth, the market may continue to reinforce the long-term AI value logic.

Meanwhile, AI capital expenditures have become a key metric for investors to gauge the health of the industry. In recent years, tech giants have kept expanding server purchases, data center construction, and computing power investment, hoping to maintain leadership in the AI competition. But heavy spending also means greater pressure on profitability, and the market needs to see whether these investments can be converted into commercial value.

Currently, the main variables affecting AI stocks include:

• Whether AI capital expenditures by large technology companies continue to expand;
• Whether AI applications generate new sources of revenue;
• Whether GPU supply meets enterprises’ computing demand;
• Whether enterprise customers are willing to keep paying for AI services.

Whether the future AI rally can continue depends largely on whether these indicators keep improving.

How do NVIDIA and AI chip demand affect the Nasdaq’s outlook?

NVIDIA remains one of the most important market watch targets in the AI industry chain, because GPU compute demand directly influences the entire AI infrastructure cycle. As demand for large model training and inference grows, high-performance computing resources become a core investment direction for technology companies.

In recent years, NVIDIA’s data center business has grown rapidly, and the company has become an important beneficiary of the AI infrastructure investment cycle. Market focus on NVIDIA has also shifted from one-quarter sales growth to longer-term questions, including whether AI chip demand will remain sustained, whether the supply chain will stay stable, and whether enterprises will keep expanding their computing power investment.

Competition in the AI chip market is also changing. AMD continues to push its data center GPU business. Google is developing its own chips such as TPU. Cloud computing companies like Microsoft and Amazon are also exploring in-house computing solutions to reduce reliance on a single supplier.

This shift in competition could affect future profit allocation across the AI industry. If AI compute demand continues to grow, chip suppliers and related industrial chain players may still receive market attention. But if companies begin optimizing capital expenditures, the market may re-evaluate the growth potential of AI infrastructure companies.

For the Nasdaq, NVIDIA is not only a semiconductor company, but also an important indicator of AI investment sentiment. Changes in chip demand can transmit through the industrial chain to affect the broader technology sector, thereby influencing index performance.

Can AI capital expenditures translate into profit? The market is reevaluating the commercial value of AI

AI infrastructure investment is moving into a stage that places greater emphasis on return on investment. In recent years, tech giants such as Microsoft, Alphabet, and Amazon have continuously increased AI-related capital expenditures—building data centers, purchasing GPUs, and developing cloud-based AI services to capture market share. These investments have driven growth in the semiconductor and cloud computing industries, and also served as an important support for the Nasdaq’s rise.

But as the scale of investment keeps expanding, the market has started to focus on a core question: whether AI investment can bring sufficient commercial returns. Large capital inputs need to correspond to higher revenue growth; otherwise, companies’ profit margins may face pressure, and investors may reduce the valuations they assign to future growth.

At present, AI commercialization is mainly concentrated in several areas, including enterprise AI software, cloud computing services, AI assistants, and automation applications. Microsoft is exploring enterprise-side AI demand through the Copilot ecosystem. Google Cloud and Amazon Web Services are also driving enterprise customers to adopt AI infrastructure. If these services can form a stable source of revenue, AI capital expenditures would shift from cost spending to long-term growth momentum.

However, AI commercialization still carries uncertainty. Deploying AI tools requires time, and some applications are still in the exploration stage. The market has not fully confirmed whether AI revenue growth can match the current massive infrastructure investment.

This is also the biggest market divergence in AI stocks today:

• The optimistic view holds that AI will become a new round of productivity upgrade similar to the evolution driven by the internet and mobile internet, and that current investment is still in the early stage of a long-term industry cycle;
• The cautious view holds that the market has already priced in a large portion of growth expectations in advance, and that more profitability data will be needed to prove that AI valuations are reasonable.

Therefore, an important thing to watch in the future direction of AI stocks is not just how much companies invest, but whether those investments can be converted into cash flow and profits.

Are AI stock valuations too high? How to balance growth expectations and market risk?

The rally in AI stocks has brought new valuation discussions. In the past few years, investors were willing to assign higher valuations to AI-related companies because the market believed that artificial intelligence could create a new cycle of industry growth. But as asset prices keep rising, valuation pressure becomes an issue the market can no longer ignore.

Currently, some AI leaders already have very high levels of market attention. Their share price performance reflects not only current profitability, but also investors’ expectations for growth headroom over the next few years. This means that if a company’s future performance exceeds market expectations, the stock may continue to receive support; but if growth rates fall short of expectations, stocks with high valuations may be more prone to volatility.

Looking at the NAS100’s trend, after the index broke above 28,000 points in 2026, it moved toward the 30,000-point area and then entered a period of consolidation. This indicates that market sentiment is still relatively positive, but investors are starting to wait for new catalysts rather than simply chasing the AI concept.

The main risks facing AI stocks currently include:

• AI capital investment speeds outpacing commercial revenue growth;
• Data center construction constrained by energy and infrastructure limitations;
• Intensifying competition in the chip industry compressing profit margins;
• Macroeconomic interest-rate changes affecting the valuations of growth stocks.

