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Alphabet stock slid Wednesday as investors digested second-quarter results that beat earnings estimates but fell short in other key areas.
The mixed results sent the stock down 5% in Wednesday afternoon trading, but Goldman Sachs analysts say they remain optimistic about the company's artificial intelligence opportunities.
Last quarter, the company saw earnings per share of $1.89 versus estimates of $1.85. Yet, ad revenue from YouTube was weaker than Wall Street expected, at $8.66 billion versus estimates of $8.95 billion. Capital expenditures in the quarter were also higher than expected, at $13.2 billion.
Goldman Sachs was upbeat in its analysis, raising Alphabet's price target from $211 to $217 in a note after the company released earnings. That represents a 25% increase from Wednesday afternoon's price of $172.80.
Goldman says its optimism comes largely from Alphabet's AI opportunity.
"While we cannot refute the continued investor debate around the future of search, we continue to believe that Alphabet is positioned as an AI first company," the analysts noted, adding that the company has existing applications into which it can further integrate its AI tools.
Investors on Tuesday's earnings call seemed worried, though, about the return on such heavy investment in AI. Alphabet's executives fielded numerous questions on the monetization of AI initiatives, including its AI-generated search result summaries and AI integration into it cloud business.
The executives provided no hard numbers and emphasized that the tech giant's AI ambitions will produce long-term returns.
It's "something which I think will end up being a big driver over time," Alphabet CEO Sundar Pichai said regarding AI's integration into its cloud unit.
Pichai also said the company has "over 2 million developers playing around with these things."
Goldman's analysts aren't phased by the potentially long timeline for gains from AI to materialize, but say they expect investors to continue focusing on the future of search, operating margin outcomes, and long-term investments in data centers and technical infrastructure to fuel AI.