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Goldman Sachs

72%credibility0 / 0 / 0

Why this score Global investment bank; its Research division produces institutionally rigorous macro/capex analysis, tempered by sell-side incentives around the AI-trade narrative.

Tracked statements

4
? unverified
The AI investment boom has accounted for nearly half of S&P 500 earnings growth this year, and this tailwind should begin to fade next year even as capex spending continues to grow.

Resolves once calendar-2027 earnings are reported. Goldman gives ‘nearly half’ for 2026 and no exact share, so the comparison will rest on its own later decomposition or a comparable one.

state of ai/the money·source ↗

? unverified
Named investors called AI-era markets a bubble: Ray Dalio saw 'classic signs' of one reminiscent of 1929 and 2000 and agreed with Jeremy Grantham that this is 'the biggest investment bubble in American history'; Goldman Sachs's Peter Oppenheimer partly dissented — 'there does not appear to be a valuation bubble … there may be an earnings bubble' — while Apollo's Torsten Slok declared 'the 60/40 portfolio is broken.'

The speakers set no fixed date; this standing bubble call is tracked against its named indicator, the equity-issuance and IPO surge — SpaceX (public and trading below its first-trade price), Anthropic and OpenAI (both reported eyeing near-$1 trillion listings). The 2027-12-31 resolveBy is a charitable concrete reading, not the speakers' own. Unverified at capture.

state of ai/the money·source ↗

? unverified
While the exact magnitude and mix of future debt issuance from the hyperscalers is uncertain, our review of management commentary leaves us expecting a growing role for debt financing in the AI buildout in the years ahead.

Still open. Bank of America counts $184.5 billion of dollar bonds from hyperscalers to 24 September and $71.8 billion more in other currencies, against Goldman’s $250 billion for 2026 — but the two counts cover different issuers and bond types. The debt-share-of-capex limb remains unmeasured.

state of ai/the money/debt and credit·source ↗

? unverified
Generative AI could expose the equivalent of ~300 million full-time jobs to automation globally.

Exposure (tasks automatable), not displacement (jobs lost); the two are routinely conflated in coverage. Not tagged as a scorable prediction because 'exposed' has no agreed observable that settles it.

state of ai/societal impact·source ↗