Is the pullback in AI chip stocks a buying opportunity? Analysis of three core drivers in the second half of 2026

On July 7, 2026, the U.S. stock market saw a landmark trading day— the Dow Jones Industrial Average closed above the 53,000-point mark for the first time, ending at 53,055.91 points, up 0.29%; the S&P 500 closed at 7,537.43 points, up 0.72%; and the Nasdaq Composite surged 1.12% to 26,121.16 points. The core force driving this rally is the AI chip sector, which had been facing sell-offs for several consecutive days.

That day, the semiconductor sector rebounded strongly. The Philadelphia Semiconductor Index rose 2.17% to 12,900.14 points. Advanced Micro Devices (AMD) jumped 6.61%, closing at $552.05; TSMC ADR rose 4.06% to close at $451.79; Broadcom rose 3.73% to $373.9; and NVIDIA edged up 0.37%, closing at $195.55.

However, just a few days earlier, market sentiment was completely different. In early July, the semiconductor sector underwent a sharp pullback— the Philadelphia Semiconductor Index plunged 6.27% and 5.44% on July 1 and 2, respectively, over two trading days, for a cumulative drop of more than 11%. The VanEck Semiconductor ETF fell by more than 5%, Micron dropped 11%, Intel dropped 9%, and AMD gave back 7%. After setting a record-best performance in the second quarter, the AI chip sector suddenly hit the brakes.

After a big rally came an even bigger drop—was it a signal of a trend reversal, or a healthy pullback during the rise? What will drive the next upswing? Let’s analyze it from three dimensions: market data, institutional judgments, and industry logic.

This Pullback: An Inevitable Adjustment After a Blow-Off Rally

To understand the nature of the pullback, first it’s necessary to look back at the scale of the prior gains. In 2026’s second quarter, the Philadelphia Semiconductor Index surged 88%. Among the “winners list” for AI trades in the first half of the year, the storage sector rose by a cumulative 318.49%, topping all sub-industries; computer hardware rose 165%; and semiconductor equipment and materials rose 129%. After such huge gains, some period of profit-taking and technical consolidation is in line with the basic laws of how markets operate.

As for the triggers of the pullback, multiple concerns overlapped within the same time window.

First, concerns about an oversupply of computing power take hold. In early July, the market reported that Meta is planning to roll out cloud computing services, renting out its excess AI computing power to external customers. This sparked widespread concern about “an oversupply of computing power.” Although Meta’s stock price rose by about 10% on July 1 on the news, investors quickly began re-evaluating the potential impact of this event on the overall supply-and-demand balance of AI computing power. In a subsequent research report, CICC (China Citic Securities) pointed out that Meta’s specific case should not be over-interpreted as a sign of an industry turning point, and that the long-term driver of AI computing power demand had not been harmed by a single action. But at elevated valuations, the market’s abnormal sensitivity to negative signals amplified short-term volatility.

Second, skepticism about AI profitability and realizing returns. A strategist at BofA Securities Japan said in a research report: “The profitability of AI investment remains a risk factor that needs to be monitored.” Persistent concerns about whether massive AI investments can sustainly realize returns formed a deeper underlying factor weighing on valuations.

Third, hedge funds continue trimming positions. Goldman Sachs data shows that the technology sector has been the U.S. stock sector most heavily net sold by hedge funds for four consecutive weeks. Continued capital outflows amplified downward pressure on the sector.

Fourth, worries about competition in the memory market. The market fears that the rise of China’s memory chip manufacturers could worsen conditions in the memory market. Meanwhile, position adjustments in leveraged semiconductor ETFs listed in South Korea triggered large-scale profit-taking.

Overall, this pullback is the result of a convergence of multiple factors—profit-taking pressure driven by the excessive gains earlier on, short-term concerns about the AI computing power supply-and-demand landscape, continued capital outflows, and the market’s high sensitivity to sentiment in a high-valuation environment.

Institutional Consensus: A “Healthy Reset,” Not a Trend Reversal

In the face of this adjustment, multiple mainstream investment institutions delivered clear views.

JPMorgan: The semiconductor upcycle is far from over. In a client report released on July 6, JPMorgan strategist Mislav Matejka explicitly stated that the recent weak performance in semiconductor stocks should be viewed as a buying opportunity. The core judgment is that “the semiconductor upcycle has not yet topped out, and effective supply is unlikely to be released on a large scale before 2028.” JPMorgan analyst Harlan Sur further pointed out that AI chips have a large backlog of orders, with order volumes far exceeding current production capacity, and revenue visibility extending far into the future. On sector allocation, JPMorgan’s priority order is “semiconductors outperform hyperscale cloud providers, and hyperscale cloud providers outperform AI risk-type names.”

