Is the AI bubble about to burst? OpenAI failing to meet internal goals drags down tech stocks and Bitcoin

On April 28, The Wall Street Journal disclosed that OpenAI recently failed to meet multiple internal revenue and new user growth targets, including the milestone of reaching 1 billion weekly active ChatGPT users by the end of 2025. The news quickly spread to the U.S. stock AI concept sector: Oracle plunged by more than 4%, AMD fell 3.4%, Nvidia fell 1.6%, SoftBank Group sank by more than 10%, and the Philadelphia Semiconductor Index overall dropped by more than 3%. Market analysts noted that investors worry this could shake the logical foundation supporting large-scale AI infrastructure spending by tech giants.

OpenAI has signed approximately $600 billion in forward compute capacity purchase commitments. Its CFO Sarah Friar also issued an internal warning: if revenue growth does not meet expectations, the company may struggle to fulfill its massive data center procurement contracts. Bloomberg industry research analysts pointed out that this not only affects OpenAI itself—major deep partners such as Oracle, Microsoft, Amazon, and CoreWeave may also face risks to their financial targets. OpenAI pushed back against the WJS report, but the market has already made its choice through pricing. What this trigger essentially tests is the safety margin of the entire AI infrastructure investment narrative.

How does panic spread from Wall Street to the crypto market?

The sell-off of AI concept stocks did not stop with traditional capital markets. On April 29, after Bitcoin broke below the $79,321 interim high, it continued to slide; within 24 hours, the lowest point reached $75,666. Ethereum simultaneously retested $2,258. According to CoinGlass data, over the past 24 hours, the total amount of forced liquidation across all on-chain contracts reached $189.74 million, with 72,126 people liquidated by force. Long positions accounted for as much as 67.4%.

The transmission mechanism follows two paths. On the macro level, crypto assets and the Nasdaq 100 index remained highly synchronized over the past quarter, #近一月维持近乎完美的联动轨迹#, reflecting their risk exposure management framework as technology risk assets being included in the same investment portfolio. On the psychological level, the market fear and greed index dropped to 26, entering the «deeper fear» range, and Bitcoin was directly pressured by the spillover of sentiment driven by valuation doubts about U.S. AI big tech. When risk appetite concentrates and contracts, high-beta crypto assets are often hit first.

Why does the same news cause divergence between AI concept stocks and AI crypto tokens?

A notable divergence is that: while the traditional AI concept stocks are generally under pressure under the same “AI” narrative, some AI-sector crypto tokens have recorded gains against the trend. According to SoSoValue data, on April 29, the AI sector in the crypto market overall rose by 0.96%. In it, Bittensor (TAO) rose 4.2%, Unibase (UB) rose 18.84%, and SkyAI (SKYAI) rose 35.11%.

The root of this divergence lies in differences in investment logic. The valuations of tech stocks are highly tied to the visibility of orders from a small number of top companies (such as OpenAI) and their ability to realize profits, #一旦下游需求预期松动#. As a result, the valuation anchor across the entire industry chain shakes. Meanwhile, most AI crypto projects focus on the decentralized compute market, distributed machine learning networks, or AI agent payment infrastructure, whose core logic is “replacing centralized AI infrastructure.” When OpenAI exposes centralization risks, these projects are revalued instead. The open machine learning network built by Bittensor and the decentralized GPU compute market of Render Network essentially create distributed competition against OpenAI. This round of divergence is an indirect market pricing of the narrative of «distributed opposition to centralization.»

Beyond risk aversion, structural characteristics within the crypto market are also diverging

Price correlation does not mean that different segments of the crypto market move in the same direction. In this adjustment, as the crypto asset with the strongest liquidity, Bitcoin was hit most directly, while major coins such as Ethereum, SOL, and XRP also weakened in tandem. SOL traded at $84.02 during the day, about 6.9% down from its recent peak. XRP was consolidating around $1.383, still hovering above earlier support levels. At the same time, the GameFi sector rose 0.4%, indicating that capital is being reallocated across different narrative sectors rather than exiting the market entirely.

From the structure of the derivatives market, #多单爆仓占比 67.4%# suggests that the decline this time was driven more by the passive liquidation of leveraged long positions, rather than by systematic suppression from active shorting forces. This structure is relatively common during the deleveraging phase after a risk event is triggered, but it does not mean that a trend reversal signal has already been established.

How do macro liquidity factors and AI risk events combine to create resonance?

AI news is not the only variable behind this crypto market pullback. On the macro level, the FOMC meeting on April 28 to 29 falls within a sensitive window. The CME FedWatch tool shows that the probability the market assigns to interest rates staying in the 3.5% to 3.75% range through April is 100%. PCE inflation is 2.8%, core is 3.1%, both staying elevated, and expectations for rate cuts continue to be suppressed. In addition, geopolitical tensions in the Middle East are pushing up oil prices, further weakening the likelihood of short-term liquidity easing.

