JPMorgan Chase is pushing back on claims that the AI boom is running too hot, arguing that the investment cycle remains early and structurally supported by real demand rather than speculation.
In a new CNBC interview, Sitara Sundar, head of Alternative Investment Strategy at JPMorgan, outlines the bank’s full framework for gauging whether artificial intelligence is drifting toward bubble territory.
She says the bank looks for four specific red flags when evaluating emerging tech cycles.
“There are four things that we tend to look at in terms of our framework to whether or not artificial intelligence is in a bubble. We look at whether or not there is excess capacity or overcapacity and overbuild, what valuations look like and whether or not fundamentals justify that, and also whether there is excess leverage in the ecosystem.
And when we put those components together, we are not yet seeing signs of excess capacity being built. We are not yet seeing signs of excess valuations. They seem to be justified by the fundamentals. We are not yet seeing signs of excess leverage.”
Sundar says the biggest factor that separates today’s AI economy from the late 1990s is the absence of unused infrastructure. The buildup is being driven by demand that is outpacing supply, not by blind optimism.
“On the capacity point I think the biggest thing that I would mention is this: we actually believe that there is probably room to go because we are still in a compute-constrained and power-constrained economy. The demand is very different than what we saw in the late 90s to early 2000s, where there was a lot of fiber optic cables that were not being utilized.”
She notes that what looks like a surge in AI construction is simply the market trying to catch up to overwhelming computing needs.
“We are still at a point in time right now where data center vacancy rates are at multiyear lows, and we are still seeing demand far outstrip supply. So we think that the investment cycle has years to go.”
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