Bank of America: Summer pullback, autumn rebound. In a report dated July 6, Bank of America Securities analyst Vivek Arya noted that after the Philadelphia Semiconductor Index surged 88% in the second quarter, it had already pulled back 11% in the third quarter, which closely matches the pattern of the sector’s historically weakest seasonal period. The bank characterized this pullback as a “healthy reset” rather than a trend reversal. BofA expects that as market visibility for 2027 cloud spending improves in the second half of 2026, related stocks—including memory chips, computing chips, semiconductor capital equipment, optical components, and networking equipment—will regain upward momentum.

Korean analysts: A short-term speed adjustment, not a worsening of fundamentals. KB Securities research head Kim Dong-won attributed the pullback to short-term overheating and portfolio rebalancing rather than a deterioration in fundamentals, saying that the adjustment reflects normalization after the first-half rally.

Domestic institutions: The industry upcycle is still ongoing. Wang Guizhong, Director of Great Tech Research at Harvest Fund, said that after the sector’s sustained rise, volatility is inevitable, but there is no systemic risk in the current AI tech track. The fundamentals of the AI industry continue to improve, with solid industry iteration and performance delivery. Cheng Xi, a fund manager at E Fund, pointed out that as AI model performance continues to improve and downstream application scenarios fully emerge, concerns about the AI investment return on which the market focused at the beginning of the year have gradually dissipated.

Taken together across institutions, the market widely characterizes this pullback as a technical adjustment rather than a structural shift. The core logic is that the fundamental support for the AI-driven semiconductor upcycle has not changed.

The Three Core Drivers of the Next Upswing

If this pullback is a “healthy reset,” then what will drive the next upswing? Based on industry trends and institutional judgments, the following three directions form the most core drivers.

Driver One: Structural Supply-and-Demand Imbalance in Memory Chips

Memory chips are the sub-sector with the biggest gain in this AI cycle and also the area where supply-and-demand contradictions are most pronounced.

On the supply side, the three major original equipment manufacturers—Samsung, SK Hynix, and Micron—are shifting most of their production capacity to High Bandwidth Memory (HBM). Traditional DRAM supply is constrained, and even the fastest ramp-up of new capacity will not be until 2027. TrendForce data shows that in the second quarter of 2026, contract prices for traditional DRAM rose 58% quarter over quarter to 63%, and NAND flash contract prices rose 70% to 75% quarter over quarter. Entering the third quarter, the overall DRAM landscape remains extremely tight, and contract prices are expected to rise 13% to 18% quarter over quarter.

On the demand side, the expansion in AI inference workloads is bringing general-purpose DRAM back to the center stage. AI servers have become the largest application market for DRAM, with server demand accounting for more than 50% of total DRAM demand. Micron has already sold out all of its HBM supply before 2026, and has locked in buyers through multi-year contracts.

The depth and persistence of the supply-and-demand mismatch provide a solid foundation for higher memory chip prices and performance realization—this is also the core logic behind why multiple institutions list it as their top priority allocation direction.

Driver Two: From Training to Inference—A Structural Upgrade in AI Computing Demand

The AI industry is undergoing a critical transition from “training-driven” to “inference-driven.” In the first half of 2026, global AI Token usage grew 4x year over year; inference demand has already exceeded training demand by 8x, becoming the main driver of computing power growth.

The significance of this shift lies in the following: training demand is concentrated among a small number of major model companies, with high concentration and cyclicality; whereas inference demand is spread across a wide range of application scenarios, offering stronger dispersion, persistence, and growth resilience. The explosive growth in Token volume is driving strong demand for customized chips such as ASICs. Institutional forecasts suggest that the number of ASICs used by Google, Amazon, Meta, OpenAI, and Microsoft will see explosive growth from 2026 to 2027.

The rise in inference demand also means that the demand structure for AI chips is evolving from “procurement by a handful of giants” to “widespread deployment across the entire industry,” with both the breadth and depth of demand increasing. This trend provides a more solid demand base for long-term growth in the AI chip market.

Driver Three: Hyperscalers’ Capital Expenditure Expansion

The capital expenditure of hyperscale cloud service providers (Microsoft, Google, Amazon, Meta, etc.) is the direct engine for AI chip demand. JPMorgan data shows that these companies’ expected capital expenditure for 2026 has been raised to 130 billion U.S. dollars, with total spending for the full year expected to exceed 650 billion U.S. dollars. A forecast released by Goldman Sachs in June 2026 further shows that the total capital expenditure of Alphabet, Amazon, Microsoft, and Meta this year will reach 725 billion U.S. dollars, a substantial increase from 410 billion U.S. dollars in 2025.

A significant portion of this capital expenditure is directly converted into chip procurement orders, making semiconductor companies the most direct beneficiaries of the AI capital expenditure wave. Mark Haefele, Chief Investment Office at UBS, noted that if there are signs the spending plans of the cloud computing giants remain unchanged, it will help reassure investors and reinforce their belief that demand for AI infrastructure remains sustainable.

From a longer-term perspective, JPMorgan expects that global stock markets will set new highs in the second half of 2026. Supporting factors include strong earnings prospects, easing inflationary pressures, and relatively light investor positioning. AI is “unlikely to be the only theme in the second half of the year,” but there is no doubt it is the most core structural storyline.

