The hype train for Artificial Intelligence is full steam ahead but financial experts and researchers are disagreeing about its financial returns. AI is being touted as the current golden child in the tech sector where it has been the financial boon for NVIDIA and its CEO Jensen Huang causing virtually every other tech manufacturer to jump into the pond, along with their investors but some are becoming concerned that that financial returns may not be all they’re cracked up to be.
A report from Goldman Sachs states that over $1 trillion is expected to be spent on AI in the following years but then venture capital firm Sequoia Capital, per Tom’s Hardware, has said the industry will need $600 billion annually just to break even with its investments. A massive stock sell-off occurred this week on July 11 that was tagged the event as a ‘wake-up call’ as financial experts warn of a potential impending bubble burst for the AI industry.
Per Investor’s Business Daily:
“Yesterday was the wake-up call many expected and wanted in order to start taking at least some profits in Mag 7 tech and semi AI winners,” Mizuho Securities trading-desk analyst Jordan Klein said in a client note Friday.
“Yesterday’s semi sell-off (was) a quick preview of what is to come when Nvidia finally guides only ‘in line’ or misses the whisper (number) by a real amount,” Klein said. “Yes, that day will eventually happen.”
NVIDIA and other stocks did, somewhat, bounce back on Friday as is typical of corrections during changes in the market but the event was well noted. The report from Goldman Sachs exposed division among its own teams as some believe the AI industry is going through expected growth patterns while others are doubtful that financial returns for AI are limited due to it being unable to solve meaningful complex problems more efficiently than present technology. Estimates for output from AI in the report are at 9% productivity increase with a GDP increase of 6.1% but MIT Professor Daron Acemoglu sharply disagrees with an estimate of 0.5% and 1%, respectively.
Per Goldman Sachs:
“The forecast differences seem to revolve more around the timing of AI’s economic impacts than the
ultimate promise of the technology. Generative AI has the potential to fundamentally change the process of scientific discovery, research and development, innovation, new product and material testing, etc. as well as create new products and platforms. But given the focus and architecture of generative AI technology today, these truly transformative changes won’t happen quickly and few—if any—will likely occur within the next 10 years.”
Jim Covello, Head of Global Equity Research at Goldman Sachs, also shared concerns with the expected costs to develop AI. Covello explains that the gains will depend on how AI is used.
“My main concern is that the substantial cost to develop and run AI technology means that AI applications must solve extremely complex and important problems for enterprises to earn an appropriate return on investment (ROI). We estimate that the AI infrastructure buildout will cost over $1tn in the next several years alone, which includes spending on data centers, utilities, and applications. So, the crucial question is: What $1tn problem will AI solve? Replacing low wage jobs with tremendously costly technology is basically the polar opposite of the prior technology transitions I’ve witnessed in my thirty years of closely following the tech industry.”
The future looks so bright
However, some experts believe that AI is moving forward at a good pace and is even gaining traction as its technology progresses. This could be thought of as a water-is-wet analogy but technology doesn’t always manage to deliver on promises made by its engineers, designers, or investors. Time, supply chains, manufacturing processes, and more, can play crucial factors in getting things off the ground and running. Kash Rangan, Senior Equity Research Analyst at Goldman Sachs shares optimism for current investments and notes the differences with it compared to previous missteps made in the 1990s.
“Leading the late-1990s investment cycle, by contrast, were companies that didn’t have the financing, reputation, or knowledge to succeed, resulting in a tremendous amount of underutilized capacity. The companies spearheading the current investment cycle are also run by very capable managements, with CFOs watching expenses like a hawk, holding companies accountable for the return on investment, and standing ready to tap the brakes on spending if the returns disappoint. Of course, this could all still fail, resulting in the loss of tens of billions of dollars in capex and interest income. But the opportunity costs of pursuing these strategies despite unknown outcomes still seems small compared to the potential opportunity of building the foundation for the next big computing architecture”