Why did AI stocks plunge? Lawmakers again propose permanently banning superintelligence, investment returns spark market concerns, Democrats retaking Congress heats up regulatory narrative

BlockBeats news, November 5 - AI-related stocks in the US market experienced another sharp decline during intraday trading, with several star stocks falling over 10%. According to BIT stock platform data, the S&P 500 index expanded its decline to 2%, the Dow fell nearly 1%, and the Nasdaq dropped over 3.5%. The US memory sector saw further deepening losses, with SanDisk plunging over 17% and Micron falling more than 12%. This round of decline is not an isolated single-day event, but a continuation and deepening of the AI and semiconductor pullback since late October under post-election policy expectations. The main reasons for the decline widely discussed in the market are summarized below.

Wall Street has recently continued to question whether the massive AI infrastructure investments by tech giants can translate into matching revenue and profits. JPMorgan estimates that global AI-related spending this year is approximately $900 billion, and cumulative spending could reach about $5.5 trillion by 2030. Trefis noted that Amazon, Alphabet, and others still claim strong AI demand, but the valuation investors are willing to pay for growth has significantly decreased; "what has changed is not demand, but the price to pay for this bill." Ted Parkhill, founder of Incline Investment Management, stated that the market is shifting from the promise of AI to the price of AI.

Earnings and guidance amplified concerns. According to Reuters analysis, recent results or outlooks from Alphabet, Amazon, Intel, and others disappointed the market: Alphabet saw its largest single-day drop since listing after advertising and search revenue fell short of expectations; Intel fell nearly 29% in a single day after guidance missed expectations. Around October 30, the Nasdaq 100 fell about 3.5%, with semiconductor-related products seeing deeper single-day declines. The S&P technology sector fell about 6.8% overall in October. Meanwhile, institutions are focused on the high ratio of capital expenditure to operating cash flow at hyperscale cloud providers, as well as the debt-driven expansion model of some neoclouds; data such as Amazon's trailing free cash flow turning negative have been repeatedly cited, with the market concerned that a slowdown in downstream spending pace will impact orders for suppliers like Nvidia.

Valuation and capital reallocation also constitute pressure. The Nasdaq 100 had fallen over 10% cumulatively from its October 6 high around November 3, entering a technical correction for the third time this year. Over the past month or so, Intel, CoreWeave, Marvell, AMD, Nvidia, and others have seen significant declines, while Apple, Microsoft, and others have been relatively resilient or even hit new highs, indicating that selling is more concentrated in names dependent on current AI spending intensity. The 10-year US Treasury yield remains around 4.9%, further suppressing the pricing of longer-duration growth stocks. After the Democrats' midterm election landslide on November 4, the Dow surged over 3%, but Nvidia, Tesla, and the data center and power equipment chain fell against the trend, showing a rotation characteristic of "leaving AI infrastructure and turning to other sectors."

Policy and local construction constraints represent another key theme. After Democrats regained control of Congress, the market is concerned that federal and state-level scrutiny over data center approvals, power usage, and community impact will intensify; in electoral races in states like Texas, "pausing or suspending data center construction" had been written into campaign platforms. UBS analysts estimate that about 30% of the expected new U.S. data center capacity in 2028 may come under pressure due to potential construction halts.

After Democrats retook Congress, the regulatory narrative further intensified. The day after the election victory, Democratic Representative Yassamin Ansari publicly called for Democrats, once in power, to prioritize pausing advanced AI research and development, strengthening industry regulation, and banning superintelligent AI. This proposal had previously been written into legislation: in September of this year, Independent Senator Bernie Sanders and Democratic Representative Greg Casar jointly pushed the "Ban Artificial Superintelligence Act," with Democratic lawmakers including Ansari and Ro Khanna joining as co-sponsors. The bill requires pausing the training, modification, and fine-tuning of advanced AI systems with training compute reaching 10²⁵ operations, and prohibits the deployment of similar unreleased systems, until a newly established federal AI regulatory agency formulates safety rules; for superintelligent AI with capabilities exceeding humans, a permanent ban is required. Democrats are expected to control both chambers in January 2027, but the party has not yet unified on the scope and duration of the pause or whether to permanently ban superintelligence; even if the relevant bill passes both chambers, it could still face a presidential veto.

At the individual stock level, Qualcomm reported quarterly results after the close on November 4, with revenue and earnings per share slightly beating expectations, but its guidance for next-quarter profit was weak, mobile phone chip revenue declined year-over-year, and the stock fell significantly after hours and the next day, further weighing on semiconductor sentiment. The market is also awaiting Nvidia's earnings report around November 17, viewing it as a key checkpoint for testing the narrative around downstream orders and capital expenditure. Overall, this round of AI market correction was driven by a combination of multiple factors—questions over returns and financing, earnings guidance shocks, interest rate and valuation repricing, and post-election infrastructure and regulatory expectations. The intraday decline on November 5 reflects a concentrated release of the above concerns rather than a single news catalyst.