Fundstrat co-founder and Bitmine chairman Tom Lee stated in a CNBC interview that the recent selloff in AI-related stocks has likely reached its bottom. Lee argued that the market remains constrained by tight supply rather than facing overcapacity, suggesting that demand for AI infrastructure continues to outpace available resources. He acknowledged the difficulty of pinpointing exact market bottoms but emphasized that spending constraints and political opposition are slowing growth without indicating a peak in the AI boom.
Lee cited the cryptocurrency market's reaction to the Binance security breach as evidence that selling pressure may have already dissipated. The hack initially impacted approximately $6.3 billion in assets. While Bitcoin fell about 4% to roughly $76,400 on Friday, with more than $1.3 billion in leveraged positions forcibly closed, Lee interpreted this limited decline as a sign that risk-averse investors had already exited. U.S. spot Bitcoin ETFs recorded their largest daily outflow of October at $643.2 million on the same day.
Despite strong AI demand, chipmakers face earnings challenges due to manufacturing limitations. Intel shares plunged nearly 30% to $65.76 after projecting quarterly revenue of $15 billion to $16 billion, which was below analyst expectations. Although Intel’s data center and AI revenue rose 78% year-over-year to $7.3 billion, production constraints hindered its ability to convert orders into revenue. Binance reported freezing about $3 billion of affected assets to cover losses using emergency reserves.
Tom Lee’s assertion that the AI stock correction has ended relies heavily on a supply-side interpretation of market dynamics, contrasting current conditions with traditional overcapacity cycles. By framing the slowdown as a result of physical and regulatory constraints rather than waning demand, he suggests that valuations remain supported by fundamental scarcity. However, this perspective requires careful scrutiny given the immediate counter-evidence from Intel, where robust order books failed to translate into financial performance due to manufacturing bottlenecks. This disconnect highlights that while demand exists, the operational capacity to monetize it is currently the primary friction point for investors.
The use of crypto market resilience as a leading indicator for broader equity sentiment introduces a layer of complexity to Lee’s thesis. While the relatively contained drop in Bitcoin following the massive Binance hack supports the idea that panic selling has exhausted itself, it also underscores the divergent nature of asset classes under stress. Crypto traders often view volatility differently than institutional equity investors, who may be more sensitive to earnings guidance and macroeconomic headwinds. Therefore, interpreting crypto stability as a proxy for AI stock bottoms assumes a correlation between retail-driven crypto sentiment and institutional-driven tech valuations that may not hold during periods of significant corporate earnings misses.
