Morgan Stanley (MS) predicts that Tesla’s supercomputer, Dojo, could bring the automaker’s enterprise value up to $500 billion.
In a recent note to investors, MS analyst Adam Jonas increased TSLA’s price target from $250 to $400 per share. The investment bank is upgrading Tesla’s rating to Overweight from Equal-Weight and making TSLA stock its “Top Pick.”
Morgan Stanley reasoned that Tesla is genuinely both an auto and tech company. The investment bank has the impression that Tesla might start functioning more like a tech company, resulting in software and services being its biggest source of revenue.
MS attributed Tesla’s growth as a tech company to Dojo, the supercomputer that trains the company’s Full Self-Driving (FSD) System. In his note, Adam Jonas and his team discuss the significance of Tesla’s progress with Dojo, comparing it to the work of other tech companies.
“While it is difficult to explicitly validate the many claims Tesla has made about Dojo’s cost and performance, we believe Tesla has a chance of bringing forth a competitive customized solution given the company’s innovation track record and capabilities,” concluded Morgan Stanley analysts.
MS thinks Tesla can tap into other industries with Dojo. The investment bank also believes Dojo could significantly impact the company’s value considering its upcoming autonomous robotaxis and Tesla Network Services.
“Our bull case valuation is raised to $550 (vs. $450). And our bear case valuation is raised to $120 (vs. $90). Within our forecasts and valuation, we express the potential of Dojo through our raised assumptions, primarily for Tesla Mobility (autonomous robo-taxis) and Tesla Network Services (SaaS Business derived from Tesla vehicles and 3rd party customers in the form of faster adoption and higher ARPU,” wrote Morgan Stanley analysts in their note.
In June, Elon Musk shared that Dojo has been online and running for a few months. Musk has also hinted that Dojo could apply to more than Tesla FSD.
“This is not intended to be just limited to Tesla cars. Those of you who’ve seen the Full Self-Driving beta can appreciate the rate at which the Tesla neural net is learning to drive. And this is a particular application of AI, but I think there’s more applications down the road that will make sense,” he said.
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