Artificial intelligence has been one of the most powerful drivers of growth throughout Wall Street since late 2022, but have investors grown impatient with skyrocketing valuations and circular funding? 

The sheer scale of the AI boom is unprecedented. At present, the Magnificent Seven, a collection of adopters that have seen their market caps swell in the age of artificial intelligence, make up around 33% of the entire S&P 500’s value. 

Despite their exceptionally high market caps, five members of the Magnificent Seven are currently trailing the S&P 500 in 2026. While the index is up 10.9% this year, only Apple (NASDAQ:AAPL) and Alphabet (NASDAQ:GOOGL) are ahead of it, gaining 16.5% and 14.8% over the same period, respectively. 

To make matters worse, three Mag7 stocks are in the red for the calendar year, and evidence is growing that there may be no quick turnaround for the embattled stocks. So what’s going wrong and what could be the long-term impact of AI fatigue? 

Semiconductor Concerns Mount

July opened with semiconductors logging their second straight losing week, with more investors opting to rotate away from the critical hardware for powering the AI boom. 

While some of the money rotated away from semiconductor stocks found its way back into the Magnificent Seven, investors also opted for healthcare, financials, industrials, and materials to provide more resilience for their portfolios. 

One of the driving concerns surrounding semiconductor stocks is the prospect of a compute capacity glut, with reports from Bloomberg suggesting that memory shortages may have peaked in Q2 and are expected to ease in the second half of 2026 and 2027. 

This could see oversupply enter the fray as early as 2028, creating fresh strains on leading industry stocks. 

Semiconductor leaders on South Korea’s KOSPI index appear to have borne the brunt of sinking sentiment, with Samsung (005930.KS) recording a seismic 20% decline in just five days. Despite a strong Nasdaq debut, SK Hynix also fell more than 15% in Seoul amid a widespread market sell-off. 

Given that margin debt climbed 8.5% to a new record of $1.42 trillion in May, its second consecutive monthly increase, leading US semiconductor stocks may be exposed to similar risks, which may accelerate sell-offs in the short term. 

Justifying Heavy Spending

Another key cause for AI fatigue stems from the sustainability of the heavy spending by hyperscalers and whether their seismic artificial intelligence infrastructure projects will ever pay off in the long-run. 

With the average forward price-to-earnings (P/E) ratio of the Magnificent Seven weighing in at around 28x, Wall Street’s largest stocks are considerably ahead of their peers on the S&P 500 on average. 

This means that investors are becoming more susceptible to possible disruptions to growth strategies. Falling token prices can suggest that there may already be excess compute capacity, while emerging competition from China could lead to unforeseen competitors offering cheaper, powerful, and open-source LLMs for users. 

Critically, the Magnificent Seven have collectively announced intentions to spend more than $700 billion on AI capital expenditures in 2026, representing a significant step up from the $400 million that was spent last year. 

However, greater investments in AI mean that companies will have to spend more time securing their ROI, and any bumps in the road could lead to severe disruption. 

This opens the door to the prospect of overbuilding, and the assumption of demand can bring far more risks to Wall Street’s most valuable stocks over time. 

AI Concessions

There are also still plenty of arguments to be made that the sheer potential of the artificial intelligence boom is too strong to overstate. 

Last year, PwC forecasted that AI adoption could boost global GDP by an additional 15% by 2035. It was also noted that an economic shift was already underway, with around $7.1 trillion in revenues estimated to have changed hands between companies in 2025 alone, even when taking tariffs into account. 

It’s with this in mind that the full extent of the AI boom can be recognized. Where new innovations are accelerating digital transformation within countless industries. 

Even in compliance, we’re seeing new efficiencies emerge where machine learning is capable of automating the monitoring of risks with around-the-clock supervision. 

Considering that The Washington Post suggested last year that investments in data center capacity throughout the US may have contributed 0.7% to GDP growth in 2025, the rise of AI fatigue may not be a signifier of a permanent market downturn on Wall Street. 

What’s Next for AI on Wall Street?

The big risk is that AI fatigue could contribute to a selling event that’s similar in scale to Samsung’s and SK Hynix’s losses on the KOSPI, where a lack of sentiment leads to sell-offs at the next significant sign of stress. 

This is likely to lead to short-term volatility for the AI-oriented Magnificent Seven and the possibility of declines on the back of any less-than-stellar earnings reports for Q2. 

Looking to the long term, the outlook is less clear. There’s still plenty of optimism for the future role that AI will play in supporting the economy, which could provide more tailwinds for pioneering stocks and the S&P 500 as a whole over time. 

Disclosure: On the date of publication, Dmytro Spilka did not hold (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer. Dmytro Spilka does not intend to make a trade in any of the securities mentioned above in the next 72 hours.

Benzinga Disclaimer: This article is from an unpaid external contributor. It does not represent Benzinga’s reporting and has not been edited for content or accuracy.