As we enter the last ten days of October 2026, the artificial intelligence sector continues to show a differentiated pattern, with significant divergence in the performance of leading AI stocks. As third-quarter financial reports are released, the market's valuation logic for various segments of the AI industry chain has become clearer, with computing power and application sectors showing a "heaven and hell" divergence. This article will provide an in-depth analysis of the current market performance, capital flows, and future investment opportunities of leading AI stocks, offering valuable references for investors.

AI Sector Divergence Intensifies, Leading Stocks Show Different Performance

As of October 23, the AI sector has shown relatively differentiated performance overall. Wind data shows that the AI concept index has risen by 3.2% this month, but with significant differences in internal structure. Computing infrastructure leading stocks have performed strongly, such as Cambricon-U (688256.SH), which has gained 18.5% this month, while some application-side AI leaders have adjusted, such as iFLYTEK (002230.SZ), which has slightly decreased by 2.3%.

This differentiated pattern mainly stems from different market expectations for the commercialization progress of various segments of the AI industry chain. As large model technology gradually matures, computing power, as the infrastructure of the AI industry, has relatively high demand certainty and is favored by institutional funds. Meanwhile, application-side AI companies face challenges of commercialization falling short of expectations, leading to valuation pressure.

Computing Power Sector: High Demand Certainty, Valuation Recovery Continues

The computing power sector has become a market focus in the last ten days of October. As the parameter scale of domestic and international large models continues to expand, demand for computing power has shown explosive growth. According to IDC forecasts, China's AI computing power market size will grow by 65% year-on-year in 2026, reaching 280 billion yuan, and this high-growth expectation supports the valuation recovery of the computing power sector.

Specifically, AI chip leader Cambricon-U, with its self-developed chip advantages, achieved 120% year-on-year revenue growth in the third quarter, with net profit achieving single-quarter profitability for the first time. The company's recently released third-generation training chip offers 3 times better performance than the previous generation, further consolidating its leading position in the AI chip field.

In addition, AI server manufacturer Inspur Information (000977.SZ) has also performed impressively, with AI server shipments increasing by 85% year-on-year in the third quarter, and market share further increasing to 35%. Institutions believe that with the acceleration of intelligent computing center construction, Inspur Information, as the domestic AI server leader, will continue to benefit from the industry's high growth.

Application Sector: Commercialization Falls Short of Expectations, Valuation Under Pressure

In sharp contrast to the computing power sector, application-side AI leading stocks have shown relatively weak performance. Taking iFLYTEK as an example, although the company has made some progress in the large model field, its third-quarter revenue growth was only 15% year-on-year, below market expectations. The company recently stated that the commercialization process in vertical fields such as education and healthcare is slower than expected, leading to short-term performance pressure.

In addition, AI security leader Hikvision (002415.SZ) also faces similar challenges. As the traditional security market becomes saturated, AI-enabled intelligent transformation has become a new growth engine for the company, but during the transformation process, it faces issues such as low customer acceptance and long project cycles, leading to weak short-term performance growth.

Institutional Capital Flows Show New Pattern, Portfolio Adjustments Significant

As the AI industry chain develops and differentiates across various segments, institutional funds' positioning in late October also showed significant changes. According to Wind data, since October, northbound funds have cumulatively net purchased approximately 4.5 billion yuan in the AI computing power sector, while reducing holdings of leading AI application stocks by about 2.8 billion yuan. This "sell applications, buy computing power" portfolio adjustment reflects institutions' different assessments of various segments in the AI industry chain.

Public Funds: Increasing Positions in Computing Power Leaders, Reducing Application Targets

As a major market force, the portfolio adjustments of public funds have a significant impact on the AI sector's performance. Data shows that since October, several AI-themed funds have significantly increased their allocation to the computing power sector, with the average holding proportion of computing power leaders such as Cambricon-U and Inspur Information increasing by 3-5 percentage points.

Meanwhile, some funds have reduced their holdings of leading AI application stocks. An AI-themed fund manager stated: "Current AI applications face challenges in commercial implementation, with relatively low certainty in short-term performance. In contrast, computing power, as the infrastructure of the AI industry, has higher demand certainty and more attractive valuations."

Private Funds: Positioning in AI + Niche Segments, Seeking Differentiated Opportunities

Different from public funds, private funds are more inclined to find opportunities in niche segments within the AI industry chain. In late October, several top private funds increased their positions in leading companies in vertical fields such as AI + healthcare and AI + finance, believing these sectors have relatively faster commercial implementation and higher investment value.