Several negative signals overlap highly within the time window, forming a «three-factor resonance»: AI valuation restructuring triggered by OpenAI’s earnings warning, FOMC holding steady to suppress liquidity, and the ETF flows weakening as they recently saw single-day net outflows of $243 million. This resonance amplifies the effect of a single shock, causing risk-averse sentiment to spill out in a concentrated way.

Is AI bubble risk a long-term tail risk for the crypto market?

Tether CEO Paolo Ardoino previously listed AI bubble risk as the «biggest risk» for Bitcoin in 2026 at the end of 2025. He noted that Bitcoin is still “too highly correlated with capital markets,” and if the AI investment boom ultimately evolves into a situation where a stock-market bubble bursts, crypto assets will be hard to stay immune. Traders on Polymarket currently price in about a 24% probability of an AI bubble bursting in 2026.

The more fundamental logic is that the AI infrastructure investment boom over the past two years attracted a large amount of institutional capital, and the risk exposure management logic of that capital is #跨资产类别的相关性回溯#. When capital expenditure return expectations in the AI space face systemic doubt, #最敏感的敞口未必是估值最高的中概成分# is not where it should be—rather, it is precisely the high-risk assets with the best liquidity and the highest leverage, which is the crypto market, that sit at the origin point of this coordinate.

Is the real value of the AI narrative for the crypto ecosystem being masked by short-term volatility?

OpenAI’s revenue difficulties do not equal failure of the AI technology roadmap, and they do not equal the end of the Crypto x AI narrative. In fact, the deep integration between AI and the crypto industry has accelerated over the past 18 months. Structural innovations such as decentralized compute markets (DePIN), AI agent payment infrastructure, and cross-verification technologies for on-chain smart contracts and AI inference are all being implemented in practice. According to industry research, in 2022 only 14% of crypto companies were building AI-related projects; by 2025, that figure had jumped to 27%. The Web3 AI agent market size has reached $7.81 billion.

#长期来看#, the growth bottleneck faced by centralized AI giants does not mean an end to the Crypto x AI narrative; it may instead accelerate the adoption of decentralized intelligent solutions. The three pain points of AI compute mismatch economics, opaque validation, and concentrated usage rights are addressed by crypto technology. The core significance of this market adjustment is to help the market distinguish #叙事热度# from #产品适配度#. This process is a necessary path for any emerging technology to move from the period of inflated innovation expectations to the stage of mature productivity.

Can the market re-anchor value amid volatility?

From a broader perspective, this round of pullback is a stress test of the AI valuation system. It exposes the core question: when #需求增长曲线不如预期陡峭#, #资本支出计划遭遇资金可持续性质疑#, and #跨资产风险溢价同时面临宏观压制# face triple pressure, #市场定价能否承受同步修正#. In the past 24 hours, the leading signals that the crypto market needs to watch include whether Coinbase Premium can turn from negative to positive, whether ETFs can resume net inflows, and whether the earnings reports of major AI concept stocks can stabilize expectations. For the long-term Crypto x AI narrative, separating truth from falsehood amid volatility is exactly a necessary step for market maturity. The evolution of technological trends never relies on a single linear growth path, and short-term market corrections do not change the underlying logic of structural coupling between distributed intelligence and blockchain ledgers.

Summary

OpenAI’s revenue warning event reveals increasingly strong risk linkage between crypto assets and technology stocks. There are four factors creating resonance in the current market: a phased revaluation of AI valuation logic, accelerated transmission of panic across markets, overlapping suppression from macro liquidity and geopolitics, and the fragility of the leverage structure within the crypto market. However, the divergent performance of AI sector tokens and AI concept stocks shows that the long-term value of the distributed AI infrastructure narrative has not been completely falsified by short-term volatility. For the crypto market, the deleveraging process amid volatility is a necessary condition for risk clearing, and also an essential stage for long-term pricing of the structural narrative of “decentralized intelligence.”

FAQ

Q: How long will OpenAI’s revenue warning affect the crypto market?

The deciding factors for how long the impact lasts are whether, in the coming months, the future financial reports of AI giants show further revisions to capital expenditure expectations, and whether the earnings seasons of major tech stocks can stabilize the market’s judgment about AI investment returns. In the short term, the crypto market may still fluctuate in line with tech stock earnings data.

Q: Are the gains in AI-sector crypto tokens sustainable?

The rise in AI-sector crypto tokens against the trend reflects a revaluation of value between distributed and centralized AI. However, the valuation of this sector still depends heavily on the progress of technology implementation and actual adoption rates. Short-term divergence does not mean that long-term trends are independent. Investors should focus on fundamental indicators such as the project’s mainnet progress, compute capacity deployment, and developer activity.

Disclaimer: This article is for reference only and does not constitute investment advice. Digital asset trading involves a high level of risk. Please make prudent decisions based on your own risk tolerance.