3 Magnificent AI Stocks to Buy Before the Anthropic IPO

Anthropic is now valued at $965 billion, with a recent S-1 filing adding to IPO interest, but the article argues investors can already access its AI growth indirectly through Alphabet, Amazon, and Microsoft. Amazon has committed more than $100 billion over a decade to AWS capacity and invested $5 billion in Anthropic, Alphabet has pledged up to $40 billion, and Microsoft has committed up to $5 billion alongside a $30 billion Azure capacity deal. The piece is bullish on the hyperscalers as a lower-volatility way to gain exposure to the same AI tailwinds driving Anthropic.

Analysis

The real economic winner here is not the frontier model vendor; it is the pick-and-shovel layer that turns AI hype into contracted, high-utilization infrastructure demand. This creates a subtle but important asymmetry: hyperscalers get recurring revenue and capital recycling optionality, while the private lab remains structurally dependent on the same three firms for compute, distribution, and funding. That means the public-market AI trade is becoming less about model-share and more about who can lock in long-duration capacity at the lowest marginal cost.

Second-order, this is bullish for custom silicon and internal cloud utilization metrics, but it also raises the risk that capex intensity stays elevated longer than consensus expects. If these deals keep scaling, the market may eventually punish any sign of under-earning on cloud margins, because investors will start capitalizing AI infrastructure commitments as quasi-financed receivables rather than optional growth. In that regime, Amazon has the cleanest relative setup if it can prove Trainium/Inferentia are actually displacing third-party accelerator spend, while Microsoft is more exposed to Azure capacity absorption risk if demand growth slows.

The contrarian read is that the headline enthusiasm may already be partially arbitraged into the hyperscalers, while the private lab itself is still mostly a venture-style outcome with binary IPO timing risk. The better trade is not chasing the IPO narrative, but buying the public names that monetize the same compute stack across multiple customers. Near term, the catalyst path is earnings guidance and capex commentary over the next 1-2 quarters; the main reversal risk is that AI spending broadens slower than infrastructure bookings, forcing a re-rating of “growth” into “bloated capex.”

Key Decisions for Investors

• Overweight AMZN vs. GOOGL and MSFT on a 3-6 month horizon: best risk/reward if AWS custom silicon adoption translates into higher gross profit dollars per AI workload; add on any post-earnings pullback tied to capex fears.
• Use a GOOGL/AMZN pair trade over 1-2 quarters: long AMZN, short GOOGL if the market continues to reward direct cloud monetization over more diffuse AI optionality; tighten if Alphabet demonstrates stronger TPU-driven margin expansion.
• Hold MSFT only as a relative-quality AI beneficiary, not the highest-beta expression: upside is more dependent on sustained Azure capacity uptake, so use call spreads instead of outright equity for 3-6 month exposure.
• Sell volatility into any Anthropic IPO-related ripples: the better way to express the theme is via the hyperscalers, so use short-dated covered calls on AMZN or MSFT after enthusiasm spikes to harvest premium while keeping core exposure.
• Do not chase NVDA on this headline alone: the article supports demand persistence, but the trade has shifted toward infrastructure owners; wait for evidence that incremental compute demand is accelerating before adding accelerator beta.