Source: Wall Street See News Author: Bu Shuqing.

Under the faith of artificial intelligence, technology giants expect unprecedented scale of AI capital expenditure of up to $1 trillion in the coming years. These investments will mainly focus on key areas such as data centers, chips, infrastructure, and power grids, aiming to lay a solid foundation for the future development of AI.

As global technology giants increase their investment in AI, a Goldman Sachs report reveals the uncertain prospect of AI investment returns.

Goldman Sachs analyst Daron Acemoglu and others released a report on Tuesday that while there were efficiency improvements reported in the developer community, the actual benefits of AI technology are still difficult to grasp. Even companies that benefit the most from AI investment, such as Nvidia, have experienced significant fluctuations in their stock prices, reflecting market concerns and uncertainties over AI investment returns.

In this report, some analysts hold an optimistic view about the long-term economic potential of AI technology, believing that although the "killer applications" of AI have not yet emerged, in the end, it will surpass the current "tools and shovels" stage and produce greater economic returns. However, some analysts are skeptical, arguing that the development of AI technology may not be as rapid as expected, and the cost-effectiveness may not be as attractive as imagined.

Looking forward to the next decade, skeptics predict that AI can only improve US productivity by 0.5%, contributing only 0.9% to GDP growth. Optimistic analysts predict that generative AI will eventually automate 25% of work tasks, increasing US productivity by 9%, and GDP growth by 6.1%.

Despite the huge differences, Goldman Sachs still believes that even if the basic narrative of AI technology cannot stand firm in the capital markets, the AI bubble may still take longer to burst.

"Doubtful voice: AI automation tasks less than 5%"

As one of the skeptics, Goldman Sachs analyst and MIT professor Daron Acemoglu believes that within the next decade, only a quarter of AI-related tasks will be cost-effective for automation, meaning that AI will have an impact on less than 5% of all tasks.

Acemoglu believes that the trend of technology improving over time and costs declining cannot be simply applied to AI. The progress of AI models may not be as rapid or impressive as many anticipate.

He also questions whether AI technology can achieve the most valuable cognitive abilities of humans, especially considering that AI models are usually trained on historical data, which may limit their ability to replicate human complex cognitive abilities.

Acemoglu predicts that within the next ten years, AI will only increase US productivity by 0.5%, and will only contribute 0.9% to GDP growth.

Jim Covello, head of Goldman Sachs global equities research, is even more pessimistic, believing that AI technology is expensive and not born to solve complex problems.

Covello pointed out that compared to the early days of the internet, the cost of AI technology has not shown a trend of decreasing over time, and he doubts that the cost of AI technology will be reduced to the degree necessary to enable automation of a large number of tasks.

"Optimistic view: AI automates 25% of tasks, US GDP increases by 6.1% in the next ten years"

Goldman Sachs analyst Joseph Briggs holds a more optimistic attitude, predicting that generative AI will eventually automate 25% of work tasks and increase US productivity by 9% and GDP growth by 6.1% in the next decade.

Briggs believes that although many AI-related tasks currently do not have cost-effective automation, the long-term potential for cost reduction of new technologies and the possibility of labor redistribution and new task creation will drive more AI automation.

Goldman Sachs' Kash Rangan and Eric Sheridan also maintain enthusiasm for the long-term transformation and return potential of AI. They believe that although large technology companies are investing heavily in AI infrastructure, there is no sign of irrational prosperity.

Rangan emphasizes that the current capital expenditure-to-revenue ratio is not significantly different from previous technology investment cycles, and investors will only reward companies that can monetize AI.

"Development bottleneck: chip and power supply shortage"

Goldman Sachs analysts generally believe that the shortage of chips and power supplies may limit the development potential of AI technology.

Goldman Sachs semiconductor analysts believe that, due to the shortage of key components of high-bandwidth memory technology and chip packaging, chips will limit the growth of AI in the next few years.

The bigger issue is whether the electrical supply can keep up.

Goldman Sachs utilities analysts predict that the popularity of AI technology and necessary data centers will drive a significant increase in electricity demand. However, American utilities companies have hardly experienced any increase in electricity consumption over the past 20 years and are grappling with an aging grid, so they may not be ready for the impending surge in demand.

How long will the AI bubble last?

Despite doubts about the economic benefits of AI technology, Goldman Sachs analysts unanimously agree that even if the fundamental narrative of AI technology ultimately fails to hold up in the capital markets, the AI bubble may take longer to burst.

Goldman Sachs stock strategist Ryan Hammond believes that AI concept stocks have more room to run, and predicts that beneficiaries of AI will continue to expand, not just giant semiconductor companies such as NVIDIA, but also large utilities companies.

In the long run, Goldman Sachs' chief equity strategist Christian Mueller-Glissmann analyzed the impact of AI on the market from a macro perspective.

He found that if AI significantly accelerates economic growth and corporate profitability without exacerbating inflation issues, S&P 500 index’s long-term returns will be higher than average.

However, he warned that realizing the potential of AI technology for investors is crucial to increasing market returns. Although AI may benefit stocks by increasing productivity growth, the market often anticipates this before actual productivity growth is realized, increasing the risk of overpricing.

Editor/Lambor