Wells Fargo Raises S&P 500 Target to 7,950, Sees AI Bull Market Continuing
N.R. Finch
Wells Fargo raised its year-end S&P 500 target to 7,950, with chief equity strategist Ohsung Kwon citing falling oil prices and accelerating AI capex — a signal that the tech-led bull market is far from over.
Why raise the target now?
Wells Fargo sees two conditions in place: market sentiment has reset after a modest pullback, and the macro backdrop is stabilizing.
This means → the bank reads the recent dip as a pause within an uptrend, not a reversal. Kwon's line: "The directional path for equities remains higher."
The new 7,950 target implies roughly mid-single-digit upside from current levels.
Why is falling oil the key catalyst?
Oil has pulled back to around $70. Kwon expects this to push inflation lower over the next two months.
In plain terms = oil is one of the economy's master cost inputs — cheaper oil drags down transport and manufacturing costs, which makes inflation data look better almost mechanically.
Lower inflation opens the door for Fed rate cuts, providing a floor under equities broadly.
Should markets worry about a hawkish Fed?
Kwon argues the market is over-reading the Fed's recent hawkish tone, calling the central bank "actually more balanced than the market perceives."
He concedes, however, that the Fed's net-hawkish stance creates headwinds for the "broadening trade" — the rotation of capital from tech into other sectors.
This means → sector rotation is unlikely to materialize near-term; capital will probably stay concentrated in tech.
Where exactly is Wells Fargo positioned?
The bank maintains an overweight on the tech sector, favoring what Kwon calls "capex beneficiaries" — specifically semiconductors and AI infrastructure companies.
The case rests on continued AI infrastructure spending by Alphabet, Meta, and other hyperscalers, with orders still growing.
Kwon: "I think the AI bull market is likely to continue to advance."
Cheaper AI models — won't that reduce compute demand?
The market fears that a shift to lower-cost AI models will shrink compute demand. Kwon sees the opposite.
In plain terms = cheaper models → more companies can afford to deploy them → total compute usage rises. This reflects AI adoption still being in its very early stages.
He also notes that during the recent volatility, semiconductor and AI-infrastructure stocks rallied while other sectors fell — "I don't see a lot of stress in the equity market right now."
What is the key test for this bull case?
One verification point matters above all: whether AI capex actually converts into revenue growth at semiconductor companies.
This means → if the next few quarters show slowing AI-related revenue at names like Nvidia and Broadcom, this bullish thesis faces a direct challenge.
Put simply, the money has been spent — now it needs to show returns. That is the hard constraint on whether this bull run can last.
Content is for reference only, not financial advice.