EXECUTIVE SUMMARY
Message
Goldman Sachs revisits the debate on generative AI, emphasizing that while the current AI boom is not a bubble, it does present both significant opportunities and risks.
The firm advocates for a balanced investment strategy, warning against overconcentration in tech giants while highlighting the potential for emerging competitors and non-tech industries to capitalize on AI-driven growth.
Key Points
- AI Boom Not a Bubble: Goldman Sachs clarifies that the current surge in AI investments is not irrational but grounded in solid fundamentals, unlike previous tech bubbles.
- Caveats in AI Investment: The report cautions that the intense focus on AI could lead to unrealistic profit expectations, potential overvaluation, and increased vulnerability to market corrections.
- Historical Patterns: AI, like previous disruptive technologies, may follow a boom-bust-recovery cycle, where early innovators might not necessarily be the long-term winners.
- Emerging Competitors: Despite the dominance of current AI leaders, new competitors are likely to emerge, especially from open-source models, challenging the monopolistic hold of the current giants.
- Investment Diversification: Goldman suggests diversifying investments beyond tech, considering second-round effects on consumer behavior and industries outside traditional technology sectors.
Key Statistics
- Global Equity Return: The technology sector has generated 32% of the global equity return and 40% of the US equity market return since 2010.
- Earnings Growth: The tech sector has seen earnings per share (EPS) rise by approximately 400% globally, compared to 25% growth in other sectors since the peak before the Global Financial Crisis (GFC).
- AI Models: The website Hugging Face hosts around 650,000 AI models, indicating rapid growth and the potential for new market entrants.
Overview
Goldman Sachs’ analysis of the generative AI sector reflects cautious optimism. While the current AI-driven market growth is substantial and supported by strong fundamentals, the report highlights the risks of overconcentration and the potential for market corrections as new competitors emerge.
The firm advises investors to diversify their portfolios, recognizing that while current AI leaders may hold significant advantages, historical patterns suggest that true long-term winners often emerge later in the cycle.
Additionally, non-tech industries and sectors that can leverage AI advancements may offer untapped opportunities for growth.
DEEP DIVE
Introduction
Goldman Sachs recently revisited the topic of generative AI (Gen-AI), a sector that has garnered immense attention and investment.
In their latest report, the investment bank delves into the nuances of the AI-driven technology boom, addressing concerns about potential overvaluation, market concentration risks, and the historical patterns that have characterized previous technology cycles.
This analysis provides a balanced view, highlighting both the significant opportunities and the inherent risks associated with the AI sector.
The Current State of AI: Not a Bubble
Goldman Sachs opens by clarifying that the current enthusiasm around generative AI does not resemble a typical speculative bubble. The bank references its June report, titled “Gen AI: too much spend, too little benefit?” and emphasizes that the question mark in the title was deliberate, indicating a cautious exploration rather than a definitive conclusion.
The report points out that the technology sector has played a dominant role in global equity markets over the past decade, contributing to 32% of global equity returns and 40% of the US equity market returns since 2010. This growth, according to Goldman Sachs, is not merely driven by hype but is underpinned by robust fundamentals. For instance, the earnings per share (EPS) of the tech sector have increased by approximately 400% globally, compared to a mere 25% growth in other sectors combined since the peak before the Global Financial Crisis (GFC).
Caveats and Risks: The Double-Edged Sword of AI Investment
Despite the strong performance and potential of the AI sector, Goldman Sachs issues several warnings. The bank suggests that while the sector’s growth is based on sound fundamentals, there are significant risks associated with the current market dynamics. One of the primary concerns is that the compelling narrative around AI could monopolize investor attention, leading to unrealistic profit expectations and potential overvaluation of AI companies. This, in turn, could make these companies vulnerable to sharp market corrections.
The report further notes that disruptive technologies, such as AI, often follow a boom-bust-recovery cycle. In the early stages of such cycles, investor enthusiasm can lead to inflated valuations and a surge of opportunistic companies trying to capitalize on the trend. However, history has shown that only a few players emerge as long-term winners, while many others fail to sustain their initial momentum.
Historical Patterns: Lessons from Past Technology Cycles
Goldman Sachs draws parallels between the current AI boom and previous technological innovations, such as the internet, radio, and the telegram. The report highlights a recurring pattern in which early innovators often receive the most attention and capital investment, but over time, new competitors emerge, leveraging the infrastructure and technology developed by the pioneers.
For example, during the dot-com bubble of the late 1990s, telecom companies were seen as the safest bets to capitalize on the growth of the internet. However, the ultimate winners were not these early players but rather companies that emerged later, such as those in the smartphone and social media industries. These later entrants were able to “free ride” on the investments made by the initial innovators and develop new business models that fully leveraged the potential of the technology.
The Competitive Landscape: New Entrants and Emerging Technologies
The report also examines the current competitive landscape within the AI sector. While the dominant AI companies, such as those involved in large-scale AI model development, currently hold significant advantages, Goldman Sachs notes that new competitors are rapidly emerging. The growth of open-source AI models, for instance, is creating a more competitive environment. The report cites the example of Hugging Face, a platform that hosts around 650,000 AI models, as evidence of the fast-paced development and democratization of AI technology.
Goldman Sachs argues that while the current AI leaders have built protective “moats” around their businesses, these barriers are not insurmountable. The increasing number of patents and innovations in the AI space suggests that new competitors will challenge the existing players, driving down costs and fostering further technological advancements.
Investment Diversification: Beyond Technology
Given the risks associated with overconcentration in the AI sector, Goldman Sachs advises investors to diversify their portfolios. The report suggests that the best way to capitalize on the AI trend may not be by investing solely in tech giants like Nvidia but by considering industries and sectors that can benefit from AI-driven innovations.
Goldman Sachs points to the potential second-round impacts of AI on consumer behavior and non-tech industries. For instance, the widespread adoption of AI could lead to an increased demand for fact-checking services, as well as changes in work patterns that might drive the regentrification of urban neighborhoods. The report also highlights the possibility of a growing market for authentic, nostalgic experiences, as people seek to balance the increasing digitalization of their lives with more tangible, real-world activities.
An example of this trend is the popularity of reality TV shows focused on traditional crafts, such as baking, sewing, and dancing. These “retro” activities tap into a desire for authenticity and human connection in a highly digitalized world. Goldman Sachs suggests that companies and industries that can cater to this demand may offer attractive investment opportunities.
Conclusion: A Cautious Optimism
In conclusion, Goldman Sachs presents a nuanced view of the generative AI sector. While the bank acknowledges the substantial opportunities that AI presents, it also emphasizes the importance of caution and diversification in investment strategies.
The current AI boom, though not a bubble, is fraught with risks, particularly related to market concentration and the potential for overvaluation.
By learning from historical patterns and considering the broader impacts of AI on various industries, investors can better navigate the complexities of this rapidly evolving market.
Goldman Sachs’ final recommendation is clear: diversify your investments. Rather than solely focusing on the AI giants, investors should look to industries that can leverage AI technology to drive growth in new and innovative ways.
Whether it’s through emerging competitors in the AI space or through non-tech sectors that benefit from AI advancements, a diversified portfolio is likely to yield the most sustainable returns in the long run.
