As the third quarter of 2026 approaches its end, the AI concept stock market presents an unprecedented differentiation pattern. According to the latest market data, the overall performance of AI concept stocks at the end of September shows a clear "divergent" trend: traditional computing power chains continue to adjust, while AI+financial innovation sectors represented by DeFAI application layer, smart risk control, and RWA tracks have strengthened against the trend, becoming new safe havens for institutional capital. This article will conduct an in-depth analysis of the current capital flow changes in the AI concept stock market, sector rotation logic, and future investment opportunities, providing comprehensive market insights to investors.
Computing Power Chain Adjustment Continues, Valuation System Reconstructs
Since entering September, the AI computing power chain sector has experienced continuous adjustments, becoming the main factor dragging down the overall performance of AI concept stocks. Data shows that the computing power chain index fell by about 12.3% in September, with the stock prices of several leading computing power companies dropping by more than 15%. This adjustment trend formed a continuous effect with the computing power chain selling triggered by NVIDIA's GB300 delay at the end of August.
Analysts point out that there are three main reasons behind the computing power chain adjustment: first, signals of global AI infrastructure capital expenditure peaking have already emerged, with the growth rate of major tech giants' procurement of computing hardware slowing down; second, the valuation of computing power concepts has already discounted the growth expectations for the next 2-3 years, showing obvious valuation bubbles; finally, as AI application layer innovation accelerates, market attention is shifting from "computing power arms race" to "application value capture".
"The peak of computing power chain valuation is an inevitable trend," said an AI industry analyst at a leading securities firm. "Over the past year, the market has been overly enthusiastic about computing power concepts, neglecting the actual value of AI application implementation. As major model providers like OpenAI significantly lower prices, the cost-effectiveness ratio of AI applications has improved significantly, which will inevitably lead to a reassessment of market demand for computing power."
Computing Power Chain Shows Internal Differentiation
Notably, even against the backdrop of overall adjustment, the computing power chain has also shown clear differentiation. High-performance GPUs, AI chips, and other core computing hardware have maintained relative strength, while computing infrastructure such as edge computing and ordinary AI servers have seen larger adjustments. This indicates that the market's perception of computing resources is shifting from "general computing power" to "high-quality computing power".
Data shows that in late September, the institutional holding ratio of high-performance GPU manufacturers like NVIDIA and AMD only decreased by 2-3%, while the institutional holdings of edge computing-related companies decreased by more than 15%. This differentiation trend reflects that although the market maintains a cautious attitude toward the computing power sector as a whole, the demand for core computing resources remains resilient.
DeFAI Application Layer Emerges Prominently, Institutional Capital Accelerates Layout
In stark contrast to the computing power chain, the DeFAI (Decentralized Finance + AI) application layer sector has seen a strong rebound at the end of September, becoming the most star sector in AI concept stocks. Data shows that the DeFAI concept stock index rose by about 18.7% in September, with sub-sectors such as AI lending and smart risk control increasing by more than 20%.
"The rise of the DeFAI application layer marks a significant shift in AI investment logic," said a quantitative investment fund manager. "In the past, the market has been overly focused on AI breakthroughs while neglecting the actual application value of AI in the financial sector. As AI models become increasingly mature in application to core financial segments such as credit assessment, risk pricing, and asset pricing, AI+finance is experiencing explosive growth."
AI Lending Track Becomes New Capital Favorite
Among the DeFAI application layer, the AI lending track has performed most impressively. Several leading AI lending platforms set new records in financing in September, with a total scale exceeding $500 million. These funds mainly came from traditional financial institutions and sovereign funds, indicating that traditional financial capital is accelerating penetration into the AI+finance sector.
The core competitiveness of AI lending platforms lies in the on-chain credit assessment system built through machine learning algorithms. Unlike traditional lending that relies on centralized credit assessment, AI lending platforms can integrate on-chain behavior data, off-chain data, and multi-dimensional cross-validation to build more comprehensive and accurate credit models, thereby achieving more precise risk pricing.
"AI lending is reconstructing the credit system of traditional finance," said the CEO of an AI lending platform. "Through algorithmic credit, we can provide financial services to long-tail users that cannot be covered by traditional financial institutions, while reducing default risks through smart risk control. This win-win model is gaining widespread market recognition."
Smart Risk Control Becomes New Valuation Anchor
The smart risk control sector also performed strongly at the end of September, with the stock prices of several smart risk control companies reaching new highs. Institutional data shows that in late September, smart risk control concept stocks received more than 2 billion yuan in net capital inflow, becoming the sector with the most capital inflow among AI concept stocks.
The core value of smart risk control enterprises lies in their ability to monitor on-chain financial risks in real-time through AI technology, providing early warnings of potential risk points. Unlike traditional risk control that relies on historical data, AI smart risk control can analyze on-chain behavior patterns in real-time, identify abnormal transactions and potential risks, thereby achieving risk prevention rather than post-processing.
"As DeFi protocol scales continue to expand, on-chain financial risks are becoming increasingly complex, and traditional risk control methods are struggling to cope," said the CTO of a smart risk control company. "Our AI system can analyze millions of on-chain data points in real-time, identify potential risk patterns, and provide comprehensive risk protection for DeFi protocols. This capability is becoming a necessity for DeFi protocols."
