Goldman Sachs: Is there "too much spend, too little benefit" in AI craze?

Investing.com -- Tech giants and other firms are set to spend roughly $1 trillion in the coming years on developing their artificial intelligence capabilities, including investments in data centers, chips and other AI-related infrastructure, according to analysts at Goldman Sachs.

But they argued that these expenditures have so far failed to yield much "beyond reports of efficiency gains" among AI developers, while Nvidia (NASDAQ:NVDA) -- the Wall Street darling and focal point of the craze around the nascent technology -- has seen its shares "sharply correct."

To explore whether heavy corporate spending on AI will deliver meaningful "benefits and returns," the investment bank spoke with a series of experts, including Daron Acemoglu, a professor at the Massachusetts Institute of Technology who specializes in economics.

AI spending's potential impact on productivity

Acemoglu took a largely skeptical stance on the outcome of the capital rush, estimating that only a quarter of AI-related actions will be "cost-effective to automate" within 10 years -- implying that AI will effect less than 5% of all tasks.

"Over this [10-year] horizon, AI technology will [...] primarily increase the efficiency of existing production processes by automating certain tasks or by making workers who perform these tasks more productive," Acemoglu told Goldman Sachs. "So, estimating the gains in productivity and growth from AI technology on a shorter horizon depends wholly on the number of production processes that the technology will impact and the degree to which this technology increases productivity or reduces costs over this timeframe."

However, he predicted that there will not be a "massive" number of tasks that will be impacted by AI in the near term, adding that most actions humans currently perform -- such as manufacturing or mining -- are "multifaceted and require real-world interaction." Instead, Acemoglu said he expects AI will have the biggest influence in the coming years on "pure mental tasks," adding that while the amount of these actions will be "non-trivial" it will not be "huge."

Ultimately, Acemoglu forecast that AI will increase U.S. productivity by only 0.5% and bolster overall economic growth by 0.9% over the next decade.

AI's "limitations"

Acemoglu added he was "less convinced" that Big Tech's plans to greatly increase the amount of data and processing power they plug into AI models will lead to faster improvements of these systems.

"Including twice as much data from [social media platform] Reddit into the next version of [OpenAI's chatbot] [ChatGPT] may improve its ability to predict the next word when engaging in an informal conversation, but it won't necessarily improve a customer service representative’s ability to help a customer troubleshoot problems with their video service," he said.

The quality of data is also crucial, Acemoglu noted, flagging that it remains unclear what will be the major sources of high-end information or whether it can be obtained "easily and cheaply."

Finally, he warned that the current architecture of AI technology itself "may have limitations."

"Human cognition involves many types of cognitive processes, sensory inputs, and reasoning capabilities. Large language models (LLMs) today have proven more impressive than many people would have predicted, but a big leap of faith is still required to believe that the architecture of predicting the next word in a sentence will achieve capabilities as smart as HAL 9000 in '2001: A Space Odyssey,'" Acemoglu said, referring to the fictional artificial intelligence character in a popular 1960s science fiction film.

An AI "bubble" or a "promising" spending cycle?

The Goldman Sachs analysts assumed a mixed approach to the crush of spending on AI, with some saying the technology has yet to show it can perform the complex problems needed to justify the elevated expenditures.

These researchers also said they do not anticipate that AI costs will ever decline to such an extent that it will be affordable for companies to automate a large portion of tasks. Fundamentally, they said the AI story that has driven an uptick in the benchmark S&P 500 so far this year is "unlikely to hold up."

Despite these concerns, other Goldman Sachs analysts took a more optimistic stance, forecasting that AI could lead to the automation of a quarter of all work actions. The current uptick in capital expenditures, they argued, seems "more promising" than prior spending cycles because "incumbents with low costs of capital and massive distribution networks and customer bases are leading it." They also predicted that U.S. productivity would improve by 9% and economic activity would grow by 6.1% cumulatively in the next decade thanks to AI advancements.

Overall, however, the Goldman Sachs analysts concluded that there is "still room for the AI theme to run, either because AI starts to deliver on its promise, or because bubbles take a long time to burst."

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