Goldman Sachs Asset Management's Sung Cho, Co-Head of Technology Investing and U.S. Fundamental Equity, recently conveyed a reassuring message during a discussion with Scott Wapner: the widespread anxiety over AI financing—often triggered by volatile valuations and perceived fragility—is largely exaggerated. The conversation explored the trajectory of AI investments, broader market prospects, and the underlying stability of the sector's capital structure, offering nuanced insights for founders, venture capitalists, and industry professionals navigating this transformative era.
Cho challenged the narrative of an impending AI bubble by analyzing the capital sources fueling the current boom. He emphasized that most AI investments are not reliant on speculative debt but are instead backed by robust internal cash flows from established tech giants. This distinction is critical in understanding the long-term resilience of the AI market.
Quantifying the massive capital inflows into AI, Cho stated, "Considering the total expenditure required over the next few years, we estimate it to be between $700 billion and $1 trillion. What should ease concerns is that 90% of this is funded by operating cash flows." This heavy reliance on internal capital—rather than external debt—highlights a fundamental strength in AI investment, differentiating it from past tech speculation cycles.
The implications are significant: companies are financing their AI ambitions from a position of financial health rather than leveraging themselves into precarious positions. Moreover, even the smaller portion of AI investments funded through debt remains stable. Cho noted that a substantial share of this debt is issued by high-rated entities, explaining, "Only about 10% is debt-funded—and much of that is issued by Meta, whose credit rating surpasses even the U.S. government, with bond spreads tighter than Treasuries." This indicates that AI-related debt financing is concentrated in highly creditworthy firms, not speculative enterprises with shaky balance sheets, further mitigating systemic risk.
Addressing concerns about specific companies like Coreweave (CRWV.US) and Oracle (ORCL.US), which have faced recent market turbulence, Cho clarified that these cases do not reflect weakening AI demand. Instead, they stem from operational challenges or supply chain bottlenecks. "By 2026, funding won’t be the issue," he said. "For Coreweave and Oracle, the problem isn’t demand—it’s supply chain backlogs." This distinction is crucial for investors, as it suggests company-specific setbacks are temporary and solvable rather than indicators of broader industry decline.
Cho’s second key insight revolves around the dynamic and inherently volatile nature of leadership in foundational AI models. Rapid shifts in perceived frontrunners define this emerging market—today’s leader could be overtaken tomorrow. He highlighted the swift changes in investor sentiment and market valuations among top AI players, observing, "Look at how perceptions shifted in 2025 alone: early in the year, Meta was seen as the dominant model; six months later, OpenAI took the lead; and recently, Google has surged ahead in investors’ eyes."
This competitive fluidity, while generating notable stock volatility, reflects fierce innovation battles rather than systemic market weakness. The financial impact is staggering—for instance, Google’s $1 trillion market cap surge over three months was directly tied to its perceived technological edge with Gemini. Such rapid reallocations of investor confidence underscore how leadership perceptions can reshape valuations overnight.
The dynamic environment will persist, with upcoming advancements—like models trained on NVIDIA’s Blackwell architecture in early 2026—likely triggering further volatility and leadership shifts. As innovation accelerates, market participants should expect continuous realignments in perceived dominance.
Ultimately, Cho’s analysis paints a picture of an AI market underpinned by ample capital, primarily sustained through operational cash flows rather than precarious leverage. While competition among leading AI developers will remain intensely volatile, these fluctuations are natural outcomes of rapid innovation, not signs of systemic financial fragility. Though anxieties persist, they appear overstated when examined against the sector’s underlying financial health and demand fundamentals.
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