Global markets mounted a sharp rebound on February 6, but the damage inflicted across January has been stark: precious metals, bitcoin and broad US equity indices suffered steep declines, while Asian markets pulled back noticeably. Traders and strategists have been searching for a single villain, and the February scramble has largely been blamed on one man — Kevin Warsh, President Trump’s surprise choice for Federal Reserve chair — whose nomination recalibrated expectations about US monetary policy and set off a chain reaction.
Warsh is an unconventional nominee for the post. A Harvard Law graduate with Wall Street experience and a prior stint as a Fed governor (2006–2011), he also brings deep crisis-management credits and close ties to high-net-worth macro investors. Markets initially feared he would champion rate hikes or a continued tight policy stance: his past opposition to QE2 and repeated calls to shrink the Fed’s balance sheet prompted a sharp dollar rally and an “epic” selloff in gold and silver as investors retrenched from traditional inflation hedges.
That narrative, however, misses important nuance. Warsh has argued publicly that the United States may be entering a productivity surge driven by AI that could exert structural downward pressure on prices. He has suggested the Fed should not mechanically keep rates high simply because GDP growth looks strong, invoking the 1990s Greenspan-era playbook when productivity gains helped contain inflation. For market participants who respect his judgment — Warsh spent years advising Stanley Druckenmiller’s family office on how to read Fed rhetoric — a public appearance laying out these views could calm nerves rather than inflame them.
Even as Warsh’s nomination provided an immediate catalyst, it was not the sole cause of January’s rout. A faster-than-expected evolution in generative, agentic AI has forced investors to reassess the durability of the legacy Software-as-a-Service (SaaS) model. The so-called “De-SaaS” thesis — that autonomous AI agents will automate workflows that today sustain subscription software economics — has knocked tens of billions off valuations across names long considered defensive growth franchises, pushing Goldman Sachs’s broad software basket to lose roughly $2 trillion in market value from its peak.
The structural AI story has also fed through to corporate results and capital-allocation debates. Amazon’s post-earnings slump, driven by a sharp fall in free cash flow and a gargantuan $200 billion-plus multi-year AI-capex plan, crystallised investor anxiety about profit dilution as firms race to build cloud and AI infrastructure. That concern is pan‑tech: Google, Amazon and Meta have signalled they will invest heavily in AI, pledging combined investments that run into the hundreds of billions, a scale that tests investors’ patience even as the expenditures are concrete — data centres, GPUs and power capacity — rather than speculative froth.
Cryptocurrencies have fared worst of all. Bitcoin plunged from mid-January highs near $97,600 to roughly $64,000, a decline of about 35%, and is down almost half from its 2025 peak. Warsh’s nomination accelerated selling in a market already suffering from narrative fatigue: the post‑halving ETF inflows, AI-crypto crossovers and other bullish storylines had been priced well ahead of deliverable fundamentals. With gold up strongly in 2025 and central banks continuing to buy, the “digital gold” argument for bitcoin has weakened, while stalled US crypto legislation and high leverage among retail and institutional holders exacerbate downside risk.
What this episode reveals is a market in the midst of structural re-pricing. Short-term volatility was amplified by event-driven moves — a Fed nomination and quarterly reports — but longer-term forces are at work: the interaction of AI as both a productivity force and a value-destroyer for certain business models, the repricing of durable capital expenditure commitments across the tech sector, and a recognition that some speculative narratives had been exhaustively discounted. The next phase will depend on how fast companies translate AI spending into sustainable cash flow, how the Fed and its chair communicate the inflation/productivity trade-off, and whether policymakers clarify the regulatory path for crypto.
For investors and policymakers alike, the immediate task is managing expectations. A public, granular articulation of Warsh’s view on inflation and productivity would likely reduce policy uncertainty. Meanwhile, corporate boards must demonstrate that AI investments will enhance margins or create defensible moats rather than merely escalate capital intensity. In crypto markets, absent stronger regulatory clarity or fresh, credible demand, a prolonged period of mean reversion seems likely before narratives can be rebuilt.