The market is not denying AI’s long-term value; it is re-evaluating the relationship between growth pace and price. For investors, the key question affecting AI stock performance is not whether AI has room to develop, but whether current valuations have already fully priced in future growth.

How do changes in Federal Reserve rates affect AI stocks and Nasdaq valuations?

Apart from industry trends, monetary policy remains an important factor influencing U.S. technology stocks. AI stocks typically fall under growth assets, and their valuations rely to a large extent on future earnings expectations, making them more sensitive to interest-rate changes.

When the market expects the Fed to cut rates, growth stocks are usually supported, because a lower-rate environment reduces the discounted pressure on future cash flows and increases investors’ willingness to accept long-term growth assets. Conversely, if inflation remains higher than expected and the Fed maintains restrictive policy, tech stock valuations may come under pressure.

In 2026, the market will continue to pay attention to U.S. inflation data, changes in the employment market, and Fed policy signals. Macro data such as CPI and PPI not only affect interest-rate expectations, but also influence how funds are allocated among tech stocks, cyclical stocks, and defensive assets.

For the Nasdaq, AI industry trends and macro liquidity create a dual impact. On one hand, advances in AI technology and corporate investment drive the tech sector’s long-term growth. On the other hand, the interest-rate environment determines how much valuation the market is willing to give to that growth.

Therefore, future AI stock performance will not be determined solely by technological breakthroughs, but also by the combined effect of industry growth and macro policy.

After the AI boom, what key variables should the U.S. stock market watch?

AI remains an important theme affecting the U.S. technology market in the coming years, but the market’s focus is continuously evolving. From early attention on model capabilities and technical breakthroughs to the current emphasis on commercialization and profitability, the logic behind AI investment is entering a more mature phase.

Key variables that will influence AI stocks and the Nasdaq’s direction mainly include:

• The rate of revenue growth from AI applications: whether companies are willing to keep paying for AI services;
• The investment cycle for data centers: whether global compute demand continues to expand;
• GPU supply and chip competition: whether AI infrastructure costs decline;
• Changes in macro policy: whether the interest-rate environment supports growth stock valuations.

If AI can continuously improve corporate efficiency and create new sources of revenue growth, related industrial chain players may still receive market attention. But if the commercialization pace lags behind expectations, the market may shift from growth trading to profit trading.

For the Nasdaq, the core of future market direction is no longer simply “whether AI has prospects,” but “whether AI growth can be delivered.”

How to track AI stocks and Nasdaq market changes through Gate?

To track AI stocks and the Nasdaq’s direction, you need to conduct a comprehensive analysis combining price changes, industry events, and the macro environment. A single price fluctuation cannot reflect market logic. Investors need to watch technology companies’ earnings reports, AI industry developments, and changes in market capital flows at the same time.

Through the Gate platform, users can follow market changes for Nasdaq-related indexes, technology stocks, and other market assets, and understand asset performance by combining price trends, trading volume, and market trends.

For example, the NAS100 chart shows that in recent years, the index’s rise has been mainly driven by growth from tech leaders and the AI investment cycle. Meanwhile, the recent consolidation at high levels reflects that the market is waiting for new fundamental confirmation. By combining AI industry news, company earnings reports, and macro data, you can understand more comprehensively the reasons behind market changes.

Summary

AI stocks are still an important force driving the Nasdaq’s trend, but the market is entering a new phase. What drove the rally in the past was the imagination space around AI technology; what will determine the market direction in the future will be the pace of AI commercialization, companies’ profitability, and the return on capital investment.

Based on the Gate NAS100 market view, after years of rally the index is already at a high level. AI-related companies are still receiving capital attention, but the market’s requirements for the quality of growth are increasing.

Key variables that will affect AI stocks and the U.S. market going forward include technology companies’ earnings performance, changes in AI capital expenditures, chip demand trends, and Fed interest-rate policy. If AI investments can be consistently converted into revenue growth, tech stocks may still receive support; if the market finds that investment does not match returns, pressure for valuation adjustments may also increase.

FAQ

Why do AI stocks affect the Nasdaq’s performance?

AI-related companies are mainly concentrated in the technology sector, and large tech companies account for a relatively high proportion of the Nasdaq’s market value. Therefore, changes in their stock prices directly affect index performance.

Why is NVIDIA an important indicator for the AI market?

NVIDIA provides many GPUs required for AI training and inference. As a key supplier for the current AI infrastructure, changes in its performance are often viewed as an important reference for AI demand.

Why is AI capital expenditure being closely watched by the market?

AI capital expenditures reflect technology companies’ judgments about future artificial intelligence demand, but the market focuses more on whether these investments can generate actual revenue.

Why do interest rate changes affect AI stocks?

The valuations of growth-oriented tech stocks depend on future earnings expectations, so interest-rate changes affect how investors price long-term cash flows.

What is the biggest risk for AI stocks in the future?

Key risks include AI commercialization moving slower than expected, insufficient returns on capital investment, intensifying industry competition, and changes in macro policy.