Analysis of Google's AI Infrastructure Scaling Plan and Market Impact

On November 6, 2025, Google’s AI Infrastructure head Amin Vahdat told employees the company must double its AI serving capacity every six months to meet demand, targeting a

[1]. This announcement came alongside the general availability of Google’s seventh-generation custom AI chip, Ironwood TPU—designed explicitly for large-scale inference and backed by Anthropic’s commitment to use up to 1 million TPUs [2].

Google CEO Sundar Pichai later warned that no company (including Google) would be immune if the AI investment bubble bursts, acknowledging “elements of irrationality” in the market while emphasizing the long-term potential of AI [3]. The plan aims to balance scaling with cost and power neutrality, though Vahdat noted this would require “collaboration and co-design” across teams [1].

• Alphabet (GOOGL)
  : Closed at $299.66 on November 21, 2025, with a +1.09% gain (volume:74.14M, above 36.19M average). This reflects investor confidence in Google’s AI scaling strategy [0].
• NVIDIA (NVDA)
  : Closed at $178.88 on November 21, 2025, with a -1.30% drop (volume:346.93M, above 192.04M average). The decline may signal concerns about reduced reliance on NVIDIA GPUs due to Google’s Ironwood TPUs [0].

The Technology sector posted a modest +0.14631% gain on November 22, 2025, underperforming Healthcare (+1.73%) and Industrials (+1.52%)—indicating mixed sentiment toward AI-related stocks [0].

Metric	Alphabet (GOOGL)	NVIDIA (NVDA)
Market Cap	$3.62T	$4.36T
P/E Ratio (TTM)	29.58	44.28
52-Week Range	$140.53–$306.42	$86.62–$212.19
Volume (Nov21, 2025)	74.14M	346.93M

1. Cost Efficiency
   : Exact cost per inference for Ironwood TPUs vs NVIDIA H100 GPUs.
2. Scaling Feasibility
   : Timeline for Google to achieve cost/power neutrality while doubling capacity.
3. Supplier Impact
   : Percentage of Google’s AI compute that will shift to Ironwood TPUs over 2–3 years.
4. Profitability
   : Long-term ROI projections for Google’s AI infrastructure investments.

1. Google’s CapEx
   : Quarterly reports to track AI infrastructure spending.
2. NVIDIA’s Earnings
   : Calls to assess impact of reduced Google reliance.
3. Ironwood Adoption
   : Third-party customer uptake (e.g., Anthropic’s 1M TPU commitment).

1. AI Bubble Correction
   : Users should be aware that Sundar Pichai warned no company would be immune if the AI bubble bursts, which may significantly impact AI-related valuations [3].
2. Scaling Constraints
   : Google’s target to double capacity every six months faces cost/power challenges—failure to meet targets could delay AI product rollouts [1].
3. NVIDIA’s Market Share
   : Google’s shift to custom TPUs may reduce NVIDIA’s cloud revenue, a key growth driver [2].

• Google’s quarterly AI infrastructure spending updates.
• NVIDIA’s cloud customer retention metrics.
• Ironwood TPU adoption rates by enterprise clients.