Potential Risk Variables That Need Attention

While analyzing the drivers behind the rally, it is also necessary to objectively review the risk factors that may constrain market performance.

Dual pressure from valuations and expectations. When both valuations and expectations are high, any disappointment can be amplified. Tech stock valuations are already elevated, making them exceptionally sensitive to negative signals. The Philadelphia Semiconductor Index has already pulled back by about 11% in the third quarter, but even after the adjustment, overall valuation levels remain at historical highs.

Ongoing validation of AI investment returns. Market concerns about whether massive AI investments can deliver returns always remain. If the financial reports of major cloud service providers show that the input-output ratio of AI is worse than expected, it could trigger another round of valuation corrections.

Geopolitical and supply chain risks. JPMorgan strategists also acknowledge that “there remains a risk that geopolitical tensions could heat up again.” The concentration of chip supply chains and uncertainty in global political and economic conditions are external variables that cannot be ignored.

Potential impact of the interest rate environment. Core PCE remains at a high level of 3.4% year over year. Structural cost pressures brought by AI computing infrastructure have delayed the Federal Reserve’s rate-cutting cycle. The suppressing effect of a high interest-rate environment on high-valuation tech stocks is worth sustained attention.

Conclusion

On July 7, 2026, the Dow Jones Index first topped 53,000 points, and the AI chip sector, after experiencing a short-term, sharp pullback, saw a strong rebound. The market performance on this day aptly reflects the key tension in the current AI chip sector—competition between short-term fluctuations and long-term trends.

From the standpoint of industry fundamentals, the three core underlying logics driving the continued upward trend in the AI chip industry are: the structural supply-and-demand imbalance in memory chips, the explosive growth in inference demand, and the expansion of capital expenditure by hyperscale cloud service providers. Mainstream institutions generally characterize this pullback as a “healthy reset” rather than a trend reversal, believing that the semiconductor upcycle is far from over.

Of course, in a high-valuation environment, the market is unusually sensitive to negative signals. Continued validation of AI investment returns, geopolitical risks, and uncertainty in the interest rate environment will all act as catalysts for short-term volatility. But in terms of industry trends, the length and strength of the AI-driven semiconductor super upcycle are already surpassing previous industry recoveries driven by consumer electronics and automobiles. For market participants, distinguishing short-term volatility from long-term trends may be the clearest awareness that is most needed in this market full of divergence.

FAQ

Q: What are the main reasons for this round of decline in AI chip stocks?

This decline is the result of multiple factors compounding: profit-taking pressure triggered by the oversized gains earlier on; Meta renting out idle AI computing power, sparking concerns about “an oversupply of computing power”; hedge funds net selling the technology sector for four consecutive weeks; ongoing uncertainty about whether massive AI investments can realize returns; and rising concerns about competition in the memory market. Several institutions believe these factors are more disruptions at the trading and technical levels rather than a deterioration in industry fundamentals.

Q: Why does JPMorgan think the chip stock pullback is a buying opportunity?

JPMorgan’s core judgment is that the semiconductor upcycle has not peaked, and effective supply is unlikely to be released on a large scale before 2028. AI chips have a large backlog of orders, with order volumes far exceeding current production capacity, and revenue visibility extends far into the future. In addition, hyperscale cloud service providers are expected to exceed 650 billion U.S. dollars in capital expenditure in 2026, which directly translates into chip procurement orders.

Q: How long will memory chip price increases last?

TrendForce data shows that in the third quarter of 2026, DRAM contract prices are expected to rise 13% to 18% quarter over quarter. The three major manufacturers will shift most of their production capacity to HBM, constraining traditional DRAM supply, and the ramp-up of new capacity will only start to scale by 2027 at the earliest. All of Micron’s HBM supply before 2026 has already been sold out. The supply-and-demand mismatch is expected to persist at least until 2027.

Q: What is the core driver behind the next upswing in AI chip stocks?

Three core drivers: first, the structural supply-and-demand imbalance in memory chips, with the price increase trend clearly established; second, the AI industry shifting from training-driven to inference-driven, with inference demand already 8x training demand and the demand structure upgrading; third, continued expansion in capital expenditure by hyperscale cloud service providers, which is expected to exceed 725 billion U.S. dollars in 2026. Together, these form the fundamental support for continued upward momentum in the AI chip industry.

Q: Is there a bubble risk in the current AI chip sector?

Wang Guizhong of Harvest Fund believes that bubbles often stem from the pace of industry development lagging behind what the market imagines. At present, however, the AI industry fundamentals continue to improve, with solid industry iteration and performance delivery. Cheng Xi of E Fund points out that the number of AI application users and usage rates have surged, monetization speed has exceeded market expectations, and the issue of AI investment return has gradually been resolved. However, it should be noted that tech stock valuations are high, making them extremely sensitive to negative signals, and short-term volatility risks cannot be ignored.