Summary
As generative artificial intelligence (AI) continues to captivate the attention of business leaders and investors, recent sentiments have shifted towards skepticism regarding its potential. Eric Sheridan, a senior research analyst within Goldman Sachs Research focusing on the U.S. Internet sector, posits that while AI holds significant promise as a potential driver of financial performance for technology companies, there remains much uncertainty. During an interview at Goldman Sachs’ Communacopia + Technology conference, Mr. Sheridan emphasized that although the promise of generative AI is substantial, the technology is still in a developmental phase. He noted that historical trends in computing cycles indicate a process where initial enthusiasm is often followed by a period of disillusionment, as companies navigate the transition from building technologies to realizing functional applications. With regards to current investor sentiments, Mr. Sheridan suggested that investors typically seek visibility and predictability, but computing cycles can present periods of instability characterized by what he termed “troughs of disillusionment.” While there has been a marked increase in capital expenditures associated with AI in 2024 compared to previous years, this upward trend may generate volatility due to the uncertainty surrounding technological advancements in the medium to long term. As investors consider the long-term horizon of technological investments, it is imperative to exercise patience, as historical evidence suggests that investing in technology over extended periods has generally yielded positive outcomes. Nevertheless, concerns persist regarding whether AI will deliver transformative applications that significantly alter businesses and the broader economy. According to Mr. Sheridan, current expenditures on AI are primarily concentrated among a limited number of large corporations, who are balancing offensive and defensive strategies in their investments. These firms have indicated a preference for overinvestment in the short term, in order to capitalize on potential opportunities without neglecting the necessity for tangible returns on their investments. The discourse surrounding AI also raises the question of its impact on both established tech giants and emerging companies. Mr. Sheridan highlighted that the entry barriers to AI deployment are notable, as it requires considerable capital investment, engineering talent, and access to vast datasets. Consequently, even innovative startups are forging partnerships with larger incumbents to leverage their resources. If AI indeed emerges as a transformative economic force, a pertinent query is how much value will accrue to technology companies. One anticipated area of benefit lies in computing needs; as AI automates and enhances productivity, organizations may reallocate budgets, redirecting funds typically spent on labor towards computational resources. At present, the understanding of AI’s potential impacts remains rudimentary, with many enterprises still exploring and testing its applications. Mr. Sheridan warned against overconfidence in predictions about AI’s trajectory over the next decade, advocating a probabilistic approach to forecasting its evolution. He noted a recurring oversight among investors in the consumer technology arena—specifically, the underestimation of the advantages inherent in existing large user bases. A company with billions of users possesses a significant edge in deploying consumer-facing AI features in their offerings, ultimately shaping consumer experiences significantly. In conclusion, while the narrative around AI is fraught with uncertainty, it is clear that the development phase is crucial for shaping future outcomes. Investors must remain mindful of the complexities surrounding AI’s integration and its broader economic implications, approaching the landscape with both caution and an open mind for the possibilities that lie ahead.
Original Source: www.goldmansachs.com
Leave a Reply