In-depth Analysis of AI Concept Stocks in October: Computing Power and Applications Dual Mainlines Lead the Market, Institutional Capital Allocation Shows New Logic

In October 2026, with the continuous breakthroughs in artificial intelligence technology and the acceleration of commercialization, the AI concept stock market has shown a clear divergent pattern. Computing power and application sectors have become the dual mainlines, leading the overall trend of AI concept stocks. The logic of institutional capital reallocation has shown new changes, with market hotspots continuously rotating. This article will conduct an in-depth analysis of the current market performance of AI concept stocks, the characteristics of sector divergence, the dynamics of leading stocks, and future investment opportunities, providing investors with a comprehensive market interpretation.

October AI Concept Stock Market Panorama: Overall Stable, Divergence Obvious

Since entering October, the AI concept stock market has shown an overall stable upward trend, but the internal structural divergence has intensified. According to monitoring data from Yuezhi Financial, as of October 18, the AI concept index has cumulatively increased by 5.32% for the month, outperforming the Shanghai Composite Index (which rose by 2.85% over the same period). However, there are significant differences in performance within sectors, with the computing power and application sectors showing distinctly different market performances.

The computing power sector has benefited from the continuous release of demand for AI large model training and breakthrough progress in domestic computing power chips, with a cumulative monthly increase of 8.75%, significantly outperforming the AI concept index. Among them, AI chips, servers, data centers and other sub-sectors have shown particularly outstanding performance. In contrast, although the overall increase in the application sector is less than that of the computing power sector, some leading stocks in vertical application fields such as AI+education, AI+healthcare, and AI+finance have shown impressive performance, with monthly increases exceeding 10%.

Market analysts point out that this divergent pattern mainly stems from the market's reassessment of the commercialization process of AI. As AI technology moves from laboratories to practical application scenarios, investors are paying more attention to the monetization capability and commercial value of AI technology, leading to obvious valuation divergence between the computing power and application sectors.

Computing Power Sector: Policy Dividends and Technological Innovation Resonate, Capital Continuously Flows In

As the infrastructure of the AI industry, the computing power sector has shown particularly strong performance in October. The policy side continues to release favorable news. The latest "Artificial Intelligence Industry Development Plan (2026-2028)" issued by the National Development and Reform Commission clearly states that by 2028, China's core AI industry scale will reach 800 billion yuan, and computing power infrastructure will become a key development direction.

In terms of technological innovation, breakthrough progress has been made in the domestic AI chip field. A leading domestic chip company's latest AI training chip has 3 times the performance of the previous generation and 40% higher energy efficiency, breaking the monopoly of foreign manufacturers in the high-end AI chip field. This technological breakthrough has directly driven the stock prices of related concept stocks to rise sharply, with a cumulative monthly increase of over 15%.

Capital flow data shows that in the past month, the computing power sector has received net inflows of over 12 billion yuan from northbound funds, accounting for more than 65% of the total northbound fund inflows into AI concept stocks. Institutional investors generally believe that as the parameter scale of AI large models continues to expand, computing power demand will show explosive growth, and the computing power sector has long-term investment value.

Application Sector: Commercialization Accelerates, Sub-sectors Show Bright Spots

Different from the rapid advance of the computing power sector, the application sector has shown structural opportunities in October. Overall, the AI application sector increased by 3.2% in the month, lower than the computing power sector, but a number of outstanding individual stocks have emerged in vertical application fields.

In the AI+education field, with the growth of personalized learning needs, AI education solution providers have been sought after by the market. An educational technology company's AI learning assistant product has been put into use in more than 5,000 schools nationwide, with monthly active users exceeding 10 million. Driven by this, the related stock price increased by 12.5% in the month.

In the AI+healthcare field, auxiliary diagnostic systems have become market hotspots. A medical AI company's pulmonary nodule detection system has an accuracy rate of 98.5%, has obtained Class III medical device certification from the National Medical Products Administration, and has been put into use in more than 300 hospitals nationwide. The company's stock price increased by 14.2% in the month, becoming the leading stock in the medical AI sector.

In the AI+finance field, the application of intelligent investment advisory and risk control systems is accelerating. A financial technology company's AI investment advisory platform has a managed asset scale exceeding 50 billion yuan, a 150% increase from the beginning of the year. Related concept stocks increased by 9.8% in the month, outperforming the market.

