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Anytime a new technology emerges, investors rush to debate its economic impact and potential to increase corporate earnings. With A.I., that debate is now well under way after enthusiasm over the technology helped the tech-heavy Nasdaq Composite surge nearly 40% in the first half of this year. Some analysts have labeled the run the start of the “A.I. gold rush,” but others warn that investors may be getting ahead of themselves when it comes to highly valued A.I.-linked stocks. These bears argue that the A.I. boom might not pan out as expected, at least for stock market investors, and that could lead to a repeat of the dot-com era bust cycle. But Goldman Sachs analysts aren’t having it, arguing this week that the A.I. hype is justified.
“A.I. probably isn’t in a hype cycle,” Kash Rangan, a software analyst at the investment bank, said in an interview for Goldman’s latest ‘Top of Mind’ publication. “When a unanimous verdict exists among the technology providers that a technological shift is actually happening, it’s real. And when customers start to become interested, it’s not hype. And customers are interested.”
To Kangan’s point, a recent survey from Upwork research of 1,400 U.S. business leaders found that nearly three-quarters (73%) of C-suite executives are actively using generative A.I. at their organizations. And AT&T CFO Pascal Desroches told Fortune’s Sheryl Estrada last month that the telecom giant has already saved “hundreds of millions of dollars” by using A.I. to improve employee efficiency. The company is even in the process of rolling out its own internal generative A.I. tool called “Ask AT&T.” A June Bank of America Research survey also found that 59% of consumers have already used OpenAI’s chatbot, ChatGPT.
Kangan went on to note that unlike past tech hype cycles like the dot-com era, the A.I. boom is being led by some of the largest companies on the planet with huge budgets, not startups. That “makes it less likely to fizzle out or take a long time to get going,” he argued.
“We’re having discussions with the CIOs of global corporations who are amazed at the productivity benefits this technology could bring if deployed internally. And all of this is occurring at a time when the market is rewarding productivity gains. So, this doesn’t feel like a hype cycle,” he said.
The fact that well capitalized big tech firms are leading the A.I. revolution and there is growing evidence for the utility of the technology, both in business and at home, has many experts feeling optimistic. Allison Natan, a senior strategist at Goldman Sachs, who created and edits the firm’s ‘Top of Mind’ publication, spoke to one of those experts, Sarah Guo, founder of the AI-focused venture capital firm Conviction, in her latest piece.
Guo is a true believer in the potential of A.I., and she’s investing accordingly, putting her name behind startups like Noogata, an Israeli firm that is creating A.I. applications for the packaged goods sector, Culture A.I., a cyber security risk management platform, and many more. But even Guo admits that there is a lot of hype these days, and investors need to learn from mistakes made during previous hype cycles.
“The recent lessons across all stages of the technology markets should not be lost on investors. All companies are eventually valued on a multiple of cash flows,” she said, adding that “distinguishing between A.I. marketing and A.I. reality will be hard work for investors” due to the rapidly changing nature of the field.
But Goldman Sachs’ managing director of equity research Eric Sheridan, who previously spent nearly a decade as an analyst at UBS, said the majority of A.I.-linked stocks are still trading at “relatively reasonable multiples” and he doesn’t believe we’re in a bubble.
“While you never know you’re in a bubble until it pops … Bubbles are typically about enterprise value to eyeballs/clicks, addressable market dynamics, or sheer euphoria as a driver of valuations as opposed to what the right multiple on net income is to pay. So, this feels very different from previous tech bubbles,” he said.
