Goldman Sachs CEO Warns That AI-Driven Markets Are in ‘Greed’ Territory

Goldman Sachs’ chief executive, David Solomon, delivered a blunt assessment of today’s market mood, arguing that the current wave of artificial intelligence-related financing is happening in a context of “more greed than fear.” The comments, made publicly in early June and widely reported afterward, were aimed at describing how investor psychology has shifted as AI spending moves from technology demonstrations to large-scale, balance-sheet decisions.

Solomon told audiences at the Economic Club of New York that markets are being driven more by appetite for returns than by concern about risk. He framed the environment as one in which capital is readily available, which in turn is pulling companies that need funds toward the market window rather than waiting for clearer indicates on macro conditions or near-term profitability.

A key example, according to the reporting, was Alphabet’s decision to raise roughly $80 billion in equity to fund its AI buildout. Follow-on equity offerings like this are additional share sales after a company has already gone public, and they can be used to finance data centers, chips, networking, and other infrastructure required to run AI models at scale.

Reuters later reported that Alphabet expanded the size of its equity plan to $84.75 billion, underscoring that big investors have so far remained willing to fund AI expansion at unprecedented scale. That larger plan included an at-the-market program, a structure that allows a company to sell shares into the open market from time to time rather than issuing all shares at once.

In Solomon’s view, the size of Alphabet’s raise was not just another deal but an indicator. He described it as a concrete datapoint showing the market can absorb AI-related capital raises at a scale that previously would have drawn more resistance. He also told companies to take advantage of the funding when it is available, pointing to liquidity conditions and investor capacity as the immediate enablers of the current fundraising cycle.

The warnings land at a moment when the AI boom is already reshaping how equity investors allocate attention and capital. In commentary on the same period, analysts and market observers noted that the excitement around AI has pushed some indexes and narratives forward even as risk perceptions remain uneven across sectors. For Goldman, which profits from underwriting and advisory work tied to equity and M&A activity, the current environment has the practical effect of sustaining deal flow, even as valuation questions linger elsewhere in the market.

Still, Goldman’s public messaging did not lay out a specific timetable for a downturn or quantify how large any correction could be. The characterization was more about the balance of emotions and expectations than a forecast. What to watch next is whether forthcoming earnings and guidance from AI-adjacent businesses translate into realized revenue and cash flow, or whether investors begin to demand more proof that the capital being raised is turning into measurable performance.