Leading Stock Analysis: Performance-driven and Valuation Repair Coexist

In October, the performance of AI concept stock leaders has shown obvious divergence, with performance-driven and valuation repair becoming the two mainlines. In the computing power field, an AI chip leader company, with the excellent performance of its latest generation of products, achieved a year-on-year increase of 185% in net profit in the third quarter, with its stock price increasing by 18.7% in the month. Another cloud service provider benefited from the explosive growth of AI training demand, with a year-on-year increase of 72% in revenue in the third quarter, and its stock price increased by 15.3% in the month.

Leading stocks in the application sector mostly benefited from the acceleration of commercialization. An AI medical company achieved a year-on-year increase of 95% in revenue and 210% in net profit in the third quarter, with its stock price increasing by 16.8% in the month. Another AI education company's AI learning product paid user base exceeded 5 million, with a year-on-year increase of 230% in monthly active users, and its stock price increased by 13.5% in the month.

It is worth noting that after experiencing rapid growth in the early stage, some AI concept stock leaders have seen valuation adjustments this month. An AI algorithm provider's stock price decreased by 8.2% in the month, mainly because the market's expectation of its commercialization process was not met. Analysts point out that AI concept stock leaders have entered a performance verification period, and investors should pay more attention to the company's actual profitability and commercialization situation.

Capital Flow and Market Trends: Institutional Reallocation Logic Emerges

Capital flow data shows that in October, the AI concept stock market has shown obvious characteristics of institutional reallocation. In terms of northbound funds, there is an overall net inflow trend, but the internal structure has changed. The computing power sector has received continuous net inflows, while the application sector has shown divergence, with some AI application concept stocks with slower commercialization progress experiencing capital outflows.

In terms of domestic institutional investors, the allocation ratio of public funds to AI concept stocks increased from 12.5% in September to 15.3% in October, but the allocation focus has shifted from general AI algorithms to computing power infrastructure such as AI chips and AI servers, as well as vertical application fields with faster commercialization progress such as AI+healthcare and AI+education.

Private funds are more focused on细分 leaders in AI concept stocks, especially companies with core technical barriers and commercialization capabilities. Data shows that the position concentration of private funds in AI concept stocks increased by 8.7 percentage points compared to the previous month, showing an investment strategy of "selecting individual stocks".

Market analysts believe that the changes in the institutional capital reallocation logic reflect the market's re-recognition of the development stage of the AI industry. As AI technology moves from laboratories to commercial applications, investors are paying more attention to the actual monetization capability and commercial value of AI technology, leading to capital concentration in computing power infrastructure and application fields with faster commercialization progress.

Investment Opportunities and Risk Warnings: Grasp the Dual Mainlines, Be Alert to Valuation Bubbles

Based on the current market performance and institutional capital trends of AI concept stocks, we believe that future investment opportunities are mainly concentrated in the following aspects:

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• Computing Power Infrastructure: AI chips, servers, data centers and other fields will continue to benefit from the growth of demand for AI large model training. Focus on leading companies with core technical barriers and domestic substitution capabilities.
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• AI+Vertical Applications: Vertical application fields such as AI+healthcare, AI+education, and AI+finance have faster commercialization progress and have emerged a number of outstanding细分 leaders worthy of attention.
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• AI Commercialization Services: AI model training, data annotation, AI consulting and other service-oriented enterprises will see continuous growth in market demand with the popularization of AI applications.
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At the same time, investors also need to be alert to the following risks:

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• Valuation Bubble Risk: The valuations of some AI concept stocks have reached historical highs, and the risk of valuation adjustment needs to be警惕.
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• Technology Iteration Risk: AI technology iteration is fast, and some companies may face the risk of technology routes being eliminated.
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• Commercialization Below Expectation Risk: The commercialization process of AI applications may face challenges in policy, market and other aspects, leading to performance below expectations.
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Conclusion: Grasp the Golden Age of AI Investment, Select Quality Targets

The October AI concept stock market has shown a clear divergent pattern, with the computing power and application sectors becoming the dual mainlines, leading the overall trend of AI concept stocks. The logic of institutional capital reallocation has shown new changes, with more attention paid to computing power infrastructure and application fields with faster commercialization progress.

Looking to the future, with the continuous breakthroughs in AI technology and the acceleration of commercialization, the AI industry will usher in a golden development period. Investors should seize this historic opportunity, focus on the two mainlines of computing power infrastructure and AI+vertical applications, select quality targets with core technical barriers and commercialization capabilities, while being alert to valuation bubbles and technology iteration risks.

On the road of AI investment, short-term market fluctuations are inevitable, but in the long run, the impact of AI technology on the economy and society will far exceed that of the Internet, and AI concept stocks are expected to become one of the most valuable investment tracks in the next decade. Investors should view AI investment from a long-term perspective and seize the wealth opportunities of the AI era.