In recent years, artificial intelligence (AI) technology has risen rapidly, and enterprises have increased investment. However, Goldman Sachs released a report in June – “GEN AI: TOO MUCH SPEND, TOO LITTLE BENEFIT?” It pointed out that many enterprises in this field of investment is not proportional to the actual return. This has led to a wide discussion: How can companies maximize the return on their AI investments?

Investment status and challenges

According to Goldman Sachs’s analysis, many companies are currently investing huge amounts of money in AI technology, with capital expenditures expected to reach $1 trillion in the coming years. These investments include data centers, chips and other AI infrastructures. However, the practical applications and returns on these investments often fall short of expectations. Even the stock of the company that has benefited the most so far, NVIDIA, has seen adjustments. This is mainly due to the blind pursuit of technology, the lack of clear strategic planning and specific implementation plans.

According to Dean Acemoglu of MI, only 25% of AI-related tasks will be cost-effective in the next decade, and AI is still expected to affect less than 5% of all work tasks. He is skeptical that technological progress may not be as rapid as expected. Acemoglu’s view reflects the potential limitations of AI applications. Despite the huge investment, enterprises could face disappointment if technology fails to effectively replace human labor. It also means that companies need to be more cautious when applying technology.

Different Views on Future Returns

Despite the pessimistic forecasts, GS economist Joseph Briggs is optimistic about the future of AI. He estimates that AI will eventually automate 25% of work tasks and increase productivity by 9%. However, challenges remain, particularly the need for key inputs such as the availability of chips and electricity.

Briggs’s optimism stems from confidence in technological progress and the potential for labor reorganizations. He believes that as costs gradually decrease, the automation potential of AI will be released. But at the same time, infrastructure shortage may limit the realization of this potential.

Resource Shortages and Economic Impacts

For the growth of AI technology, the supply of chips and power is key. Semiconductor analysts at Goldman Sachs point out that chip demand will exceed supply in the next few years. Especially in high-bandwidth memory and complex packaging technology. Additionally, a surge in electricity demand could exacerbate the problem. Experts estimate that by 2030, promoting new power generation alone will require an investment of US$ 50 billion.

Insufficient power supply capacity may become an important bottleneck limiting the development of AI. Especially when the existing power infrastructure is aging, how to cope with the surge in power demand will be a great challenge for enterprises and policy makers.

Market Prospects and Investment Opportunities

Despite doubts about the long-term potential of AI technology, investors remain optimistic about infrastructure providers. Ryan Hammond, a strategist at GS, said that AI beneficiaries will not be limited to NVIDIA, and utility companies may be the next winners.

As AI continues to develop, the market demand for its infrastructure will continue to rise. Investors need to pay attention to companies that can effectively convert AI spending into economic benefits, especially in the power and chip fields.

Conclusion

The Goldman Sachs report reveals the complexity of corporate investment in artificial intelligence. It also emphasizes the importance of efficient capital utilization and technological maturity. As technology continues to evolve, companies must remain flexible and adjust strategies in timely manner to ensure the return on AI investments is truly realized. Faced with market uncertainty, companies and investors need to conduct an in-depth analysis of the potential and challenges of AI technology in order to take advantage of future competition.

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