Lu Zhang on the Signals and Noise in the AI Investment Boom

By Finance News On Sep 24, 2026

Hyperscalers continue to ramp up capital expenditure forecasts and order backlogs, escalating spending on AI infrastructure to record levels.

According to Goldman Sachs’ (NYSE:GS) research, AI-related issuers now account for a quarter of all new US investment-grade corporate debt this year, pushing the firm to raise its 2026 issuance forecast to US$2.3 trillion, up from US$2.1 trillion at the start of the year. The most creditworthy companies have grown capital spending by at least 35 percent year-over-year for ten straight quarters, and AI-related borrowers now drive nearly half of all convertible bond issuance.

While the underlying demand for compute is real and structural, Lu Zhang, founder and managing partner of Fusion Fund, described the market’s signal-to-noise ratio as “really low”, making it difficult for investors to separate the conviction from the hype.

Stress testing the AI thesis

The market has delivered a run of real tests in the final weeks of Q3. Most recently, AI-linked stocks sold off alongside a broader risk-off move in mid-September before reversing as oil eased and bond yields fell.

Sell-offs have recurring narratives including doubts over whether AI spending reflects real demand or circular vendor financing, warnings from AI’s own leaders that development itself may need to slow and analysts flagging historical bubble-peak signals.

Hyperscaler Q2 earnings, while beating estimates on the surface, raised some red flags. Capital spending grew roughly three to four times faster than revenue last quarter for Microsoft (NASDAQ:MSFT), Alphabet (NASDAQ:GOOGL), Amazon (NASDAQ:AMZN) and Meta Platforms (NASDAQ:META). Free cash flow also fell – Meta’s collapsed by more than 90 percent, Amazon and Oracle (NYSE:ORCL) both went negative, with Oracle falling by close to US$24 billion.

NVIDIA (NASDAQ:NVDA) posted real profit, but its own free cash flow still fell by US$27 billion in a single quarter, largely because it’s extending credit to its own customers to help them buy its chips, while Amazon’s profit beat came mostly from a paper markup on its Anthropic stake, not the underlying business.

Meanwhile, Nvidia’s compute guarantee backing OpenAI’s data-center buildout has reportedly shrunk from an initial US$250 billion to US$105 billion, and OpenAI’s own CFO has acknowledged that Nvidia’s investment effectively comes back to Nvidia as chip purchases.

Real demand, or financing dressed up as demand?

According to Zhang, big tech is “very determined” to keep building, willing to fund it with debt and equity rather than cash because losing access to compute to a competitor isn’t a risk they can afford to take.

“They have to invest, regardless (of whether) they like it or not,” she said. Hyperscalers’ own stated logic for spending this aggressively isn’t about near-term unit…