US technology and semiconductor stocks are facing growing turbulence as investors reevaluate the potential and risks of the artificial intelligence (AI) sector. After meteoric gains for AI-related equities throughout 2024 and into this year, a wave of profit-taking and mounting skepticism has triggered back-to-back sell-offs across major indices, with the tech-heavy NASDAQ posting its steepest two-day decline in three months.

Big Tech and Chip Leaders Under Pressure

The latest market pullback saw prominent names like Amazon (AMZN) and Apple (AAPL) slipping close to 2% in Wednesday trading, while Google parent Alphabet (GOOGL, GOOG) dropped 1%. Nvidia (NVDA), which has become synonymous with the AI hardware revolution, navigated volatility to close fractionally lower after a 3.5% rout the prior session. Similar downward sentiment hit chipmakers Broadcom (AVGO) and Micron Technology (MU), which fell over 1% and nearly 4% respectively, continuing a trend of losses across the sector.

CoreWeave (CRWV), an AI-focused data center platform serving blue-chip clients such as Microsoft and Meta, has seen its shares decline over 20% in just five sessions. Meanwhile, Palantir Technologies (PLTR), known for its defense and AI analytics work, shed another 1% as enthusiasm cools.

Several “Magnificent Seven” tech stocks—Amazon, Apple, Alphabet, Meta Platforms, Microsoft, Nvidia, and Tesla—are all showing signs of rotation as fund managers rebalance portfolios after an exuberant first half of the year. The S&P 500 Information Technology sector slumped 2.1% this week, while the Philadelphia Semiconductor Index is on track for its worst monthly performance since late 2023.

AI Boom Under Scrutiny Amid Bubble Fears

Recent sentiment shifts have been accelerated by influential research and high-profile warnings. This week, a Massachusetts Institute of Technology (MIT) study revealed that 95% of corporate AI initiatives deliver no measurable financial return. The report—which analyzed results across hundreds of global companies—suggests widespread overexuberance and misallocated capital regarding generative AI experiments. The findings were first reported by Fortune and immediately drew reactions from institutional investors questioning near-term revenue prospects for AI deployments.

Amplifying caution, Sam Altman, CEO of OpenAI—developers of ChatGPT and one of the industry’s key evangelists—publicly acknowledged the possibility of an “AI bubble” in interviews this week, a departure from his previously optimistic stance. Altman commented, “When bubbles happen, smart people get overexcited about a kernel of truth. Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes.” His remarks come shortly after OpenAI concluded a multi-billion-dollar funding round at a rumored valuation of over $100 billion.

DA Davidson analyst Gil Luria described the market movement as a “pendulum swing” away from unbridled optimism, noting that, “AI still has limited applications beyond chatbots and search augmentation.” This echoes a broader Wall Street debate over whether the sector’s runaway valuations have outrun the pace of true commercial adoption.

Market Rotation and Earnings in Focus

The latest sell-off follows a sharp rotation by investors out of AI and growth stocks in favor of sectors with clearer earnings visibility and near-term cash flows, such as healthcare, industrials, and energy. This mirrors historical patterns seen during previous technology bubbles, where early breakthroughs stirred speculation far ahead of widespread, profitable deployment.

Despite these concerns, Q2 and Q3 earnings from Big Tech have largely beat analyst expectations, underscoring continued topline momentum. Alphabet, Meta Platforms, and Amazon all cited AI as a key business driver in their latest conference calls, with incremental revenues coming from cloud infrastructure, ad targeting, and consumer products. Meta (Facebook’s parent) attributed a 13% jump in advertising revenue partially to AI-powered content curation and recommendation systems. Likewise, Microsoft’s Azure division reported double-digit growth, buoyed by rising AI-related enterprise demand.

However, the cost of maintaining pole position is climbing. According to a recent projection, cumulative capital expenditure on AI infrastructure among the top five U.S. tech giants is set to surpass $360 billion in 2025—raising questions over long-term ROI if productivity gains remain elusive.

China, Policy Risks, and the Global Perspective

External shocks are also shaping the AI investment narrative. In January, Chinese AI firm DeepSeek introduced a new language model boasting performance on par or exceeding Western equivalents but at a fraction of the deployment cost. This event triggered a sharp correction in U.S. tech share prices, reigniting debate about sustainable AI margins and the prospect of a “race to the bottom” on cloud compute pricing.

The U.S. policy landscape adds further uncertainty. The Biden administration continues to weigh restrictions targeting advanced chip exports to China, potentially impacting sales for Nvidia, AMD, and other key U.S. semiconductor players. Likewise, more clarity is expected after former President Donald Trump’s policy statements regarding trade and tech towards the November 2025 elections.

Long-term Bulls vs. Cautious Realists

Despite the correction, some strategists argue the AI revolution is just beginning. “We are still in the early days of the AI Revolution—the use cases are about to massively expand as more companies realize the value being driven,” Wedbush analyst Dan Ives wrote in a client note. He suggested that the current volatility offers a long entry point, forecasting that the “tech bull cycle will be well intact for another two to three years given the trillions being poured into AI.”

Conversely, skeptics emphasize the chasm between demonstrable AI-driven revenue and market hype. Many enterprise pilots have failed to materialize into revenue-generating products, reinforcing the MIT study’s conclusions and validating short-term profit-taking by investors.

Looking Ahead: All Eyes on Nvidia

The next major catalyst for AI and semiconductor sentiment will be Nvidia’s earnings report on August 27. As Nvidia powers much of the global AI computing backbone, its forward guidance and commentary on demand trends will shape institutional positioning going into Q4. Investors will also be watching for updates on new product launches, competitive threats from China, and the company’s ability to maintain its pricing power in an increasingly crowded market.

Whether the AI wave proves a generational transformation or another bubble remains to be seen, but for now, the market is clearly demanding more proof of real-world impact before rewarding sky-high growth multiples. Volatility is likely to remain elevated as investors weigh quarterly results, policy headwinds, and new research into the economic value of AI.

Reporting by Laura Bratton. For more on tech markets and the AI sector, follow the latest updates on our technology news page.