AI Concept Stocks Market Analysis for Second Week of August: Computing Chain Valuation Restructuring and DeFAI Application Layer Fund Shift

AI Concept Stocks Market Panorama for Second Week of August: Fund Flows Reveal New Market Logic

In the second week of August 2026, the AI concept stock market showed significant structural differentiation. As the news of NVIDIA's GB300 chip delay continued to unfold, computing chain related stock valuations continuously sought bottom levels, while DeFAI application layers became new favorites for funds, with smart risk control and RWA tracks receiving institutional counter-cyclical positions. This differentiation not only reflects short-term market sentiment but reveals a fundamental shift in AI investment logic—from purely pursuing computing scale to focusing on practical application scenarios and commercial value.

Overall Market Performance: A Tale of Two Extremes

As of the close on August 12, the AI concept index rose slightly by 0.8% for the week, but internal differentiation was extremely significant. The computing chain sector fell by 4.2% during the week, while the DeFAI application layer rose by 5.7%, forming a stark contrast in performance. In terms of market trading volume, AI concept stocks overall shrank by 12% compared to the previous week, but DeFAI-related counter-trend volume increased by 15%, indicating that funds are shifting from the computing chain to the application layer.

From a sector rotation perspective, the AI concept stock market is experiencing a shift from "hardware first" to "application-led." This transformation is not accidental but based on the internal logic of industrial development. As AI infrastructure gradually matures, market attention is turning to practical application scenarios and commercialization, especially in segments that can generate stable cash flows.

Computing Chain: Valuation Restructuring in Progress

The computing chain sector continued to face pressure this week, with related stocks in AI chip design, server manufacturing, and cooling solutions generally falling. The ongoing impact of NVIDIA's GB300 chip delay has led to a revaluation of the entire industry chain. Market analysts generally believe that this event marks the beginning of a rational adjustment period for AI computing power investment, with over-hyped valuation bubbles gradually being squeezed out.

From a valuation perspective, the computing chain sector currently has an average P/E ratio of about 65 times, down 30% from its high at the beginning of the year but still above historical averages. Some institutional investors believe that as AI application scenarios become more diverse and computing power demands diversify, a model solely dependent on high-end GPUs will be unsustainable, and the computing power industry chain needs more balanced development.

Notably, the computing power leasing leader released its interim earnings forecast this week, showing a 35% year-on-year increase in revenue, but profit growth slowed to 15%, raising market concerns about computing power utilization and business models. This data further validates the trend of the computing chain shifting from "scale expansion" to "efficiency improvement."

DeFAI Application Layer: New Fund Favorite and Value Reassessment

In stark contrast to the computing chain, the DeFAI application layer performed strongly this week, becoming a hot spot for market funds. AI-driven encrypted lending protocols, smart risk control systems, and RWA asset tokenization all saw gains, with AI risk control concept stocks rising more than 7% during the week.

In terms of fund flows, large institutions are accelerating their positions in the DeFAI track. According to market data, among the top ten AI concept stocks this week, six were DeFAI-related, receiving a combined net inflow of over 2 billion yuan. This change in fund flow reflects institutional investors' recognition of the commercial value of the AI application layer.

BlackRock announced this week the completion of the first RWA on-chain credit asset tokenization transaction, tokenizing traditional credit assets on the blockchain after evaluation by an AI risk control model. This landmark event not only validates the feasibility of the RWA model but has also injected strong momentum into the DeFAI track, with related concept stocks rising accordingly.

Smart Risk Control: Value Validation of AI Applications

Smart risk control became this week's market focus, with related concept stocks leading in gains. As the DeFi market expands, risk control has become a key bottleneck for industry development, and AI technology, with its data processing and pattern recognition advantages, is becoming an effective tool to solve this problem.

On-chain liquidation warning robots became a hot topic in the market this week. These AI systems can monitor on-chain data in real time, identify potential risks through machine learning models, and provide early warnings of possible liquidation events, offering valuable decision-making basis for investors. Market data shows that lending protocols using AI risk control have bad debt rates more than 40% lower than traditional models, significantly enhancing asset security.

The news that regulatory sandboxes have for the first time included on-chain credit data has further boosted AI risk control concept stocks. This initiative shows that regulators are actively exploring how to combine AI technology with traditional financial regulatory frameworks, providing new ideas for the compliant development of the DeFAI industry.

RWA Track: Bridging Traditional Finance and the Crypto World

RWA (Real World Assets) tokenization made significant progress this week, becoming a highlight in AI concept stocks. RWA enables real-world assets (such as real estate, bonds, credit, etc.) to be tokenized, allowing them to be traded and financed on the blockchain, thus breaking down barriers between traditional finance and the crypto world.

