“AI infrastructure beyond Nvidia: where is the real bottleneck — power, memory, or networking?”

I’m building a long-term AI infrastructure watchlist and trying to understand where the market may still be underestimating the bottlenecks.

The names I’m currently researching are:
Eaton (ETN)
Schneider Electric
GE Vernova (GEV)
Arista Networks (ANET)
Micron (MU)

My thesis is:
Nvidia and TSMC are obvious winners.
The next bottlenecks may be power infrastructure, networking and memory.
AI data centers cannot scale without electricity, transformers, switchgear, cooling, networking and HBM memory.
For those who follow these companies closely:
What is the strongest bear case for each?
Which company is most overvalued today?
Which company has the highest probability of disappointing over the next 3 years?
If AI capex slowed by 30-40%, which of these would get hit hardest?
Which one is the most misunderstood by the market today?

I’m not looking for price targets or short-term trades. I’m interested in understanding where the thesis could be wrong.