For example, a billion-level private fund recently heavily purchased the AI healthcare leader Weining Health (300253.SZ), optimistic about its leading position in the medical AI field. The company's medical AI business revenue grew by 60% year-on-year in the third quarter, becoming the main growth driver of its performance.

Policy Support Continues to Strengthen, AI Industry Welcomes New Development Opportunities

In late October, the policy environment continued to release positive news, injecting new momentum into the development of the AI industry. On October 18, the Ministry of Industry and Information Technology released the "Artificial Intelligence Industry Innovation and Development Action Plan (2026-2028)", clearly stating that by 2028, China's artificial intelligence core industry scale will exceed 800 billion yuan, with an average annual growth rate maintained at over 25%.

The action plan also emphasizes that it will focus on supporting the construction of AI computing power infrastructure, innovation in large model technology, and industry application implementation, providing clear guidance for the development of various segments in the AI industry chain. Analysts believe that with the continuous release of policy dividends, the AI industry will usher in a new round of development opportunities.

Local Policies Intensively Introduced, AI Industry Accelerates Implementation

Under the guidance of national policies, various regions have also successively introduced specific measures to support the development of the AI industry. On October 20, Beijing released the "Implementation Plan for Promoting the Innovative Development of the Artificial Intelligence Industry", proposing that by 2027, the city's artificial intelligence core industry scale will reach 300 billion yuan, cultivating more than 10 leading AI enterprises with international competitiveness.

Meanwhile, similar policies have been successively introduced in places like Shanghai and Guangdong, promoting the deep integration of AI technology and the real economy. The intensive introduction of these local policies will further accelerate the commercial implementation of AI technology, bringing development opportunities to related enterprises.

Future Investment Strategy: Grasping the Dual Main Lines of Computing Power and Applications, Focusing on Niche Field Opportunities

Looking ahead, the AI industry will continue to maintain high growth momentum, but its internal structure will continue to differentiate. Investors should focus on the dual mainstays of computing power and applications, while also paying attention to investment opportunities in niche areas. Computing Power Sector: Focus on AI Chip and Server Leaders As the infrastructure of the AI industry, computing power will remain a key focus for institutional funds. Investors are advised to pay attention to leading companies in the AI chip sector such as Cambricon-U and Hygon Information (688041.SH), as well as companies in the AI server sector such as Inspur Information and Sugon (603019.SH). These companies will continue to benefit from the rapid growth in demand for AI computing power, leveraging their technological advantages and economies of scale. Application Sector: Focus on Niche Areas with Faster Commercialization Although AI companies in the application sector face challenges in commercialization, some niche areas have already made breakthroughs. Investors are advised to focus on areas with faster commercialization such as AI+Healthcare and AI+Finance, including companies like Weining Health and Hengsheng Electronics (600570.SH). These companies, with their deep expertise in vertical domains, are expected to be the first to achieve commercial monetization of AI technology. Emerging Fields: Focus on Frontier Directions such as AI+Robotics and AI+Autonomous Driving In addition to traditional AI applications, emerging fields such as AI+Robotics and AI+Autonomous Driving are also worth attention. As technology continues to mature, these fields are expected to become new growth points for the AI industry. Investors are advised to focus on companies in the robotics sector such as Topstar (300607.SZ) and Estun (002747.SZ), as well as companies in the autonomous driving sector such as Hesai Technology (HSAI.US) and Pony.ai. Risk Warnings: Pay Attention to Uncertainties in Technological Iteration and Commercialization Despite the broad prospects of the AI industry, investors should also be aware of related risks. First, AI technology evolves rapidly, and companies may face the risk of their technological approaches being disrupted. Second, commercialization falling short of expectations may lead to valuation adjustments. Finally, factors such as policy changes and increased market competition may also affect the performance of related companies. Therefore, when investing in leading AI stocks, investors should maintain rationality, focus on the core competitiveness and long-term development potential of companies, and avoid blindly chasing high prices. At the same time, it is recommended to adopt a diversified investment strategy, balancing allocations between computing power and application sectors to reduce risks from volatility in a single sector. Overall, in late October, leading AI stocks showed a differentiated pattern, with the computing power sector performing strongly and the application sector relatively weak. As policy dividends continue to be released and the commercialization process accelerates, the AI industry will maintain its high growth momentum. Investors should focus on the dual mainstays of computing power and applications, pay attention to investment opportunities in niche areas, and share the development dividends of the AI era while controlling risks.