The application of AI technology in the RWA field is mainly reflected in asset valuation, risk pricing, and compliance monitoring. By analyzing large amounts of historical data through machine learning models, AI systems can more accurately assess asset values, formulate reasonable risk pricing, and monitor transaction compliance in real time, significantly improving the efficiency and security of the RWA market.

Market analysts believe that the RWA track has trillion-level market potential, and AI technology will be a key driving force for development in this field. As the regulatory environment gradually clarifies and technology matures, RWA is expected to become the next explosive point in the DeFAI industry.

Institutional Movements: Counter-Cyclical Layout and Value Discovery

Facing the structural differentiation of AI concept stocks, institutional investors are adopting different strategies. Some institutions are choosing to reduce positions in overvalued computing chain stocks and instead add to undervalued DeFAI application layer stocks, especially high-quality ones with stable cash flows and clear business models.

According to market data, the operations of the top five institutional investors in AI concept stocks this week showed clear differentiation: reducing computing chain stocks by a total of 1.5 billion yuan while increasing DeFAI-related stocks by over 2 billion yuan, with a net increase of 500 million yuan. This change in fund flow reflects institutional investors' rethinking of AI investment logic.

Notably, some controlling shareholders of AI concept stocks have been increasing their holdings this week, taking practical action to support industry earnings reports. This "real money" increase not only enhances market confidence but also shows that industry insiders recognize the long-term value of the AI application layer.

Leading Stock Analysis: Structural Opportunities in Differentiation

This week, the performance of leading AI concept stocks showed clear differentiation, with computing chain leaders continuing to adjust while DeFAI application layer leaders led the sector. This differentiation reflects market differences in recognition of different business models and profitability.

In the computing chain sector, the AI computing power leasing leader released its interim earnings forecast this week, showing a 35% year-on-year increase in revenue, but profit growth slowed to 15%, raising market concerns about computing power utilization and business models. In contrast, DeFAI application layer leaders showed strong growth momentum, with several companies reporting revenue growth of over 50% and profit growth reaching more than 70%.

From a valuation perspective, the average P/E ratio of DeFAI application layer leaders is about 45 times, which is still higher than traditional financial sectors but has a clear advantage over the computing chain sector's 65 times. This indicates that the market has begun to differentiate pricing for business models and growth potential across different segments.

Outlook: Investment Logic Restructuring and Opportunities

Looking ahead, the AI concept stock market may continue to show structural differentiation. As AI investment logic shifts from "technology-driven" to "application-driven," those that can effectively combine AI technology with practical application scenarios and generate stable cash flows will gain market favor.

In terms of investment opportunities, the DeFAI application layer, smart risk control, and RWA track may become market hotspots in the next phase. These areas not only have clear business models and growth potential but can also benefit from efficiency improvements and cost reductions brought by AI technology, forming a virtuous cycle.

In terms of risks, investors need to pay attention to regulatory policy changes, technology iteration risks, and increased market competition. Especially in the DeFAI field, changes in regulatory policies may have a significant impact on industry development, and investors need to closely monitor related developments.

Overall, the AI concept stock market is at a critical turning point from "hardware first" to "application-led." Investors should rationally view market differentiation, focus on high-quality stocks with real commercial value and growth potential, and avoid blindly chasing short-term hotspots.

Investment Strategy Recommendations: Seizing Structural Opportunities in Differentiation

Based on current market conditions and industry development trends, we offer the following investment strategy recommendations:

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1. Focus on DeFAI Application Layer Opportunities: As funds shift from the computing chain to the application layer, DeFAI-related stocks may face valuation reassessment opportunities. Investors can focus on high-quality stocks with stable cash flows, clear business models, and competitive advantages.
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2. Position in Smart Risk Control Track: As the DeFi market expands, risk control will become a key bottleneck for industry development. AI-driven smart risk control systems, with their technical advantages, are expected to dominate this field, with related concept stocks having long-term investment value.
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4. Seize RWA Development Opportunities: As a bridge connecting traditional finance and the crypto world, RWA tokenization has huge market potential. As the regulatory environment gradually clarifies and technology matures, the RWA track is expected to experience explosive growth.
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5. Monitor Institutional Movements: The fund flows of large institutions often indicate future market direction. Investors can closely monitor changes in institutional investors' positions and operations to seize market opportunities.
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6. Control Risks and Diversify Investments: The AI concept stock market is highly volatile, and investors should control position sizes, diversify investments, and avoid over-concentrating funds in a single stock or sector.
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In summary, the market performance of AI concept stocks in the second week of August reveals a fundamental shift in AI investment logic. From purely pursuing computing scale to focusing on practical application scenarios and commercial value, this shift not only reflects the market's deepening understanding of AI technology but also points investors toward future investment directions. Finding opportunities in differentiation and grasping trends in change will be the key to successful AI investing.