RWA Track Experiences Explosive Growth
The real-world asset (RWA) on-chain tokenization track has experienced explosive growth at the end of September, becoming one of the fastest-growing sectors in AI concept stocks. Data shows that the RWA concept stock index has increased by more than 25% in September, with several RWA platforms securing large-scale financing.
The core value of the RWA track lies in tokenizing real-world assets (such as real estate, bonds, equities, etc.) through technical means, thereby improving asset liquidity and divisibility. The application of AI technology in the RWA field is mainly reflected in asset valuation, risk pricing, and compliance monitoring, providing technical support for the healthy development of RWA.
"BlackRock's recent implementation of the first on-chain tokenization of RWA credit assets marks the formal recognition of the RWA track by traditional financial giants," said the founder of an RWA platform. "As AI technology becomes increasingly mature in asset valuation and risk pricing, the RWA track is experiencing explosive growth and is expected to become a trillion-dollar market in the next 3-5 years."
Institutional Capital Accelerates Layout in RWA Track
At the end of September, several traditional financial institutions announced their entry into the RWA track, with Wall Street giants including Goldman Sachs and Morgan Stanley launching RWA-related products. The entry of these institutions has brought substantial capital and resources to the RWA track, accelerating its large-scale development.
"The explosion of the RWA track is not accidental but an inevitable trend in the development of financial technology," said an investment bank analyst. "AI technology solves the core pain points in the RWA field - asset valuation and risk pricing, which enables the safe and efficient on-chain tokenization of real-world assets, providing a feasible path for the integration of traditional finance and blockchain."
Market Sentiment Shifts to "Pragmatism," Investment Logic Reconstructs
With the evolution of the AI concept stock market pattern at the end of September, market sentiment is shifting from "computing power faith" to "pragmatism." Investors are paying more attention to the actual application value and commercial implementation capabilities of AI technology, rather than purely technological breakthroughs and computing scale.
"AI investment logic is undergoing fundamental reconstruction," said a partner of an AI investment fund. "Over the past year, the market has been overly enthusiastic about computing power concepts, neglecting the actual value of AI application implementation. As AI technology becomes increasingly mature in fields such as finance, healthcare, and education, the market is reassessing the actual value of AI enterprises. Those companies that can transform AI technology into actual commercial value will receive more favor."
Investment Strategy Shifts to "Value Capture"
In terms of investment strategy, institutions are shifting from "computing power arms race" to "application value capture." Data shows that in late September, the financing amount of AI application layer companies exceeded that of computing power companies for the first time, indicating that capital is flowing toward the AI application field at an accelerated pace.
"The golden inflection point of AI investment has arrived," said a head of a well-known investment institution. "From the computing power bubble to the value reevaluation of DeFAI applications, it marks that AI investment has entered a new stage. In the future, those companies that can deeply integrate AI technology with the real economy and solve practical problems will gain the largest development space."
Future Investment Opportunities and Risk Warnings
Looking ahead, the AI concept stock market will present the following investment opportunities and risks:
Investment Opportunities
- AI Lending Track: With the improvement of algorithmic credit systems, AI lending platforms will provide financial services to long-tail users that cannot be covered by traditional financial institutions, with broad market space.
- Smart Risk Control: As DeFi protocol scales continue to expand, smart risk control will become a necessity for the DeFi ecosystem, and related companies will experience explosive growth.
- RWA Track: Traditional financial giants are accelerating their layout in the RWA track, and the application of AI technology in asset valuation and risk pricing will promote the large-scale development of RWA.
- AI Agent: The commercial implementation of autonomous financial decision-making AI Agents will reshape the DeFi lending landscape, and the application layer investment logic will undergo fundamental changes.
Risk Warnings
- Regulatory Risks: With the rapid development of AI+finance, regulatory policies may become stricter, and related companies need to closely monitor regulatory developments.
- Technical Risks: AI technology is still in a rapid development stage, and technical issues such as model security and data privacy have not been fully resolved.
- Market Risks: The valuation of AI concept stocks is still at a relatively high level, and market fluctuations may increase investor risks.
- Competitive Risks: As the AI+finance track heats up, competition will become increasingly fierce, and companies need to maintain technological innovation advantages.
Conclusion: From Computing Power Bubble to Value Reevaluation of DeFAI Applications
The differentiation pattern of the AI concept stock market at the end of September 2026 marks a significant shift in AI investment logic. From the computing power bubble to the value reevaluation of DeFAI applications, AI investment is shifting from "technology worship" to "value capture." In this transformation process, AI+financial innovation fields such as AI lending, smart risk control, and RWA tracks will become investment hotspots.
For investors, grasping the shift in AI investment logic is crucial. In the future, those companies that can deeply integrate AI technology with the real economy and solve practical problems will gain the largest development space. At the same time, investors also need to pay attention to regulatory risks, technical risks, and market risks, and do a good job of risk control while seizing investment opportunities.
"The golden inflection point of AI investment has arrived," concluded a well-known AI investor. "From the computing power arms race to the explosion of DeFAI applications, it marks that AI investment has entered a new stage. In the next 3-5 years, AI+finance will become the core field for AI application implementation, and related companies will experience explosive growth. Investors need to adjust their investment strategies and focus on the actual application value and commercial implementation capabilities of AI technology."
