Fears of an AI Bubble Seem Overhyped: A Rebuttal to the Goldman and Sequoia Reports
๐ Abstract
The article discusses the skepticism expressed by Goldman Sachs and Sequoia about the AI-fueled rally for markets and the economy. It analyzes the key points made in their reports, including:
- Generative AI has more use cases around automation and cost reduction than revenue generation
- Efficiency gains from AI will be competed away over time, benefiting consumers rather than companies
- Much of today's AI revenue is not yet sustainable due to various adoption challenges
- Many AI businesses lack defensibility, and AGI is overhyped
The article then presents the author's perspective, which aligns with some of the points made in the reports, but also identifies areas where the author disagrees or sees additional nuance:
- Viable AI use cases are real and near-term, with rapid technology improvements
- Efficiency gains can still benefit incumbents with strong moats
- New AI infrastructure and component companies can benefit
- Consumers will accrue most of the gains, benefiting a wide range of companies
Overall, the article suggests that the economic impact of AI may be primarily about efficiency gains, but the gains to the economy, consumers, investors, and builders will be significant, even if the majority of the returns do not go to the industries where AI has the biggest impact.
๐ Q&A
[01] Skepticism about AI-fueled rally
1. What are the key points made by Goldman Sachs and Sequoia in their reports about the AI-fueled rally?
- Generative AI is overhyped as a driver of market returns because:
- The technology is only being used for efficiency gains, not driving new revenue streams
- The costs and quality of AI technology aren't improving fast enough to drive widespread adoption
- Many of the AI businesses emerging don't have great defensibility, and as a result won't be able to build incredibly valuable new companies
- AGI is overhyped, and there is little evidence that we're heading towards a world where AI accelerates this much
2. What does the author agree with in the logic of these reports? The author agrees with the following points made in the reports:
- Generative AI has more use cases around automation and cost reduction than use cases that generate revenue
- The profit improvements from many cost-reduction initiatives will be competed away over time
- Much of today's AI revenue isn't yet sustainable due to various adoption challenges
3. What does the author think was missing in the logic of these reports? The author believes the reports missed the following points:
- Viable AI use cases are real and near-term, with rapid technology improvements
- A small change in accuracy or cost can push many automation use cases into feasibility
- Efficiency gains can still benefit incumbents with strong moats, and distribution channels will become more valuable
- New AI infrastructure and component companies can benefit
- Consumers will accrue most of the gains, benefiting a wide range of companies
[02] Author's perspective on the economic impact of AI
1. What is the author's base case on the impact of AI on American productivity in the next decade? The author's base case is that there will be a 2-5x surge in American productivity in the next decade as a result of AI, and that we are in the early stages of a sustained shift in markets.
2. How does the author explain the potential beneficiaries of the economic gains from AI, even if it doesn't create new revenue streams for incumbents? According to the author, the beneficiaries would be:
- Consumers, who will reap most of the gains and spend more on a variety of non-AI products
- Incumbents with good moats, who will be able to keep some of the efficiency gains
- Companies that adopt AI ahead of the market, which may be able to use the transition period to deepen their moats
- New infrastructural components for AI use cases
- Investors that systematically back the companies in the second and third categories
3. Why does the author believe there is still an under-appreciation in markets of the long-term impact of AI? The author believes that even though AI's economic impact may just be about efficiency gains, and even though the majority of the returns might not go to the industries where AI has the biggest impact, the gains to the economy, consumers, investors, and builders will be very real.