AI infrastructure explosion Goldman Sachs reshapes TMT investment banking landscape! Bet on the trading torrent of the “era of computing power”

The Zhitong Finance App learned that with the full rise of the global artificial intelligence technology industry and almost all infrastructure business portfolios serving this cutting-edge industry globally, investment banking market leaders, including Wall Street financial giants Goldman Sachs, Morgan Stanley, and J.P. Morgan Chase, are undergoing large-scale restructuring of part of their technology, media and telecommunications (TMT) investment banking business teams.

According to an Asian AI computing power industry chain field research report recently released by Goldman Sachs, demand for AI server clusters is expected to continue to grow strongly in 2026, demand for optical network equipment is also extremely strong, supply growth in the DRAM memory chip market is still moderate, and demand continues to greatly exceed supply.

Some media quoted an internal memorandum as reporting that Yasmine Coupal and Jason Tofsky will lead a new global infrastructure technology business segment, which will be built by integrating Goldman Sachs Telecom (Telecom) with the CoreTech business team. Kyle Jessen will be the head of infrastructure technology mergers and acquisitions (infrastructure technology M&A) business, and will also be responsible for coverage of the semiconductor business segment.

The internal memorandum also shows that another new business segment is Global Internet and Media (Global Internet and Media), and the team will be led by Brandon Watkins and Alekhya Uppalapati. A Goldman Sachs spokesperson confirmed the contents of the internal memorandum disclosed by the media.

Since ChatGPT became popular around the world in early 2023, Wall Street financial leaders, including Goldman Sachs and Morgan Stanley, have been seeking to seize large-scale business investment opportunities in the AI technology industry (including large-scale AI-related mergers and acquisitions, IPOs, etc.); in this industry, companies are investing or financing billions of dollars in AI data centers and injecting large amounts of capital into global AI developers such as ChatGPT developer OpenAI. OpenAI said it promised to invest about 1.4 trillion US dollars in the construction of hyperscale AI infrastructure to support AI training/inference.

Goldman Sachs recently visited core companies in the AI computing power supply chain in Asia and found that demand for AI servers continues to be strong and is expected to continue until 2026. Among them, the AI ASIC computing power cluster led by Google is expected to grow faster than AI GPUs, but the latter will also maintain strong growth, and neither shows any signs of slowing down.

In terms of AI computing power infrastructure suppliers, Nvidia's Rubin architecture series AI GPU computing power clusters are scheduled to be put into operation in mid-2026, and production capacity will rise strongly in the second half of 2026. Goldman Sachs said that core suppliers in Asia specifically pointed out that demand for TPU AI chips provided by Broadcom to Google is growing most rapidly in computing power infrastructure. Demand for optical network equipment continues to be strong, mainly benefiting from significant speed upgrades (such as the final transition to 800Gb to 1.6T) and price increases. Goldman Sachs research also shows that supply growth in the DRAM market is still moderate, demand continues to greatly exceed supply, and traditional DRAM pricing is expected to rise sharply.

Regarding the trend of US stocks in 2026, Goldman Sachs's stock strategist team said that with the widespread application of artificial intelligence technology and the resilience of the US economy, the US stock market will reach a new high next year, and corporate profits are expected to rise by double digits.

A team of Goldman Sachs strategists led by Ben Snider indicated in the latest report that the overall earnings per share of S&P 500 companies are expected to jump 12% next year and increase by a further 10% in 2027. Based on the improvement in profit expectations and the AI boom that will still dominate US stock trading, Goldman Sachs has reiterated the target position that the S&P 500 index will trade at around 7,600 points next year, which means that US stocks still have room to rise by about 10% compared to current levels.

According to the prediction model of the Goldman Sachs strategist team, productivity gains driven by artificial intelligence are gradually being transformed into actual corporate profits, and the adoption of AI core technologies such as the big AI model is still in the early stages, but the penetration of AI into daily operations as reported by large companies so far is significantly faster than that of small enterprises.

Google Gemini 3 has undoubtedly recently set off a new wave of AI applications around the world. Once released, the Gemini 3 series products brought huge AI token processing capacity, forcing Google to drastically reduce the amount of free access to Gemini 3 Pro and Nano Banana Pro, and also imposed temporary restrictions on Pro subscribers. Combined with South Korea's recent trade export data, demand for HBM storage systems and enterprise-grade SSDs continues to be strong, further verifying that “the AI boom is still in the early stages of construction where computing power infrastructure is in short supply.”

According to Wall Street giants Morgan Stanley, Citi, Loop Capital, and Wedbush, the global AI infrastructure investment wave with AI computing power hardware at the core is far from over and is only at the beginning. Driven by an unprecedented “AI inference computing power demand storm”, the scale of this round of AI infrastructure investment, which will continue until 2030, is expected to reach 3 trillion to 4 trillion US dollars.